Home

Dynamic distributed-sensor thermostat network for forecasting

1. Did the event occur yes or no and the second adjustment may be more useful when determining a continuous condition e g Where was the center of the event The adjustment can be identified by e g looking up an identifier e g a device or sensor identifier in a look up table The look up table can include one or more adjustments for the identifier These stored adjustments may have been previously determined e g by weight adjustment assigner 508 e g by analyzing past sensor data points with respect to known event properties by considering whether a particular device s sensor data points reliably co varied with other nearby device s sensor data points and or by assessing vari ability across past sensor data points In some instances a single look up table stores both weights and adjustments In some instances different look up tables store weights and adjustments It will be appreciated that in some instances the adjustments are stored in multiple look up tables e g each relating to a different event property At block 815 the weighted and or adjusted sensor data points are fitted e g by inter device correlator 510 The fit could involve fitting a one dimensional two dimensional or multi dimensional function The function can include con sist of e g a power function a logarithmic function a Gaus sian function and or a trigonometric function One or more parameters can be identified as a r
2. 5 533 668 A 7 1996 Erikson 2005 0189429 1 9 2005 Breeden 5 544 036 A 8 1996 Brown Jr et al 2005 0194456 1 9 2005 Tessier et al 5555927 A 9 1996 Shah 2005 0270151 Al 12 2005 Winick 5 595 342 1 1997 McNair et al 2005 0280421 Al 12 2005 Yomoda et al 5 611 484 3 1997 Uhrich 2006 0105697 1 5 2006 Aronstam et al 5 635 806 A 6 1997 Tinsley et al 2006 0149395 Al 7 2006 Archacki et al 5 644 173 A 7 1997 Elliason et al 2006 0186214 Al 8 2006 Simon et al 5 646 349 7 1997 Twigg et al 2006 0196953 1 9 2006 Simon et al 5761083 6 1998 Brown Jr et al 2006 0208099 9 2006 Chapman et al 5 802 467 9 1998 Salazar et al 2007 0052537 Al 3 2007 Stults etal tes 340 540 5 839 654 11 1998 Weber 2007 0114295 1 5 2007 Jenkins 5 902 183 5 1999 D Souza 2007 0131787 1 6 2007 Rossi et al 5 909 378 A 6 1999 De Milleville 2007 0228183 Al 10 2007 Kennedy et al 5 926 776 A 7 1999 Glorioso et al 2008 0015740 Al 1 2008 Osann 5 977 964 A 11 1999 Williams et al 2008 0015742 Al 1 2008 Kulyk et al 6 062 482 A 5 2000 Gauthier et al 2008 0077474 1 3 2008 Dumas et al 705 10 6 098 893 A 8 2000 Berglund et al 2008 0099568 Al 5 2008 Nicodem et al 6 116 512 A 9 2000 Dushane et al 2008 0128523 Al 6 2008 Hoglund et al 6 216 956 4 2001 Ehlers et al 2008 0161977 7 2008 Takach et al 6 349 883 2 2002 Simmons et al 2008 0185450 Al 8 2008 Kwon et al 6 356 204 B1 3 2002 Guindi 2008 0191045 Al 8 2008 Har
3. It will be appreciated that devices referred to herein need not be within an enclosure or vessel For example a device can be on an exterior surface nearby or connected to an enclosure or vessel As another example a device can include a portable device such as a cell phone or laptop that is configured to be carried by a user Thus although particular examples are set forth in the context of a smart home it is to be appreciated that 20 25 30 35 40 45 50 55 60 65 6 the scope of applicability of the described extensible devices and services platform is not so limited As described further herein one or more intelligent multi sensing network connected devices can be used to promote user comfort convenience safety and or cost savings FIG 1 illustrates an example of general device components which can be included in an intelligent network connected device 100 i e device Each of one more or all devices 100 within a system of devices can include one or more sensors 102 a user interface component 104 a power supply e g including a power connection 106 and or battery 108 a communications component 110 a modularity unit e g including a docking station 112 and replaceable module 114 and intelligence components 116 Particular sensors 102 user interface components 104 power supply configura tions communications components 110 modularity units and or intelligence components 116 can be the
4. analyzing past sensor data points with respect to known event properties by considering whether a particular device s sen sor data points reliably co varied with other nearby device s sensor data points and or by assessing variability across past sensor data points It will be appreciated that in some instances the weights are stored in multiple look up tables e g each relating to a different event property At block 810 an adjustment is applied to one or more sensor data points e g by inter device correlator 510 The adjustment can include a linear adjustment e g such that a sensor measurement should be adjusted based on an additive or multiplicative factor or a nonlinear adjustment In some instances a plurality of adjustments are applied to each data point For example a first adjustment can be used when attempting to determine whether an event occurred or is occurring and one or more second adjustments can be used to determine a magnitude location or trajectory of the event As a specific illustration a first adjustment could include a step wise function that transforms a sensor measurement to 1 if it as above a threshold and 0 otherwise and a second adjustment could include a multiplicative and additive scal ing factor In both instances the adjustments can result in normalized sensor measurements across devices though the first adjustment may be more useful when determining a binary condition e g
5. DATA SERVICES amp i U S Patent 31 2013 Sheet 4 of 13 US 8 620 841 B1 EX EXTRINSIC INFORMATION WEATHER FORECAST e g FROM INTERNET PRICES 416 NEIGHBORHOOD HOME INFORMATION PROCESSING PARADIGMS e SECURITY DEMAND SERVICES RESPONSE 410a ADVERTISING COMMUNICATION PROCESSING 306 ENGINE m SOCIAL 410c CHALLENGES RULES COMPLIANCE REWARDS 410d 404 DS DATA SOURCE DEVICES DC DATA CONSUMER EX SS SERVICE SOURCE LIGHTS HVAC WATER CONTROLLERS SENSORS SC SERVICE CONSUMER HOME APPLIANCES SMOKE CO HAZARD SENSORS ALARMS FIG 4 U S Patent 31 2013 Sheet 5 of 13 05 8 620 841 B1 EX EXTRINSIC INFORMATION WEATHER FORECAST FROM INTERNET PRICES NEIGHBORHOOD HOME INFORMATION 306 PROCESSING ENGINE 502 DEVICE 23 LOCATIONS WEIGHT ADJUSTMENT ASSIGNER DS DATA SOURCE DEVICE DC DATA CONSUMER EX SS SERVICE SOURCE LIGHTS HVAC WATER CONTROLLERS SENSORS HOME APPLIANCES SMOKE CO HAZARD SENSORS ALARMS FIG 5 SC SERVICE CONSUMER U S Patent PAUSE UNTIL NEXT MEASUREMENT TIME Dec 31 2013 Sheet 6 of 13 US 8 620 841 600a START 605 DETECT SENSOR MEASUREMENT i 610 TRANSMISSION CRITERION SATISFIED 620 615 TRANSMIT SENSOR DATA FIG 6A U S Patent 31 2013 Sheet 7 of 13 US 8 620 841 B1 600b START 605 DETECT
6. a primary purpose unrelated to collecting mea 56 References Cited surements from a type of sensor that collected the measure U S PATENT DOCUMENTS ment A measurement set identifier can select a set of mea surements The electronic devices associated with the set of measurements can be in close geographical proximity relative 22 e to their geographical proximity other devices ppp device correlator access the set collectively analyze 4 646 964 3 1987 Parker et al 4 656 835 4 1987 Kidder et al the measurements An event detector can determine whether 4 657 179 4 1987 Aggers et al an event occurred An event forecaster can forecast a future 4 685 614 A 8 1987 Levine event property An alert engine can identify one or more T SPA I88 quc eu entities to be alerted of the future event property generate at 4 751 961 A 6 1988 Levine et al 4 948 040 A 8 1990 Kobayashi et al least one alert identifying the future event property and trans 5 088 645 A 2 1992 Bell mit the at least one alert to the identified one or more entities 5 211 332 A 5 1993 Adams 5 224 648 A 7 1993 Simon et al 18 Claims 13 Drawing Sheets 1000 10708 1012 ROTATE RING US 8 620 841 B1 Page 2 56 References Cited 2003 0231001 1 12 2003 Bruning 2004 0249479 Al 12 2004 Shorrock U S PATENT DOCUMENTS 2005 0043907 Al 2 2005 Eckel et al 2005 0128067 Al 6 2005 Zakrewski
7. began and or a trajectory of the event For example the event properties could include that an earthquake event was estimated to have begun at 10 32 am at a location with geographic coordinates x1 x2 and with a strength of 6 8 on the Richter scale As another example the event properties could include that at 10 34 am an earthquake event spread to neighborhoods with zip codes X X and X with a strength of 4 4 4 8 In some instances a single fit can result in estimation as to whether the event occurred at block 825 and estimation of one or more other event properties In some instances two three or more fits are used For example a first fit can be used during an estimation as to whether the event occurred a second fit for the event s magnitude and the third fit for the event s location These fits may be simultaneously deter mined or successively determined FIG 9 illustrates a flowchart for a process 900 of forecast ing event properties and sending alerts For example one or more of blocks 730 740 of process 700 can include one more or all of blocks 905 920 of process 900 Atblock 905 an event trajectory can be estimated based on an event magnitude or past trajectory e g by event fore caster 514 For example a spread of an earthquake initially centered on a first location may depend on the earthquake s magnitude As another example a reach ofa tornado or storm can depend on a past trajectory of the tornado or stor
8. for forecasting events as recited in claim 7 wherein collectively analyzing the sensor measurements pro vided by the thermostat devices comprises generating or refining a time sensitive model 12 The method for forecasting events as recited in claim 7 wherein collectively analyzing the sensor measurements pro videdby the thermostat devices comprises counting a number of sensor measurements in the set of sensor measurements 13 The method for forecasting events as recited in claim 7 wherein the same or different collective analysis ofthe sensor measurements provided by the thermostat devices comprises predicting a trajectory of the event 20 25 30 35 40 45 32 14 crowdsourced event detection network comprising a population of thermostat devices each said thermostat device comprising a housing and at least one non tem perature related sensor coupled to the housing the at least one non temperature related sensor being config ured to sense at least one environmental characteristic or condition that is generally unrelated to controlling a temperature condition within a structure each said ther mostat device further comprising a data transmission component configured to transmit first information rep resentative of said least one sensed environmental char acteristic or condition for reception by an aggregating processor wherein said non temperature related sensor is selected from the group consisting of seism
9. more of the smart home devices of FIG 2 can further allow a user to interact with the device even ifthe user is not proximate to the device For example a user can communicate with a device using a computer e g a desktop computer laptop computer or tablet or other portable electronic device e g a smart phone 266 A webpage or app can be configured to receive communications from the user and control the device based on the communications and or to present information about the device s operation to the user For example the user can view a current setpoint temperature for a device and adjust it using a computer The user can be in the structure during this remote communication or outside the structure The smart home also can include a variety of non commu nicating legacy appliances 140 such as old conventional washer dryers refrigerators and the like which can be con trolled albeit coarsely ON OFF by virtue of the wall plug interfaces 210 The smart home can further include a variety of partially communicating legacy appliances 242 such as IR controlled wall air conditioners or other IR controlled devices which can be controlled by IR signals provided by the hazard detection units 204 or the light switches 208 FIG 3 illustrates a network level view of an extensible devices and services platform with which the smart home of FIGS 1 and or 2 can be integrated Each of the intelligent network connected devices from FIG 2 c
10. paradigms described hereinabove can be used as a processing device in a larger distributed virtualized com puting scheme for carrying out the described processing para digms or for any of a variety of other purposes consistent with the present teachings The computer system 1100 can include a computer 1102 keyboard 1122 a network router 1112 a printer 1108 and a monitor 1106 The monitor 1106 processor 1102 and keyboard 1122 are part of a computer system 1126 which can be a laptop computer desktop com puter handheld computer mainframe computer etc The monitor 1106 can be a CRT flat screen etc A user 1104 can input commands into the computer 1102 using various input devices such as a mouse keyboard 1122 20 25 30 35 40 45 50 55 60 65 24 track ball touch screen etc If the computer system 1100 comprises a mainframe a designer 1104 can access the com puter 1102 using for example a terminal or terminal inter face Additionally the computer system 1126 may be con nected to a printer 1108 and a server 1110 using a network router 1112 which may connect to the Internet 1118 or a WAN The server 1110 may for example be used to store addi tional software programs and data In one embodiment soft ware implementing the systems and methods described herein can be stored on a storage medium in the server 1110 Thus the software can be run from the storage medium in the server 1110 In anothe
11. predicting where and when severe weather events will strike can provide residents with the warning necessary to protect themselves and their belongings from the damage As another example timely prediction of impending earthquake events even if provided only a few seconds in advance can prevent injury or death by allowing recipients of earthquake alarm to move quickly to a safer location or position before the onset of the earthquake Even predictions dealing with less severe events can result in substantial advantages For example if a person s actions can be reliably predicted other related people can more efficiently plan their activities and or par ticular conveniences can be appropriately timed to be ready upon the person s arrival at a location Utilization of such advantages could improve productivity safety and comfort on many different scales and in many different ways Despite these strong advantages producing reliable pre dictions remains a difficult task There are many unknowns that influence a future event and frequently contributing variables are also unknown Thus weather predictions are frequently erroneous natural disasters frequently strike with out warning and substantial time is wasted waiting on certain events such as the arrival of others or preparing an environ ment only after such others actually arrive SUMMARY Provided according to one or more embodiments are sys tems methods computer program
12. same or simi lar across devices 100 or can vary depending on device type or model By way of example and not by way of limitation one or more sensors 102 in a device 100 may be able to e g detect acceleration temperature humidity water supplied power proximity external motion device motion sound signals ultrasound signals light signals fire smoke carbon monox ide global positioning satellite GPS signals or radio fre quency RF or other electromagnetic signals or fields Thus for example sensors 102 can include temperature sensor s humidity sensor s hazard related sensor s or other environ mental sensor s accelerometer s microphone s optical sensors up to and including camera s e g charged coupled device or video cameras active or passive radiation sensors GPS receiver s or radio frequency identification detector s While FIG 1 illustrates an embodiment with a single sensor many embodiments will include multiple sensors In some instances device 100 includes one or more primary sensors and one or more secondary sensors The primary sensor s can sense data central to the core operation of the device e g sensing a temperature in a thermostat or sensing smoke in a smoke detector The secondary sensor s can sense other types of data e g motion light or sound which can be used for energy efficiency objectives or smart operation objec tives In some instances an average user may even be una
13. satisfied at block 610 pro cess 600a continues to block 620 at which the process is paused until the next measurement time This could entail pausing the process for a defined time interval or pausing the process until another sensor measurement is detected based on an external effect Following the pause process 600a returns to block 605 FIG 6B illustrates a flowchart for another process 6005 of transmitting data from a device 100 to a remote server in accordance with an embodiment of the invention Process 6005 is similar to that of process 600a However process 6005 does not include block 610 Thus sensor data is reliably transmitted upon detection of the sensor measurement This could result in regular sensor data transmission or transmis sion of sensor data each time that an external effect resulted in the sensor measurement to be detected FIG 7 illustrates a flowchart for a process 700 of analyzing sensor data points to forecast event properties At block 705 a plurality of sensor data points are accessed In some instances a central server receives data points for each of a plurality of devices In some instances a device generates at least one sensor data point based on a measurement by a local sensor and receives at least one sensor data point from another device Thus a data point can be accessed after it is received from another device or after it is locally generated Each sensor data point can include a raw or processed
14. smart home devices represents one par ticularly useful and advantageous embodiment the scope of the present teachings is applicable across a broad variety of scenarios including those discussed further herein in which a population of smart home devices is provided that are each equipped with one or more sensors and the outputs of those sensors are received and processed in a groupwise manner to achieve one or more useful crowdsourced intelligence results Not unimportantly according to one or more of the preferred embodiments the relative ubiquity of the sensor network that is key to the effective crowdsourced intelligence is fostered primarily by the popularity attractiveness and or essential underlying functionality of the smart home devices within which the sensors are embedded rather than their functionality as part of the crowdsourced detection network For example for the particular exemplary scenario of a crowdsourced earthquake detection network the accelerom eters movement sensors may be preferably embedded in a smart home device comprising an elegant visually appeal ing intelligent network connected self programming ther mostat such as that described in the commonly assigned US08195313B1 which is hereby incorporated by reference in its entirety for all purposes Notably the popularity and increasing ubiquity of the smart home device of US08195313B1 is driven by its consumer appeal along with the fact that every h
15. 0 45 50 55 10 other device that is network connected anywhere in the world The devices can send and receive communications via any of a variety of custom or standard wireless protocols Wi Fi ZigBee 6LoWPAN etc and or any of a variety of custom or standard wired protocols CAT6 Ethernet Home Plug etc The wall plug interfaces 210 can serve as wireless or wired repeaters and or can function as bridges between i devices plugged into AC outlets and communicating using Homeplug or other power line protocol and ii devices that not plugged into AC outlets For example a first device can communicate with a second device via a wireless router 260 A device can further com municate with remote devices via a connection to a network such as the Internet 262 Through the Internet 262 the device can communicate with a central server or a cloud computing system 264 The central server or cloud computing system 264 can be associated with a manufacturer support entity or service provider associated with the device For one embodi ment a user may be able to contact customer support using a device itself rather than needing to use other communication means such as a telephone or Internet connected computer Further software updates can be automatically sent from the central server or cloud computing system 264 to devices e g when available when purchased or at routine inter vals By virtue of network connectivity one or
16. 106 and or AC to DC powering circuitry and can prevent the user from being exposed to high voltage wires In some instances docking stations 112 are specific to a type or model of device such that e g a thermostat device includes a different dock ing station than a smoke detector device In some instances docking stations 112 can be shared across multiple types and or models of devices 100 Replaceable module 114 ofthe modularity unit can include some or all sensors 102 processors user interface compo nents 104 batteries 108 communications components 110 intelligence components 116 and so forth of the device Replaceable module 114 can be configured to attach to e g plug into or connect to docking station 112 In some instances a set of replaceable modules 114 are produced with the capabilities hardware and or software varying across the replaceable modules 114 Users can therefore eas ily upgrade or replace their replaceable module 114 without having to replace all device components or to completely reinstall device 100 For example a user can begin with an inexpensive device including a first replaceable module with limited intelligence and software capabilities The user can then easily upgrade the device to include a more capable replaceable module As another example if a user has a Model 1 device in their basement a Model 2 device in their living room and upgrades their living room device to include a Model 3 replace
17. B2 1 2007 Kates 2010 0250009 1 9 2010 Lifson et al 7168627 B2 1 2007 Kates 2010 0261465 Al 10 2010 Rhoads et al 7289887 B2 10 2007 Rodgers 2010 0262298 Al 10 2010 Johnson et al 7 360 370 B2 4 2008 Shah et al 2010 0262299 Al 10 2010 Cheung RE40437 E 7 2008 Rosen 2010 0280667 A1 11 2010 Steinberg 7 434 742 B2 10 2008 Mueller et al 2010 0289643 Al 11 2010 Trundle et al 7 460 690 B2 12 2008 Cohen et al 2010 0305771 Al 12 2010 Rodgers 7 469 550 B2 12 2008 Chapman Jr et al 2010 0308119 A1 12 2010 Steinberg et al 7 537 171 2 5 2009 Mueller et al 2010 0318227 Al 12 2010 Steinberg et al 7 558 648 B2 7 2009 Hoglund et al 2011 0001812 A1 1 2011 Kang etal 7 571 865 B2 8 2009 Nicodem et al 2011 0046792 Al 2 2011 Imes et al 7 605 714 B2 10 2009 Thompson et al 2011 0046805 A1 2 2011 Bedros et al 7 044 869 B2 1 2010 Hoglund et al 2011 0046806 Al 2 2011 Nagel et al 7 702 424 B2 4 2010 Cannon et al 2011 0054699 Al 3 2011 Imes etal pen S DIR orna i 2011 0077896 Al 3 2011 Steinberg 7845042835 abo Heer pera 2011 0130636 1 6 2011 Daniel et al 600 301 SEDES RI S01 Sanaa al 2011 0185895 Al 8 2011 Freen por 2011 0253796 Al 10 2011 etal 203710257 MN 2011 0307103 Al 12 2011 Cheung 7 847 681 B2 12 2010 Singhal et al 2012 0065935 AI 3 2012 Steinberg et al 7 848 900 B2 12 2010 Steinberg et al 2012 0085831 Al 4 2012 Kopp 7 854 389 B2 12 2010 Ahmed 2012 0158350 AI 6 2012 Steinberg 7 904 209 B2 3 2011 Podgorny et
18. SENSOR MEASUREMENT PAUSE UNTIL NEXT MEASUREMENT TIME FIG 6B U S Patent 31 2013 Sheet 8 of 13 US 8 620 841 1 700 A 70 5 ACCESS PLURALITY OF SENSOR DATA POINTS 0 71 ASSOCIATE EACH SENSOR DATA POINT WITH TIME AND LOCATION 71 IDENTIFY SET OF SENSOR DATA POINTS 5 720 ANALYZE SET OF SENSOR DATA POINTS 725 Y DETECT EVENT OCCURRENCE LOCATION MAGNITUDE AND OR TRAJECTORY 30 Y FORECAST FUTURE PROPERTIES OF EVENT 7 Y IDENTIFY ENTITIES TO BE ALERTED 7 35 740 GENERATE SEND ALERTS FIG 7 U S Patent Dec 31 2013 Sheet 9 of 13 US 8 620 841 B1 800 805 APPLY WEIGHT EACH SENSOR DATA POINT APPLY ADJUSTMENTS TO ONE OR MORE SENSOR DATA POINTS FIT SENSOR DATA POINTS 810 15 820 ASSESS CRITERION 825 ESTIMATE EVENT LOCATION MAGNITUDE AND OR TRAJECTORY BASED ON FIT PARAMETERS FIG 8 U S Patent Dec 31 2013 Sheet 10 of 13 US 8 620 841 B1 900 905 ESTIMATE EVENT TRAJECTORY BASED ON EVENT MAGNITUDE OR PAST TRAJECTORY 910 5 FUTURE EVENT LOCATION BASED ON ESTIMATED EVENT TRAJECTORY 915 IDENTIFY DEVICES IN FORECASTED FUTURE EVENT LOCATION 920 TRANSMIT ALERT TO IDENTIFIED DEVICES OR TO USER DEVICES ASSOCIATED WITH IDENTIFIED DEVICES FIG 9 U S Patent 31 2013 Sh
19. US008620841B1 a2 United States Patent 10 Patent No US 8 620 841 Filson et al 45 Date of Patent Dec 31 2013 54 DYNAMIC DISTRIBUTED SENSOR 5 240 178 8 1993 Dewolf et al THERMOSTAT NETWORK FOR 5 348 078 A 9 1994 Dushane et al 5 381 950 A 1 1995 Aldridge FORECASTING EXTERNAL EVENTS 5395042 A 3 1995 Riley et al 5 476 221 12 1995 S 75 Inventors John B Filson Mountain View 5 499 196 A 3 1996 ee bite US Eric B Daniels East Palo Alto Continued CA US Adam Mittleman Redwood g 221 ee FOREIGN PATENT DOCUMENTS ocklin Yo atsuoka Palo Alto CA US CA 2202008 C 2 2000 EP 196069 B1 12 1991 73 Assignee Nest Labs Inc Palo Alto CA US Continued Notice Subject to any disclaimer the term of this OTHER PUBLICATIONS patent is extended or adjusted under 35 et re U S C 154 b by 0 days Yan et al Research on event prediction in time series data 2004 IEEE pp 2874 2878 21 Appl No 13 601 890 Continued 22 Filed Aug 31 2012 Primary Examiner David Vincent 51 Int Cl 74 Attorney Agent or Firm Kilpatrick Townsend amp G06F 15 18 2006 01 Stockton LLP 52 e sedis 2400 ABSTRACT 58 Field of Classification 5 XE Systems and methods for forecasting events be provided USPC 706 12 45 A measurement database can store sensor measurements See application file for complete search history d each having been provided by a non portable electronic device with
20. able module the user can move the Model 2 replaceable module into the basement to connect to the existing docking station The Model 2 replaceable module may then e g begin an initiation process in order to identify its new location e g by requesting information from a user via a user interface Intelligence components 116 ofthe device can support one or more of a variety of different device functionalities Intel ligence components 116 generally include one or more pro cessors configured and programmed to carry out and or cause to be carried out one or more of the advantageous function alities described herein The intelligence components 116 can be implemented in the form of general purpose processors carrying out computer code stored in local memory e g flash memory hard drive random access memory special 20 25 30 35 40 45 50 55 60 65 8 purpose processors or application specific integrated circuits combinations thereof and or using other types of hardware firmware software processing platforms The intelligence components 116 can furthermore be implemented as local ized versions or counterparts of algorithms carried out or governed remotely by central servers or cloud based systems such as by virtue of running a Java virtual machine JVM that executes instructions provided from a cloud server using Asynchronous Javascript and XML AJAX or similar proto cols By way of example intellig
21. al 2012 0221151 Al 8 2012 Steinberg 7 904 830 B2 3 2011 Hoglund et al 2012 0262303 1 10 2012 Fahey 340 870 02 8 010 237 B2 8 2011 Cheung 8 019 567 2 9 2011 Steinberg FOREIGN PATENT DOCUMENTS 8 090 477 Bl 1 2012 Steinberg 8 131 497 B2 3 2012 Steinberg EP 1275037 B1 2 2006 8 180 492 B2 5 2012 Steinberg JP 59106311 A 6 1984 8 195 313 B1 6 2012 Fadell etal 700 83 JP 01252850 A 10 1989 2001 0033481 1 10 2001 Chien 362 34 JP 09298780 A 11 1997 US 8 620 841 B1 Page 3 56 References Cited FOREIGN PATENT DOCUMENTS JP 10023565 A 1 1998 WO 2008054938 2 5 2008 OTHER PUBLICATIONS Zhang et al Forecasting with artificial neural networks The state of the art 1998 Elsevier pp 1 28 Author Unknown Aprilaire Electronic Thermostats Model 8355 User s Manual Research Products Corporation 2000 16 pages Author Unknown Braeburn 5300 Installer Guide Braeburn Sys tems LLC 2009 10 pages Author Unknown Braeburn Model 5200 Braeburn Systems LLC 2011 11 pages Author Unknown Ecobee Smart Si Thermostat Installation Manual Ecobee 2012 40 pages Author Unknown Ecobee Smart Si Thermostat User Manual Ecobee 2012 44 pages Author Unknown Ecobee Smart Thermostat Installation Manual 2011 20 pages Author Unknown Ecobee Smart Thermostat User Manual 2010 20 pages Author Unknown Electric Heat Lock Out on Heat Pumps Washing ton State University Extension Energy Program Apr 2010
22. an adjust ment to be associated with a device by assessing data point values associated with the device over a period of time The data point values can be compared to data point values of other devices orto control values For example weight adjust ment assigner 508 can compare an average of a device s data point value across a time period to a set value e g 0 or 9 8 m s for an accelerometer reading a value looked up from an external source e g an average temperature over the time period or a calculated value e g a mean median or mode of device specific average values across a set of nearby devices As another example weight adjustment assigner 508 can compare individual data point values across a time US 8 620 841 B1 15 period to other values a mean median or mode of time matched data point values for a set of devices determined adjustment can include a single value such as one that can be added to or multiplied to data point values or a more complicated function such as a power function or loga rithmic function Weight adjustment assigner 508 can periodically deter mine weights and or adjustments and store the weights and or adjustments in one or more look up tables e g a weight look up table and an adjustment look up table Each weight and or adjustment can be associated with a device and or sensor e g using a device ID or sensor ID In some instances blank entries in the look up table c
23. an be associated with a default assignment e g a default weight or no adjust ment or the look up table can be prepopulated with the default assignments which can thereafter be adjusted by weight adjustment assigner Upon identification of a data set by data set identifier 504 the set identification can be transmitted to an inter device correlator 510 In some instances the identified set includes set properties e g Device IDs a a and transmission times b b Thus the identified set includes one or more data set criteria Inter device correlator 510 can then pull the data points from data point database 502 that corresponds to the data set In some instances data set identifier 504 identi fies a specific set of data points e g Data Point IDs c In these instances either data set identifier 504 can retrieve the appropriate data points from data point database 502 and transmit them to inter device correlator 510 or inter device correlator 510 can itself retrieve the points Inter device correlator 510 analyzes the set of data points collectively in an attempt to identify whether an event resulted in observed sensor readings For example an earth quake would give rise to large accelerometer readings a power outage would give rise to low voltage detection mea surements a tornado would give rise to low pressure mea surements or a storm and or clouds would give rise to low outdoor light intensities However each of th
24. an communicate with one or more remote central servers or cloud computing systems 264 The communication can be enabled by estab lishing connection to the Internet 262 either directly for example using 3G 4G connectivity to a wireless carrier though a hubbed network which can be scheme ranging from a simple wireless router for example up to and including an intelligent dedicated whole home control node or through any combination thereof The central server or cloud computing system 264 can collect operation data 302 from the smart home devices For example the devices can routinely transmit operation data or can transmit operation data in specific instances e g when requesting customer support The central server or cloud computing architecture 264 can further provide one or more services 304 The services 304 can include e g software update customer support sensor data collection logging US 8 620 841 B1 11 remote access remote or distributed control or use sugges tions e g based on collected operation data 304 to improve performance reduce utility cost etc Data associated with the services 304 can be stored at the central server or cloud computing system 264 and the central server or cloud com puting system 264 can retrieve and transmit the data at an appropriate time e g at regular intervals upon receiving request from a user etc One salient feature of the described extensible devices and servic
25. as a current temperature annual precipitation level alti tude etc Thus event forecaster 514 can identify these char acteristics e g based on data in data points within the iden tified data set or other data points or from an external source and use the characteristics in its forecasting An alert engine 516 can then generate and transmit alerts that are indicative of or identify the forecasted event In some instances alert engine 516 identifies devices in locations likely to be affected by the event in the future Alert engine 516 can specifically receive a location zone or location crite rion from event forecaster 514 and identify devices in that location based on data in the device locations database 506 These devices can include devices within the identified data set and or other devices Alerts can then be sent to the iden tified devices Insome instances alert engine 516 identifies users likely to be interested in the event A user profile database 518 can associate for each user a telephone number e g a cellular phone number an email or a portable device ID with a device ID Alert engine 516 can predict that a user will be interested in the event if the event is predicted to affect a location at which the device is located e g a home or if the US 8 620 841 B1 17 user is estimated to be within an area predicted to be affected e g determined based on cell phone tracking techniques Alert engine 516 can th
26. as occurred 4 The event forecasting system of claim 1 wherein the sensor measurements provided by the thermostat devices in the measurement set are associated with a similar measure ment time 5 The event forecasting system of claim 1 wherein ther mostat devices associated with the sensor measurements in the measurement set are further associated with a plurality of users 6 The event forecasting system of claim 1 wherein the event includes a weather related or natural disaster event 7I A method for forecasting events the method comprising storing a plurality of sensor measurements in a measure ment database each sensor measurement having been provided by a thermostat device wherein a primary purpose of at least one respective thermostat device is to control a temperature condition within a structure in addition to collecting measurements from a non tem perature related sensor that collected the sensor mea surement wherein said non temperature related sensor is selected from the group consisting of seismic activity sensors hazard related environmental sensors micro phones optical sensors and radiation sensors US 8 620 841 B1 31 selecting a set ofsensor measurements from the plurality of sensor measurements provided by the thermostat devices in the measurement database wherein the ther mostat devices associated with the set of sensor mea surements are in close geographical proximity relative to their geograph
27. ata 68 0311 Honeywell International Inc Jan 2012 126 pages Introducing the New Smart Si Thermostat Datasheet online Ecobee Mar 2012 retrieved on Feb 25 2013 Retrieved from the Internet lt URL https www ecobee com solutions home smart si gt Lux PSPU732T Manual LUX Products Corporation Jan 2009 48 pages NetX RP32 Wifi Network Thermostat Consumer Brochure Network Thermostat May 2011 2 pages Venstar T5800 Manual Venstar Inc Sep 2011 63 pages White Rodgers Emerson Model 1F81 261 Installation and Operat ing Instructions White Rodgers Apr 2010 8 pages White Rodgers Emerson Model IF98EZ 1621 Homeowner s User Guide White Rodgers Jan 2012 28 pages cited by examiner U S Patent 31 2013 Sheet 1 of 13 US 8 620 841 B1 DEVICE 100 oo ee REPLACEABLE MODULE DOCKING STATION 4 t POWER 106 i L L OMNEA IE 222255522262 520220200 h p 116 108 2 INTELLIGENT COMPONENTS FIG 1 US 8 620 841 Sheet 2 of 13 Dec 31 2013 U S Patent 92 5 892 DIJ 992 NOILVOIMMHI U S Patent 31 2013 Sheet 3 of 13 US 8 620 841 1 NEST PARTNER S DATA ENGINES STATISTICS 306 GOVERNMENTS 324 INFERENCES INDEXING ACADEMIC INSTITUTIONS 326 t E OPS
28. ates a flowchart for a process of forecasting event properties and sending alerts FIGS 10A 10B illustrate an example of a thermostat device that may be used to collect sensor measurements FIG 11 illustrates a block diagram of an embodiment of a computer system and FIG 12 illustrates a block diagram of an embodiment of a special purpose computer DETAILED DESCRIPTION OF THE INVENTION Provided according to one or more embodiments are sys tems methods computer program products and related busi ness methods for utilizing measurements obtained from a set of distributed sensors to predict events Each sensor within a network of sensors can collect data and transmit the data to a central server As used herein central server refers to any of a variety of different processing devices and or groups of pro cessing devices that are capable of receiving data derived from the sensors and processing the received information As would be readily appreciated by the skilled artisan it is not required that the one or more processors forming the central server be located in any particular geographical location rela tive to the sensors or to each other While in one embodiment the central server can be implemented in cloud based com puting and storage environment such as the EC2 Elastic Compute Cloud offering from Amazon com of Seattle Wash it is to be appreciated that the central server can be implemented on any of a variety of different har
29. ative of the forecasted future event and an alerting mechanism configured to alert a nearby home occupant of the forecasted future event UNITED STATES PATENT AND TRADEMARK OFFICE CERTIFICATE OF CORRECTION PATENT NO 8 620 841 Page 1011 APPLICATION NO 13 601890 DATED December 31 2013 INVENTOR S John B Filson et al It is certified that error appears in the above identified patent and that said Letters Patent is hereby corrected as shown below In the Claims Column 30 Line 7 Please omit sensors hazard and replace with sensors hazard Column 30 Line 8 Please omit microphones optical and replace with microphones optical Column 30 Line 9 Please omit sors and radiation and replace with sors and radiation Column 30 Line 66 Please omit environmental sensors micro and replace with environmental Sensors micro Signed and Sealed this Twenty ninth Day of April 2014 MARE Z _ Michelle K Lee Deputy Director of the United States Patent and Trademark Office
30. be passed forwarded or transmitted via any suitable means including memory shar ing message passing token passing network transmission etc While the principles of the disclosure have been described above in connection with specific apparatuses and methods it is to be clearly understood that this description is made only by way of example and not as limitation on the scope of the disclosure What is claimed is 1 A event forecasting system comprising a measurement database that stores a plurality of sensor measurements each sensor measurement having been 20 25 30 35 40 45 50 55 60 65 30 provided by a thermostat device wherein a primary purpose of each thermostat device is to control a tem perature condition within a structure in addition to col lecting measurements from non temperature related sensor that collected the sensor measurement wherein said non temperature related sensor is selected from the group consisting of seismic activity sensors hazard related environmental sensors microphones optical sen sors and radiation sensors a measurement set identifier that selects a set of sensor measurements from the plurality of sensor measure ments provided by the thermostat devices in the mea surement database wherein the thermostat devices asso ciated with the set of sensor measurements are in close geographical proximity relative to their geographical proximity to other devices an
31. can be determined based on a location associated with a data point having an abnormal e g above or below US 8 620 841 B1 19 threshold sensor measurement or a location associated with a request for an event detection or event forecast analysis At block 720 the set of sensor data points is analyzed e g by inter device correlator 510 The analysis can include determining whether an abnormal sensor measurement is consistent or inconsistent with other sensor measurements generating statistics generating a model performing a data fit and comparing generated statistics or values to one or more thresholds At block 725 it can be determined whether a particular type of event is occurring and if so the event s location magnitude and or trajectory e g by event detector 512 The determination about the event s occurrence can be deter mined based on a number or percentage of data points having a characteristic sensor measurement e g above threshold or below threshold measurements quality of fit statistics or estimated event magnitude e g concluding that no event occurred if a sufficiently low magnitude is estimated The location magnitude and or trajectory can be determined based on which data points were associated with the most extreme measurements fit parameters e g offset param eters and or time sensitive analyses At block 730 future event properties can be forecasted e g by event forecaster 514 The
32. can integrate seamlessly with each other and or with cloud based server systems to provide any of a variety of useful smart home objectives One more or each of the devices illustrated in the smart home environment and or in the figure can include one or more sensors a user interface a power supply a communications component a modularity unit and intelligent software as described with respect to FIG 1 Examples of devices are shown in FIG 2 An intelligent multi sensing network connected thermo stat 202 can detect ambient climate characteristics e g tem perature and or humidity and control a heating ventilation and air conditioning HVAC system 203 One or more intel ligent network connected multi sensing hazard detection units 204 can detect the presence of a hazardous substance and or a hazardous condition in the home environment e g smoke fire or carbon monoxide One or more intelligent multi sensing network connected entryway interface devices 206 which can be termed a smart doorbell can detect a person s approach to or departure from a location control audible functionality announce a person s approach or departure via audio or visual means or control settings on a security system e g to activate or deactivate the security system Each of a plurality of intelligent multi sensing network connected wall light switches 208 can detect ambient lighting conditions detect room occupancy states and control a
33. cating an event occurrence and or forecasting future event properties Thermostat 1000 has a large front face lying inside the outer ring 1012 The front face of thermostat 1000 comprises a clear cover 1014 that according to some embodiments is polycarbonate and a metallic portion 1024 preferably having a number of slots formed therein as shown According to some embodiments metallic portion 1024 has number of slot like openings so as to facilitate the use of a passive infrared motion sensor 1030 mounted therebeneath Metallic portion 1024 can alternatively be termed a metallic front grille portion Further description of the metallic portion front grille portion is provided in the commonly assigned U S Ser No 13 199 108 which is hereby incorporated by refer ence in its entirety for all purposes Motion sensing as well as other techniques can be use used in the detection and or predict of occupancy as is described further in the commonly assigned U S Ser No 12 881 430 which is hereby incorporated by reference in its entirety According to some embodiments occupancy information is used in generating an effective and efficient scheduled pro US 8 620 841 B1 23 gram Preferably an active proximity sensor 1070A 15 vided to detect an approaching user by infrared light reflec tion and an ambient light sensor 1070B is provided to sense visible light Proximity sensor 1070A can be used to detect proximity in the range of abo
34. cating that the server has issued an escalated tornado watch state Example 4 A plurality of light switches are provided Each light switch includes a motion detector Users purchase the devices and mount each light switch to a wall Within a building each light switch communicates wirelessly with a control box that includes a processing system Each motion detector is continuously active Once a motion detector detects motion it transmits a signal to the control box identifying the light switch and indicating that motion has been detected The control box correlates the motion detections across the light switches and identifies common patterns e g a frequent successive detection sequence is one that activates the motion detector Switch 3 then 5 then 8 Based on these patterns the control box estimates location information about the switches e g Switch 3 is near Switch 5 The control box can later receive select motion detections and forecast future motion detections e g if detections are made by Switch 3 and then 5 the control box can forecast that motion will be detected by Switch 8 The control box then sends messages to light switches involved in the forecast e g Switch 8 Switch 8 then automatically turns on the US 8 620 841 B1 29 light before motion is detected The automatic lighting can be prevented if ambient lighting is above a threshold In this way a person s path can be illuminated as they wa
35. d US 8 620 841 B1 27 The central server identifies median acceleration measure ments and estimates an earthquake magnitude based on the median The central server assesses whether there are any similarly occurring events among other nearby populations of thermostats The central server then forecasts other areas likely to be affected in view of the earthquake s magnitude and known properties about earthquake propagation The central server consults the database to identify other devices in the forecasted location and transmits a signal to each ofthe other devices Upon receiving the signal each of the other devices sounds an alarm indicating that people should take cover Example 2 Sprinkler systems are provided Each system includes a control box with temperature humidity and wind detector Users purchase the sprinkler system and each user mounts the control box on a wall outside a dwelling e g on a house exterior surface The control box or a separately provided device provided in conjunction with the control box is equipped with a user interface having a similar physical look and feel to the user interface of the thermostat device described above with respect to FIGS 10A 10B Each sprin kler system detects a local wireless network and requests a password A respective user enters the password by rotating a rotatable ring ofthe control box or other user interface device associated with the control box of the sprinkler sys
36. device can identify his phone number or email address and a message can there fore be sent to his phone or email account The message can identify the occurrence ofthe event and or can include past or forecasted event properties 20 25 30 35 40 45 50 55 60 65 22 FIGS 10A 10B illustrate one example of a thermostat device 1000 that may be used to collect sensor measurements The term thermostat is used to represent a particular type of VSCU unit Versatile Sensing and Control that is particu larly applicable for HVAC control in an enclosure As used herein the term HVAC includes systems providing both heating and cooling heating only cooling only as well as systems that provide other occupant comfort and or condi tioning functionality such as humidification dehumidifica tion and ventilation Although thermostat and VSCU unit may be seen as generally interchangeable for the context of HVAC control of an enclosure it is within the scope of the present teachings for each of the embodiments hereinabove and hereinbelow to be applied to VSCU units having control functionality over measurable characteristics other than tem perature e g pressure flow rate height position velocity acceleration capacity power loudness brightness for any of a variety of different control systems involving the gover nance of one or more measurable characteristics of one or more physical systems and or t
37. dware and software platforms ranging from concentrated single loca tion computing devices to distributed networks of computing devices including virtualized computing devices The central server can identify the set of sensors from the network of sensors by e g identifying sensors within a geographical region identifying sensors that have transmitted data within a time period and or identifying sensors that have transmitted a particular type of data The central server can then aggregate data across the set of sensors estimate characteristics of a current event e g its existence severity or movement and predict characteristics of the event in the future The central server can then transmit information about the predicted char acteristic to one or more devices associated with users likely to be affected by or interested in the future event Embodiments described further herein are but representa tive examples of devices methods systems services and or computer program products that can be used in conjunction with an extensible devices and services platform that while being particularly applicable and advantageous in the smart home context is generally applicable to any type of enclosure or group of enclosures e g offices factories or retail stores vessels e g automobiles or aircraft or other resource con suming physical systems that will be occupied by humans or with which humans will physically or logically interact
38. e executed by the processor s 1260 RAM 1270 and non volatile storage drive 1280 may also provide a repository to store data and data structures used in accordance with the present invention RAM 1270 and non volatile storage drive 1280 may include a number of memories including a main random access memory RAM to store of instructions and data during program execution and a read only memory ROM in which fixed instructions are stored RAM 1270 and non volatile storage drive 1280 may include a file storage subsystem providing persistent non volatile storage of pro gram and or data files RAM 1270 and non volatile storage drive 1280 may also include removable storage systems such as removable flash memory Bus subsystem 1290 provides a mechanism to allow the various components and subsystems of computer 1102 com municate with each other as intended Although bus sub system 1290 is shown schematically as a single bus alterna 5 20 40 45 50 55 26 tive embodiments of the bus subsystem may utilize multiple busses or communication paths within the computer 1102 For a firmware and or software implementation the meth odologies may be implemented with modules e g proce dures functions and so on that perform the functions described herein Any machine readable medium tangibly embodying instructions may be used in implementing the methodologies described herein For example software codes may be stored in a memo
39. ected In some instances the sensor measurement is collected by the sensor at routine intervals e g every minute 5 minutes 15 minutes 30 minutes hour 2 hours 6 hours 12 hours or 24 hours In some instances the sensor measurement is only collected upon the occurrence of particular external effects For example device 100 can include a sensor that only detects movement if a central mass is sufficiently moved to reach a perimeter or external notch At block 610 it is determined whether a transmission criterion is satisfied The transmission criterion can relate to the sensor measurement For example the criterion can 20 40 45 50 55 65 18 require the measurement to be above a threshold below a threshold or to have changed from a previous measurement by at least a given amount If the criterion is satisfied process 600a can continue to block 615 at which sensor data is transmitted The sensor data can include a raw version of the sensor measurement or a processed version of the sensor measurement e g normal ized time averaged or otherwise filtered or processed The sensor data can further include e g a measurement time a transmission time a device identifier and or a device loca tion identifier The sensor data can be transmitted wirelessly to a central server or to other devices e g other nearby devices Following the data transmission or if the transmission criterion is determined to not be
40. ed based on asame or different collective analysis of the sensor measure ments One or more entities to be alerted of the future event property can be identified At least one alert identifying the future event property can be generated and the at least one alert can be transmitted to the identified one or more entities In some embodiments a crowdsourced event detection network is provided that includes a population of non por table smart home devices Each smart home device can have a primary function as one of a thermostat a hazard detector a wall switch an entertainment device a lighting device and a home appliance Each smart home device can include a housing and at least one sensor coupled to the housing The at least one sensor can be configured to sense at least one envi ronmental characteristic or condition that is generally unre lated to the primary function of the smart home device Each smart home device can further include a data transmission component configured to transmit first information represen tative of said least one sensed environmental characteristic or condition for reception by an aggregating processor The aggregating processor can be configured and programmed to receive the first information from each of a plurality of the smart home devices and to forecast a future event based on collective analysis thereof The aggregating processor can be further configured and programmed to identify one or more entities
41. eet 11 0113 US 8 620 841 B1 1000 7N 1012 FIG 10B NX OX press g2 2 CLICK U S Patent 31 2013 Sheet 12 of 13 US 8 620 841 B1 1100 1106 440g FIG 11 US 8 620 841 Sheet 13 of 13 Dec 31 2013 U S Patent L Old 022 Oreck 062 s SiA q eoepejul SIH8IOA UON 55020 wopuey UOHeoUNWUWOD 082 JOgUO A 19S uononussu 901 28195 uononnsuj R L 195 uogonujsu 002 ponpoig 5 9621 US 8 620 841 B1 1 DYNAMIC DISTRIBUTED SENSOR THERMOSTAT NETWORK FOR FORECASTING EXTERNAL EVENTS FIELD This patent specification relates to systems methods and related computer program products for aggregating measure ments obtained from a dynamic network of sensors in order to forecast external events More particularly this patent speci fication relates to a dynamic process of identifying a set of sensors e g each being housed within a thermostat appli cable to an event s forecast aggregating measurements from the set of sensors and forecasting a future characteristic of the event based on the aggregated measurements BACKGROUND Accurate and timely prediction of impending future events can be useful and beneficial in many ways For example
42. ell as the devices of the smart home Even though the devices situated in the smart home will have an endless variety of different individual capabilities and limitations they can all be thought of as sharing common characteristics in that each of them is a data consumer 402 DC a data source 404 DS a services consumer 406 SC and a services source 408 SS Advan tageously in addition to providing the essential control infor mation needed for the devices to achieve their local and 0 5 20 30 40 45 50 12 immediate objectives the extensible devices and services platform can also be configured to harness the large amount of data that is flowing out of these devices In addition to enhanc ing or optimizing the actual operation of the devices them selves with respect to their immediate functions the exten sible devices and services platform can also be directed to repurposing that data in a variety of automated extensible flexible and or scalable ways to achieve a variety of useful objectives These objectives may be predefined or adaptively identified based on e g usage patterns device efficiency and or user input e g requesting specific functionality For example FIG 4 shows processing engine 306 as including a number of paradigms 410 Processing engine 306 can include a managed services paradigm 410a that monitors and manages primary or secondary device functions The device function
43. en send alerts to the users via a tele phone call email or notification sent to a portable device In some instances alert engine 516 is sent to higher level entities such as an emergency control center health care Workers utility company weather station etc These higher level entities can themselves alert areas likely be affected by the event attempt to reduce the event s effect or prepare for post event action An alert can explicitly or implicitly identify an event type an indication that the event is forecasted to reach a specific location a prediction as to when the event will reach the location an actual and or predicted trajectory of the event and a past and or predicted event magnitude The follow lists examples of possible alerts Text message sent to user s cell phone reading Earth quake imminent Take cover Phone message sent to user s cell phone stating Severe hail storm predicted to reach your house at 4 30 pm Signal sent to wall thermostat that causes the thermostat to broadcast Tornado watch Signal sent to a user s wall plug interfaces indicating that the devices should safely kill power within 1 minute due to forecasted power outage Alerts can be sent e g over a network such as the Internet or over a cell phone network User preferences can indicate how they wish to be alerted e g via text message phone call or home device alert For fast moving events alerts can be pushed to
44. ence components 116 can be intelligence components 116 configured to detect when a location e g a house or room is occupied up to and includ ing whether it is occupied by a specific person or is occupied by a specific number of people e g relative to one or more thresholds Such detection can occur e g by analyzing microphone signals detecting user movements e g in front of a device detecting openings and closings of doors or garage doors detecting wireless signals detecting an IP address of a received signal or detecting operation of one or more devices within a time window Intelligence components 116 may include image recognition technology to identify particular occupants or objects In some instances intelligence components 116 can be configured to predict desirable settings and or to implement those settings For example based on the presence detection intelligence components 116 can adjust device settings to e g conserve power when nobody is home or in a particular room or to accord with user preferences e g general at home preferences or user specific preferences As another example based on the detection of a particular person animal or object e g a child pet or lost object intelligence com ponents 116 can initiate an audio or visual indicator of where the person animal or object is or can initiate an alarm or security feature if an unrecognized person is detected under certain conditions e g at
45. er such that the thermostat can communicate over the Internet Each thermostat further requests that a user enter an address which may be a full specific street address in some embodiments or a more general area identifier such as a ZIP code in other embodiment at which it is located The user again enters the address using the rotatable ring Each ther mostat then transmits a message to a central server identifying the thermostat and the address Alternatively once the user has paired their thermostat with an online account associated with the thermostat the user may provide their address infor mation using browser based access to that online account The central server associates each thermostat with its address in a database The accelerometers collect acceleration measurements every minute If any of the three acceleration measurements one for each spatial dimension exceed a threshold the ther mostat transmits the acceleration measurements to a center server along with a device identifier The central server upon receiving the communication looks up the thermostat s address and identifies other ther mostats near the communication transmitting thermostat The central server determines that 10 of 15 other nearby thermostats have also transmitted similar communications within the last minute This 6696 transmission rate exceeds an event occurrence threshold and thus the central server deter mines that an earthquake has occurre
46. er 1102 a monitor 1106 coupled to computer 1102 one or more additional user output devices 1230 optional coupled to computer 1102 one or more user input devices 1240 e g keyboard mouse track ball touch screen coupled to com puter 1102 an optional communications interface 1250 coupled to computer 1102 a computer program product 1205 stored in a tangible computer readable memory in computer 1102 Computer program product 1205 directs system 1200 to perform the above described methods Computer 1102 may include one or more processors 1260 that communicate with a number of peripheral devices via a bus subsystem 1290 These peripheral devices may include user output device s 1230 user input device s 1240 communications interface 1250 and a storage subsystem such as random access memory RAM 1270 and non volatile storage drive 1280 e g disk drive optical drive solid state drive which are forms of tangible computer readable memory Computer program product 1205 may be stored in non volatile storage drive 1280 or another computer readable medium accessible to computer 1102 and loaded into memory 1270 Each processor 1260 may comprise a micro processor such as a microprocessor from Intel amp or Advanced Micro Devices Inc amp or the like To support computer pro gram product 1205 the computer 1102 runs an operating system that handles the communications of product 1205 with the above noted components as well as the commun
47. es to the generation of inferential abstractions that can assist on a per home basis for example an inference can be drawn that the homeowner has left for vacation and so security detection equipment can be put on heightened sensitivity to the gen eration of statistics and associated inferential abstractions that can be used for government or charitable purposes For example processing engine 306 can generate statistics about device usage across a population of devices and send the statistics to device users service providers or other entities e g that have requested or may have provided monetary compensation for the statistics As specific illustrations sta tistics can be transmitted to charities 322 governmental enti ties 324 the Food and Drug Administration or the Envi ronmental Protection Agency academic institutions 326 e g university researchers businesses 328 e g providing device warranties or service to related equipment or utility companies 330 These entities can use the data to form pro grams to reduce energy usage to preemptively service faulty equipment to prepare for high service demands to track past service performance etc or to perform any of a variety of beneficial functions or tasks now known or hereinafter devel oped FIG 4 illustrates an abstracted functional view of the extensible devices and services platform of FIG 3 with par ticular reference to the processing engine 306 as w
48. es platform as illustrated in FIG 3 is a processing engine 306 which can be concentrated at a single server or distributed among several different computing entities with out limitation Processing engine 306 can include engines configured to receive data from a set of devices e g via the Internet or a hubbed network to index the data to analyze the data and or to generate statistics based on the analysis or as part of the analysis The analyzed data can be stored as derived data 308 Results of the analysis or statistics can thereafter be transmitted back to a device providing ops data used to derive the results to other devices to a server provid ing a webpage to a user of the device or to other non device entities For example use statistics use statistics relative to use of other devices use patterns and or statistics summariz ing sensor readings can be transmitted The results or statis tics can be provided via the Internet 262 In this manner processing engine 306 can be configured and programmed to derive a variety of useful information from the operational data obtained from the smart home A single server can include one or more engines The derived data can be highly beneficial at a variety of different granularities for a variety of useful purposes rang ing from explicit programmed control of the devices on a per home per neighborhood or per region basis for example demand response programs for electrical utiliti
49. ese measure ments could be caused by other factors within a single device e g house renovations or romping teenagers causing large accelerometer readings intentionally turning off the power causing low voltage detection measurements faulty sensor readings causing low pressure measurements or a deck cov ering causing low outdoor light intensities By collectively analyzing the data points inter device correlator 510 can better estimate whether a very local event or a more substan tial event caused the sensor readings Consistent and corre lated readings across a set of nearby devices e g across a neighborhood or zip code suggest the presence of a substan tial event Inter device correlator 510 can utilize any of a variety of techniques to collectively analyze the set of data points For example statistics can be performed to determine whether dramatic sensor readings were outliers Similarly clustering techniques can be used to determine whether at least a plu rality of devices exhibited similar extreme sensor readings Location and or time sensitive fitting e g 1 4 or 2 d Gaus sian fitting can be used to characterize whether sensor read ings vary in a continuous manner The analysis performed by inter device correlator 510 e g and data properties analyzed by inter device correlator 510 can include analyses used to predict an event of interest For example earthquake prediction techniques disclosed in Allen et al Rea
50. esult of the fit The param eters can include numeric values to be included within the fitted function e g coefficients powers offsets etc and or one or more quality of fit values At block 820 event occurrence criterion is assessed e g by event detector 512 The assessment can include compar ing one or more fit parameters to one or more thresholds For example a criterion can indicate that an event occurred if a quality of fit parameter exceeded a first value and an ampli tude coefficient of a Gaussian function exceeded a second value In some instances the thresholds are not fixed e g such that lower quality of fit parameters are acceptable when detecting the event occurrence given higher amplitude coef US 8 620 841 B1 21 ficients The assessment can include identifying a binary event occurrence answer a probability metric and or a fidence metric For example a binary event occurrence answer can include Yes indicating that that the event occurred 76 indicating that there is a 76 probability that the event occurred and or 0 6 indicating a confidence metric on a 0 to 1 scale of the Yes or 76 result At block 825 other event properties are estimated e g by event detector 512 The other event properties can include e g a measurement timed or initial event location e g iden tifying its central location or its reach a measurement timed or initial event magnitude a time that the event
51. future event properties can include a future location and or magnitude of the event In some instances the future properties indicate qualitative properties ofthe event such as whether a storm will produce snow hail or rain The future event properties can be fore casted e g based on time sensitive analyses using a predic tive model or based on known trajectory or propagation properties associated with the event type At block 735 entities to be alerted are identified e g by alert engine 516 Block 735 can include identifying locations likely to be affected by the event in the future and identifying devices within the locations The identified entities can then either include those devices or users associated with those devices e g to be alerted via phone text message or email Insome instances block 735 includes identifying entities that requested general alerts e g requesting an alert whenever an event is detected within a nearby area or requesting specific alerts e g recently having requested a local forecast At block 740 alerts are generated and sent to the identified entities e g by alert engine 516 The alerts can include an indication that the event was detected an estimate of the event s past location time or magnitude and or an indication of the event s forecasted future e g its future location arrival time and magnitude FIG 8 illustrates a flowchart for a process 800 of analyzing sensor data po
52. he governance of other energy or resource consuming systems such as water usage systems air usage systems systems involving the usage of other natu ral resources and systems involving the usage of various other forms of energy As illustrated thermostat 1000 includes a user friendly interface according to some embodiments Thermostat 1000 includes control circuitry and is electrically connected to an HVAC system Thermostat 1000 is wall mounted is circular in shape and has an outer rotatable ring 1012 for receiving user input Outer rotatable ring 1012 allows the user to make adjust ments such as selecting a new target temperature For example by rotating outer ring 1012 clockwise a target set point temperature can be increased and by rotating the outer ring 1012 counter clockwise the target setpoint temperature can be decreased A central electronic display 1016 may include e g a dot matrix layout individually addressable such that arbitrary shapes can be generated rather than being a segmented lay out a combination of a dot matrix layout and a segmented layout or a backlit color liquid crystal display LCD An example of information displayed on electronic display 1016 is illustrated in FIG 10A and includes central numerals 1020 that are representative of a current setpoint temperature It will be appreciated that electronic display 1016 can display other types of information such as information identifying or indi
53. hin one or more network connected smart home devices that are each affixed to a home structure or that otherwise have normally stationary dispositions within the home It has been found that network connected thermostats and network connected haz ard detectors are two particularly useful smart home devices within which to embed such sensors although many other examples network connected light switches network con nected doorbells network connected home appliances are also within the scope of the present teachings According to a preferred embodiment the smart home accelerometer equipped or other motion sensing equipped devices within any particular local geographic area such as a ZIP code are programmed and configured to quickly report the occurrence of their individual sensed movements to a common central server such as a cloud based server system which is in turn is programmed and configured to perform correlation calcu lations on the received data to detect the occurrence of an earthquake event and where applicable promptly detect a geographical speed and trajectory of the earthquake event Alarms or other advance warnings can then be promptly communicated to persons geographically located in the path of the earthquake event or to first responders In one particu larly advantageous embodiment the same smart home devices within which the accelerometers movement sensors embedded are also equipped to receive these warning
54. ht appropriate letters and clicking the ring to select the highlighted letter such that the device can communicate over the Internet A user of each device registers the device online using a serial number The user also enters the address of the device location and his phone number A central server receives this data and associates each device with its address in a first database and associates each device with a user phone num ber in a second database The central server communicates with external govern mental agencies that control the official issuance of tornado watches and warning Upon receiving a message from the agency that a tornado watch has been issued the central server looks up devices within the tornado watch area using the first database The central server then sends a message to those devices requesting regular pressure sensor data The devices collect the measurements and communicate the mea surements to the central server The central server routinely analyzes the pressure sensor data and compares an average of a subset of the data e g the data within an 80 9096 range with 096 being the lowest received value and 10096 being the highest to a threshold Upon detecting that the average exceeds the threshold the central server sends an electronic alert over the Internet to the governmental agency Further the central server sends text messages to the smartphones associated with the devices in the tornado watch area indi
55. i cations between the above noted components in support of the computer program product 1205 Exemplary operating US 8 620 841 B1 25 systems include Windows or the like from Microsoft Cor poration Solaris amp from Sun Microsystems LINUX UNIX and the like User input devices 1240 include all possible types of devices and mechanisms to input information to computer system 1102 These may include a keyboard a keypad a mouse a scanner a digital drawing pad a touch screen incor porated into the display audio input devices such as voice recognition systems microphones and other types of input devices In various embodiments user input devices 1240 are typically embodied as a computer mouse a trackball a track pad a joystick wireless remote a drawing tablet a voice command system User input devices 1240 typically allow a user to select objects icons text and the like that appear on the monitor 1106 via a command such as a click of a button or the like User output devices 1230 include all possible types of devices and mechanisms to output information from com puter 1102 These may include a display e g monitor 1106 printers non visual displays such as audio output devices etc Communications interface 1250 provides an interface to other communication networks and devices and may serve as an interface to receive data from and transmit data to other systems WANs and or the Internet 1118 Embodiments of communicati
56. ic activity sensors hazard related environmental sensors micro phones optical sensors and radiation sensors wherein the aggregating processor is configured and pro grammed to receive the first information from each of a plurality of the thermostat devices to forecast a future event based on a collective analysis thereof to identify one or more entities to be alerted ofthe forecasted future event and to transmit second information representative of the forecasted future event to the identified one or more entities 15 The crowdsourced event detection network of claim 14 wherein another thermostat device comprises the aggregating processor 16 The crowdsourced event detection network of claim 14 further comprising a central server that comprises the aggre gating processor 17 The crowdsourced event detection network of claim 14 wherein the at least one non temperature related sensor in each of said population of thermostat devices includes an accelerometer and wherein the central server is configured to forecast earthquake events based on a collective analysis of the received first information derived from motion sensed by said accelerometers 18 The crowdsourced event detection network of claim 14 wherein each said thermostat device further comprises a data receiving and processing component configured to receive data communications from said aggregating processor and to identify therefrom said second information represent
57. ical proximity to other devices collectively analyzing the sensor measurements provided by the thermostat devices to determine whether a large scale event was occurring wherein the determination that a large scale event was occurring requires consis tency between at least two of the sensor measurements provided by the thermostat devices forecasting a future event property wherein the future event property is forecasted based on a same or different collective analysis of the sensor measurements provided by the thermostat devices identifying one or more entities to be alerted of the future event property generating at least one alert identifying the future event property and transmitting the at least one alert to the identified one or more entities 8 The method for forecasting events as recited in claim 7 wherein the one or more entities include a thermostat device not associated with the set of thermostat devices and associ ated with geographic location extending beyond a geographic area associated with the thermostat devices associated with the set of sensor measurements 9 The method for forecasting events as recited in claim 7 wherein transmitting the at least one alert comprises sending a signal to a phone of a user associated with a thermostat device likely to be affected by the event in the future 10 The method for forecasting events as recited in claim 7 wherein the event comprises an earthquake 11 The method
58. ich include fore casts for a region spanned by the plurality of sprinkler sys tems The forecasts are routinely sent to meteorology centers Further a user of the sprinkler system can request a forecast using the sprinkler system user interface or using a website which can receive an identifier of the sprinkler system and or ofthe user A message is transmitted to the central server the message including an indication of the request and an iden tifier of the sprinkler system or the user The central server looks up the coordinates of the sprinkler system and identifies a forecast specific to those coordinates A message with the forecast information is then transmitted back to the user e g 40 45 55 28 back to the sprinkler system or over the Internet via the website and the forecast is displayed to the user Example 3 A variety of devices are provided the devices including smoke detectors wall plug interfaces thermostats and light switches Each device includes a pressure sensor Users pur chase the devices and appropriately positions the device e g mounting it to a wall Each device may be equipped with a user interface having a similar physical look and feel to the user interface of the thermostat device described above with respect to FIGS 10A 10B Each device detects a local wire less network and requests a password A respective user enters the password by rotating a rotatable ring of the device to highlig
59. inter device correlator that accesses the selected set of sensor measurements provided by the thermostat devices and that collectively analyzes the sensor mea surements an event detector that determines whether an event has occurred based on the results of the collective analysis wherein the determination that an event has occurred requires that a criterion involving at least two of the sensor measurements provided by the thermostat devices be satisfied an event forecaster that forecasts a future event property wherein the future event property is forecasted based on a same or different collective analysis of the sensor measurements provided by the thermostat devices and an alert engine that identifies one or more entities to be alerted of the future event property that generates at least one alert identifying the future event property and that transmits the at least one alertto the identified one or more entities 2 The event forecasting system of claim 1 further com prising a device location database that stores for each ther mostat device of a plurality of thermostat devices a location associated with the thermostat device wherein the measurement set identifier accesses the device location database when selecting the set of sen sor measurements provided by the thermostat devices 3 The event forecasting system of claim 1 wherein the event forecaster forecasts the future event property upon a determination that the event h
60. ints to detect event properties For example block 720 of process 700 can include one more or all of blocks 805 820 of process 800 At block 805 weight is applied to each of one more or all sensor data points e g by inter device correlator 510 The weight can represent or be indicative of a reliability of the sensor data point or how informative the sensor data point as to one or more event properties In some instances a plurality of weights are applied to each data point For example a first weight can be used when attempting to determine whether an event occurred or is occurring and one or more second weights can be used to determine a magnitude location or trajectory of the event Thus if a particular device s sensor reliably measured an above threshold reading only when the event occurred but the measurement was otherwise uninfor mative as to the event s magnitude multiple weights could be useful e g weighting more highly the sensor reading to first determine whether an event occurred and then weighting more lowly the sensor reading to determine event properties 0 5 35 40 45 50 65 20 The weight can be identified by e g looking up iden tifier e g a device or sensor identifier in a look up table The look up table can include one or more weights for the iden tifier These stored weights may have been previously deter mined e g by weight adjustment assigner 508 e g by
61. l time earthquake detection and hazard assessment by ElarmS across California Geophysical Research Letters 36 2009 1 6 by Sakaki et al Earthquake shakes Twitter users real time event detection by social sen 20 25 30 35 40 45 50 55 60 65 16 sors WWW 2010 2010 851 860 and or by U S Pat No 6 356 204 each of which is hereby incorporated by reference in its entirety for all purposes can be used Inter device correlator 510 can produce one or more parameters as a result of the analysis The parameters could include e g a reliability metric an extreme sensor reading a time and or location associated with an extreme sensor read ing or one or more fit parameters e g a Gaussian fit ampli tude offset and or width or a quality of fit metric These parameters can be transmitted to an event detector 512 Based on the parameters event detector 512 can estimate whether an event occurred a magnitude of the event a loca tion of the event a past trajectory of the event and or a time of the event For example to determine whether an event occurred event detector 512 can compare a percentage of data points with dramatic sensor measurement values e g beyond one or two standard deviations from the mean or above or below a fixed measurement threshold to a percent age threshold or event detector 512 can compare a quality of fit metric to a threshold Event detector 512 can estimate a location and
62. l to be presented e g to announce the visitor s presence within a room that a user is occupying FIG 2 illustrates an example of a smart home environment within which one or more of the devices methods systems services and or computer program products described fur ther herein can be applicable The depicted smart home envi ronment includes a structure 250 which can include e g a house office building garage or mobile home It will be US 8 620 841 B1 9 appreciated that devices can also be integrated into a smart home environment that does not include an entire structure 250 such as an apartment condominium or office space Further the smart home environment can control and or be coupled to devices outside of the actual structure 250 Indeed several devices in the smart home environment need not physically be within the structure 250 at all For example a device controlling a pool heater or irrigation system can be located outside of the structure 250 The depicted structure 250 includes a plurality of rooms 252 separated at least partly from each other via walls 254 The walls 254 can include interior walls or exterior walls Each room can further include a floor 256 and a ceiling 258 Devices can be mounted on integrated with and or supported by a wall 254 floor or ceiling The smart home depicted in FIG 2 includes a plurality of devices including intelligent multi sensing network con nected devices that
63. les compliance regulations and or rewards and or that uses operation data to determine whether a challenge has been met a rule or regulation has been complied with and or a reward has been earned The challenges rules or regulations can relate to efforts to conserve energy to live safely e g reducing exposure to toxins or carcinogens to conserve money and or equipment life to improve health etc Processing engine 306 can integrate or otherwise utilize extrinsic information 416 from extrinsic sources to improve the functioning of one or more processing paradigms Extrin sic information 416 can be used to interpret operational data received from a device to determine a characteristic of the environment near the device e g outside a structure that the deviceis enclosed in to determine services or products avail able to the user to identify a social network or social network information to determine contact information of entities e g public service entities such as an emergency response team the police or a hospital near the device etc to identify statistical or environmental conditions trends or other infor mation associated with a home or neighborhood and so forth An extraordinary range and variety of benefits can be brought about by and fit within the scope of the described extensible devices and services platform ranging from the ordinary to the profound Thus in one ordinary example each bedroom of the smar
64. lk throughout the house even if light switches are on opposite sides of the room from entryways Specific details are given in the above description to pro videathorough understanding ofthe embodiments However it is understood that the embodiments may be practiced with out these specific details For example circuits may be shown in block diagrams in order not to obscure the embodiments in unnecessary detail In other instances well known circuits processes algorithms structures and techniques may be shown without unnecessary detail in order to avoid obscuring the embodiments Implementation of the techniques blocks steps and means described above may be done in various ways For example these techniques blocks steps and means may be imple mented in hardware software or a combination thereof For a hardware implementation the processing units may be implemented within one or more application specific inte grated circuits ASICs digital signal processors DSPs digital signal processing devices DSPDs programmable logic devices PLDs field programmable gate arrays FP GAs processors controllers micro controllers micropro cessors other electronic units designed to perform the func tions described above and or a combination thereof Also it is noted that the embodiments may be described as a process which is depicted as a flowchart a flow diagram a data flow diagram a structure diagram or a block diagram Al
65. m Estimating the event trajectory can include extrapolating a past trajectory Estimating the event trajectory can also or alternatively include considering characteristics of areas near the event e g land surface properties weather conditions fault line presence or altitude At block 910 a future event location 15 forecasted based on the estimated event trajectory e g by event forecaster 514 The future event location can include a central location e g a center of a tornado or storm or an area For example an earthquake can initially affect a small area around the earth quake s epicenter and can later spread to affect an asymmetri cal ring shaped area Thus an estimate of the ring shaped area can be made The estimated future event location can include e g a range of geographic coordinates a set of zip codes or a list of cities At block 915 devices in the forecasted future event loca tion are identified e g by alert engine 516 The devices can be identified by looking up the future event location in a database e g device locations database 506 The database can be populated with an address coordinate set city and or zip code for each device This data can be provided by user input or by smart device technology e g that uses GPS signals At block 920 alerts are transmitted to the identified devices or to user devices associated with identified devices e g by alert engine 516 For example a user ofa
66. night or when lights are out As yet another example intelligence components 116 can detect hourly weekly or even seasonal trends in user settings and adjust settings accordingly For example intelligence com ponents 116 can detect that a particular device is turned on every week day at 6 30 am or that a device setting is gradually adjusted from a high setting to lower settings over the last three hours Intelligence components 116 can then predict that the device is to be turned on every week day at 6 30 am or that the setting should continue to gradually lower its setting over a longer time period In some instances devices can interact with each other such that events detected by a first device influences actions of a second device For example a first device can detect that a user has pulled into a garage e g by detecting motion in the garage detecting a change in light in the garage or detecting opening of the garage door The first device can transmit this information to a second device such that the second device can e g adjust a home temperature setting a light setting music setting and or a security alarm setting As another example a first device can detect a user approaching a front door e g by detecting motion or sudden light pattern changes The first device can e g cause a general audio or visual signal to be presented e g such as sounding of a doorbell or cause a location specific audio or visual signa
67. of data points can include data points associated with similar locations and or times For example the set of data points can include all data points associated with a same zip code and received within a particular time period e g the last 30 seconds 1 minute 5 minutes 10 minutes 30 minutes 60 minutes 2 hours 6 hours 12 hours or 24 hours As another example the set of data points can include all data points associated with a loca tion that is less than a fixed distance away from a location of an instant data point To illustrate ifa data point indicates that massive acceleration is detected at Location 1 then the data set can include all data points associated with a location less than 1 mile away from Location 1 and received within the last minute In order to identify data points associated with similar locations data set identifier 504 can use a device location database 506 For example each device of a plurality of devices can transmit one or more data points to processing engine 306 over a period of time The data point can include a device ID and a location e g determined based on user inputor location identification technology such as GPS tech 0 5 40 45 60 65 14 nology Processing engine 306 thereafter populate device location database 506 to associate each device ID with the respective location the location including e g geo graphical coordinates a street address a c
68. ome usually needs at least one thermostat While being a greatly beneficial by product of the device subiquity when adapted and configured according to the present teachings the fact that the device can be made part of a life saving crowdsourced earthquake detection network according to the present teachings need not itself be the cen tral reason for that ubiquity In some embodiments an event forecasting system is pro vided A measurement database can store a plurality of sensor measurements each sensor measurement having been pro vided by a non portable electronic device A primary purpose of each respective electronic device can be unrelated to col lecting measurements from a type of sensor that collected the sensor measurement A measurement set identifier can select a set of sensor measurements from the plurality of sensor measurements in the measurement database The electronic devices associated with the set of sensor measurements can be in close geographical proximity relative to their geographical proximity to other devices An inter device correlator can access the selected set of sensor measurements and collec tively analyze the sensor measurements An event detector can determine whether an event has occurred based on the results of the collective analysis The determination that an event has occurred can require that a criterion involving at least two of the sensor measurements be satisfied An event forecaster can forecast a f
69. onnection or other power defi scenario communications component 110 in device 100 can include a component that enables device 100 to communicate with a central server or a remote device such as another device described herein or a portable user device Communi cations component 110 can allow device 100 to communicate via e g Wi Fi ZigBee 3G 4G wireless CAT6 wired Ether net HomePlug or other powerline communications method telephone or optical fiber by way of non limiting examples Communications component 110 can include a wireless card an Ethernet plug or nother transceiver connection modularity unit in device 100 can include a static physi cal connection and a replaceable module 114 Thus the modularity unit can provide the capability to upgrade replace able module 114 without completely reinstalling device 100 e g to preserve wiring The static physical connection can include a docking station 112 which may also be termed an interface box that can attach to a building structure For example docking station 112 could be mounted to a wall via screws or stuck onto a ceiling via adhesive Docking station 112 can in some instances extend through part of the build ing structure For example docking station 112 can connect to wiring e g to 120V line voltage wires behind the wall via a hole made through a wall s sheetrock Docking station 112 can include circuitry such as power connection circuitry
70. ons interface 1250 typically include an Ethernet card a modem telephone satellite cable ISDN a asyn chronous digital subscriber line DSL unit a FireWire interface a USB interface a wireless network adapter and thelike Forexample communications interface 1250 may be coupled to a computer network to a FireWire bus or the like In other embodiments communications interface 1250 may be physically integrated on the motherboard of computer 1102 and or may be a software program or the like RAM 1270 and non volatile storage drive 1280 are examples of tangible computer readable media configured to store data such as computer program product embodiments ofthe present invention including executable computer code human readable code or the like Other types of tangible computer readable media include floppy disks removable hard disks optical storage media such as CD ROMs DVDs bar codes semiconductor memories such as flash memories read only memories ROMs battery backed volatile memo ries networked storage devices and the like RAM 1270 and non volatile storage drive 1280 may be configured to store the basic programming and data constructs that provide the func tionality of various embodiments of the present invention as described above Software instruction sets that provide the functionality of the present invention may be stored in RAM 1270 and non volatile storage drive 1280 These instruction sets or code may b
71. or Unknown The Perfect Climate Comfort Center PC8900A W8900A C Product Data Sheet Honeywell International Inc 2001 44 pages Author Unknown Trane Communicating Thermostats for Fan Coil Trane 2011 32 pages Author Unknown Trane Communicating Thermostats for Heat Pump Control Trane 2011 32 pages Author Unknown Trane Install XL600 Installation Manual Trane 2006 16 pages Author Unknown Trane XL950 Installation Guide Trane 2011 20 pages Author Unknown Venstar T2900Manual Venstar Inc 2008 113 pages Author Unknown VisionPRO 8000 Series Installation Guide Honeywell International Inc 2012 12 pages Author Unknown VisionPRO 8000 Series Operating Manual Honeywell International Inc 2012 96 pages Author Unknown VisionPRO Wi Fi Programmable Thermostat Honeywell International Inc 2012 48 pages Allen et al Real Time Earthquake Detection and Hazard Assess ment by ElarmS Across California Geophysical Research Letters vol 36 L00B08 2009 pp 1 6 Arens et al Demand Response Enabling Technology Development Phase I Report Jun 2003 Nov 2005 Jul 27 P DemandRes UC Papers DR Phasel Report Final Draft Apr 24 26 doc University of California Berkeley pp 1 108 Arens et al New Thermostat Demand Response Enabling Technol ogy Poster University of California Berkeley Jun 10 2004 Bourke Server Load Balancing O Reilly amp Associates Inc Aug 2001 182 pages Delee
72. or time of an event based on when and or where extreme sensor readings occurred or based on an offset fit parameter Event detector 512 can estimate a trajectory based on a tracking locations associated with dramatic measure ment values over a period of time or based on time sensitive fit parameters Event detector 512 can estimate an event mag nitude based on a single dramatic measurement value e g the highest or lowest within the set an average of dramatic measurement values e g an average of the 5 highest or lowest within the set or a fit parameter e g a Gaussian fit amplitude After an event has been detected an event forecaster 514 can make predictions about future characteristics ofthe event For example event forecaster 514 can predict where the event will later move to and when it will reach that destination Event forecaster 514 can predict one or more affected areas which will experience effects of given characteristics of the event These predictions can be made based on past trajecto ries ofthe event e g estimated by event detector 512 and or known trajectory characteristics of the type of event Event forecaster 514 can predict future strengths or characteristic changes of the event For example an earthquake s strength can decrease as it spreads and a precipitation type e g snow rain or hail can change as a storm moves Event character istics can depend on current characteristics of other areas such
73. ounty a city and or a zip code Subsequently if data set identifier 504 is attempt ing to identify a set of data points near a particular location e g alocation associated with an instant data point data set identifier 504 can consult device location database 505 to identify appropriate device IDs and can then search for data points within data point database 502 that are associated with the device IDs A weight adjustment assigner 508 can assign a weight and or adjustment to each of one more or all data point values within the data set The weight can be associated with an estimated reliability or a sensor or device associated with a respective data point value given device can be less reliable than others e g due to its age its model its device type its mounting position e g vertical versus horizontal its location e g upstairs versus downstairs or stability or insulation of an enclosure surrounding or supporting the device e g with older houses being more influenced by external environments than newer houses Weight adjustment assigner 508 can determine a weight to be associated with a device by assessing data point values associated with the device over a period of time A device associated with highly variable data point values can be assigned depending on the embodiment a relatively high weight to indicate that the sensoris sensitiveto environmental changes and provides informative data or a relatively low
74. power and or dim state ofoneor more lights In some instances light switches 208 can further or alternatively control a power state or speed of a fan such as a ceiling fan Each of a plurality of intelligent multi sensing network connected wall plug interfaces 210 can detect occupancy of a room or enclosure and control supply of power to one or more wall plugs e g such that power 15 not supplied to the plug if nobody is at home The smart home may further include a plurality of intelligent multi sensing network connected appliances 212 such as refrigerators stoves and or ovens televisions washers dryers lights inside and or outside the structure 250 stereos intercom systems garage door openers floor fans ceiling fans whole house fans wall air conditioners pool heaters 214 irrigation systems 216 security systems and so forth While descriptions of FIG 2 can identify spe cific sensors and functionalities associated with specific devices it will be appreciated that any ofa variety of sensors and functionalities such as those described throughout the specification can be integrated into the device In addition to containing processing and sensing capabili ties each ofthe devices 202 204 206 208 210 212 214 and 216 can be capable of data communications and information sharing with any other of the devices 202 204 206 208 210 212 214 and 216 devices as well as to any cloud server or any 20 25 30 4
75. pp 1 3 Author Unknown Honeywell Installation Guide FocusPRO TH6000 Series Honeywell International Inc 2012 24 pages Author Unknown Honeywell Operating Manual FocusPRO TH6000 Series Honeywell International Inc 2011 80 pages Author Unknown Honeywell Prestige Product Data Honeywell International Inc 2012 126 pages Author Unknown Honeywell Prestige THX9321 9421 Operating Manual Honeywell International Inc 2011 120 pages Author Unknown Hunter Internet Thermostat Installation Guide Hunter Fan Co 2012 8 pages Author Unknown Lennox ComfortSense 5000 Owners Guide Len nox Industries Inc 2007 32 pages Author Unknown Lennox ComfortSense 7000 Owners Guide Len nox Industries Inc 2009 15 pages Author Unknown Lennox iComfort Manual Lennox Industries Inc 2010 20 pages Author Unknown NetX RP32 WiFi Network Thermostat Specifica tion Sheet Network Thermostat 2012 2 pages Author Unknown RobertShaw Product Manual 9620 Maple Chase Company 2001 14 pages Author Unknown RobertShaw Product Manual 982512 Maple Chase Company 2006 36 pages Author Unknown SYSTXCCUIZ01 V Infinity Control Installation Instructions Carrier Corp 2012 20 pages Author Unknown T8611G Chronotherm IB Deluxe Programmable Heat Pump Thermostat Product Data Honeywell International Inc 1997 24 pages Author Unknown TB PAC TB PHP Base Series Programmable Thermostats Carrier Corp 2012 8 pages Auth
76. products and related busi ness methods for utilizing measurements obtained from a set of distributed sensors to predict events Each sensor within a network of sensors can collect data and transmit the data to a central server The central server can identify the set of sen sors from the network of sensors by e g identifying sensors within a geographical region identifying sensors that trans mitted data within a time period and or identifying sensors that transmitted a particular type of data The central server can then aggregate data across the set of sensors estimate characteristics of a current event e g its existence severity or movement and predict characteristics of the event in the future The central server can then transmit information about the predicted characteristic to one or more devices associated with users likely to be affected by or interested in the future event As a specific example a building can include one or more smart devices such as a thermostat hazard detection unit e g smoke detector and or carbon monoxide detector light switch wall plug interface security system or appliance A _ 0 20 35 40 45 50 55 65 2 network of devices include smart devices across multiple rooms across multiple buildings across cities etc Within a given network the devices can include different device types or same or similar device types Each device within the net work can incl
77. r embodiment software implementing the systems and methods described herein can be stored on a storage medium in the computer 1102 Thus the software can berun from the storage medium in the computer system 1126 Therefore in this embodiment the software can be used whether or not computer 1102 is connected to network router 1112 Printer 1108 may be connected directly to computer 1102 in which case the computer system 1126 can print whether or not it is connected to network router 1112 With reference to FIG 12 an embodiment of a special purpose computer system 1200 is shown For example one or more of intelligent components 116 processing engine 306 and components thereof may be a special purpose computer system 1200 The above methods may be implemented by computer program products that direct a computer system to perform the actions ofthe above described methods and com ponents Each such computer program product may com prise sets of instructions codes embodied on a computer readable medium that directs the processor of a computer system to perform corresponding actions The instructions may be configured to run in sequential order or in parallel such as under different processing threads or in a combi nation thereof After loading the computer program products ona general purpose computer system 1126 it is transformed into the special purpose computer system 1200 Special purpose computer system 1200 comprises a com put
78. rre lated for example to different nutrition programs in local schools FIG 5 illustrates components of processing engine 306 according to an embodiment of the invention Processing engine 306 can receive data points indicative of sensor mea surements from each ofa plurality of devices Each data point can include multiple values such as a continuous scale dis crete scale or binary sensor measurement a measurement time a transmission time a device identifier and or a device location identifier For example a data point can include one or more temperature pressure humidity acceleration or motion detection sensor readings The data point can be stored in a data point database 502 Processing engine 306 can include a data set identifier 504 which can identify a set of data points to analyze In various embodiments different events can initiate the set identifica tion For example a data set can be identified upon receiving a data point with a concerning or unusual sensor measure ment upon receiving a request from a user or other entity for event information or at regular intervals some instances all data within a data set is received from a same device type e g all from sprinkler systems and or relates to measurements of a same or similar type e g all including temperature data In some instances data within a data is received from different device types and or relates to measurements of different types The set
79. ry Memory may be imple mented within the processor or external to the processor As used herein the term memory refers to any type of long term short term volatile nonvolatile or other storage medium and is not to be limited to any particular type of memory or number of memories or type of media upon which memory is stored Moreover as disclosed herein the term storage medium may represent one or more memories for storing data includ ing read only memory ROM random access memory RAM magnetic RAM core memory magnetic disk storage mediums optical storage mediums flash memory devices and or other machine readable mediums for storing informa tion The term machine readable medium includes but is not limited to portable or fixed storage devices optical stor age devices wireless channels and or various other storage mediums capable of storing that contain or carry instruction s and or data EXAMPLES Example 1 Thermostats are provided and each thermostat includes set of accelerometers which detect acceleration in each of three perpendicular directions Users purchase the thermo stat and each user mounts the thermostat on a wall in a dwelling e g in his home Each thermostat detects a local wireless network and requests a password A respective user enters the password by rotating a rotatable ring of the ther mostat to highlight appropriate letters and clicking the ring to select the highlighted lett
80. s and to quickly provide audible and or visual earthquake alarms to home occupants Even if provided only seconds before the earthquake arrival a valuable service is provided because these seconds can be used by the occupant to move to a safer location or position Especially for scenarios in which the network connected smart home devices such as network connected thermo stats network connected hazard detectors etc constitute even modestly popular consumer items there is thereby func tionally formed a crowdsourced earthquake detection net work that can be orders of magnitude larger than known official earthquake detection networks in terms of the number of accelerometer movement sensor nodes provided More US 8 620 841 B1 3 over by virtue of correlations that can be performed for localized neighborhoods or geographies the crowdsourced earthquake detection network can be highly robust against false alarms Thus for example while one house in a neigh borhood might be shaking due to romping teenagers or a nearby passing truck which might trigger a sensed earth quake detection event when considered in isolation the fact that other homes in the community are not shaking will be factored in by the correlations performed by the central server and the false alarm condition will be avoided It is to be appreciated that while crowdsourced earthquake detection based on a population of accelerometer equipped network connected
81. s can include ensuring proper operation of a device given user inputs estimating that e g and responding to an intruder is oris attempting to bein a dwelling detecting a failure of equipment coupled to the device e g a light bulb having burned out implementing or otherwise responding to energy demand response events or alerting a user ofa current or predicted future event or characteristic Processing engine 306 can further include an advertising communication para digm 4105 that estimates characteristics e g demographic information desires and or products of interest of a user based on device usage Services promotions products or upgrades can then be offered or automatically provided to the user Processing engine 306 can further include a social para 410 that uses information from a social network vides information to a social network for example based on device usage and or processes data associated with user and or device interactions with the social network platform For example a user s status as reported to their trusted con tacts on the social network could be updated to indicate when they are home based on light detection security system inac tivation or device usage detectors As another example a user may be able to share device usage statistics with other users Processing engine 306 can include a challenges rules com pliance rewards paradigm 4104 that informs a user of chal lenges ru
82. sensor mea surement value a measurement time a transmission time a device identifier and or a device location identifier At block 710 each sensor data point can be associated with a time and location The time can include a time at which the sensor data point was generated or received or a time within the sensor data point e g a measurement time The location can include a location within the sensor data point or a loca tion associated with a device ID in the sensor data point e g determined based on associations in device locations data base 506 In some instances the sensor data points and the associated times and locations are stored in data point data base 502 It will be appreciated that the plurality of data points can be accessed associated with times and locations and or stored at a same time or at different times e g subsequent to receipt of each data point At block 715 a set of sensor data points is identified e g by data set identifier 504 In some instances this identifica tion is precipitated by and or conditioned on detection of an abnormal sensor measurement in a data point a request by a user or external entity for an event detection or event forecast analysis or passage of a routine time interval The identified set of sensor data points can include those associated with a location within a same geographic region and or those asso ciated with a time within a same time period The geographic region
83. t home can be provided with a smoke fire CO alarm that includes an occupancy sensor wherein the occupancy sensor is also capable of inferring e g by virtue of motion detection facial recognition US 8 620 841 B1 13 audible sound patterns etc whether the occupant is asleep or awake If a serious fire event is sensed the remote security monitoring service or fire department is advised of how many occupants there are in each bedroom and whether those occupants are still asleep or immobile or whether they have properly evacuated the bedroom While this is of course a very advantageous capability accommodated by the described extensible devices and services platform there can be substantially more profound examples that can truly illustrate the potential of a larger intelligence that can be made available By way of perhaps a more profound example the same data bedroom occupancy data that is being used for fire safety can also be repurposed by the processing engine 306 in the context of a social paradigm of neighbor hood child development and education Thus for example the same bedroom occupancy and motion data discussed in the ordinary example can be collected and made available for processing properly anonymized in which the sleep patterns of schoolchildren in a particular ZIP code can be identified and tracked Localized variations in the sleeping patterns of the schoolchildren may be identified and co
84. tem to highlight appropriate letters and clicking the ring to select the highlighted letter such that the sprinkler system can commu nicate over the Internet Each sprinkler system also receives GPS signals and iden tifies its geographic coordinates The sprinkler system then transmits a message to a central server identifying the sprin kler system and the coordinates The central server associates each sprinkler system with its coordinates in a database The sprinkler systems collect measurements from the tem perature humidity and wind sensors for five minutes every hour The sprinkler system averages these measurements across the time period and transmits the averaged measure ments and a device identifier to the central server The central server upon receiving the communication looks up coordinates for the sprinkler system The central server then inputs the coordinates and the average measure ments into a model The model gradually learns about how the average measurements predicts future measurements The learning may involve weighting sensor measurements e g to reduce the influence of likely faulty sensor readings cor relating measurement readings in a first region with later measurement readings in a second region and considering non measurement variables such as the date time of day and topography The model can include utilization of thermody namic and or aerodynamic principles The model outputs regular forecasts wh
85. ter 6 385 510 B1 5 2002 Hoog et al 2008 0317292 Al 12 2008 Baker et al 6 453 687 B2 9 2002 Sharood et al 2009 0045263 Al 2 2009 Mueller et al 6 519 509 B1 2 2003 Nierlich et al 5548967 BS aoi 2009 0171862 7 2009 Harrod et al 348 owling etal 19 2009 0194601 Al 8 2009 Floh 6 574 581 Bl 6 2003 Bohrer et al 6604023 Bl 8 2003 Brown et al 2009 0236433 1 9 2009 Mueller et al 6 619 055 1 9 2003 Addy 2009 0243836 Al 10 2009 McSheffrey keV ended tate OA 340 524 6 619 555 B2 9 2003 Rosen 2009 0243842 1 10 2009 Mitchell et al 6 622 115 BL 9 2003 Brown et al 2009 0254225 Al 10 2009 Boucher et al 6 622 025 B2 9 2003 Carner et al 2009 0259713 Al 10 2009 Blumrich et al 6 645 066 B2 11 2003 Gutta et al 2009 0261174 A1 10 2009 Butler et al 6 769 482 B2 8 2004 Wagner et al 2010 0000239 Al 1 2010 Lifson et al 6 798 341 B1 9 2004 Eckel et al 2010 0006660 Al 1 2010 Leen etal 6 851 621 Bl 2 2005 Wacker et al 2010 0019051 Al 1 2010 Rosen 6 891 838 BL 5 2005 Petite et al 2010 0025483 Al 2 2010 Hoeynck et al 6 909 921 B1 6 2005 Bilger 2010 0070084 Al 3 2010 Steinberg et al Pes p 42 1 et al 2010 0070086 Al 3 2010 Harrod et al 983 es 2010 0070234 Al 3 2010 Steinberg et al 6 997 390 B2 2 2006 Alles 2010 0084482 Al 4 2010 Kennedy et al 7 024 336 B2 4 2006 Salsbury et al 2010 0168924 Al 7 2010 Tessier et al 7 055 759 B2 6 2006 Wacker et al 2010080 A 3010 kaolina stal 7 135 965 B2 11 2006 Chapman Jr et al CRE 7156316
86. though a flowchart may describe the operations as a sequential process many of the operations can be performed in parallel or concurrently In addition the order of the opera tions may be re arranged A process is terminated when its operations are completed but could have additional steps not included in the figure A process may correspond to a method a function a procedure a subroutine a subprogram etc When a process corresponds to a function its termination corresponds to a return of the function to the calling function or the main function Furthermore embodiments may be implemented by hard ware software scripting languages firmware middleware microcode hardware description languages and or any com bination thereof When implemented in software firmware middleware scripting language and or microcode the pro gram code or code segments to perform the necessary tasks may be stored in a machine readable medium such as a stor age medium A code segment or machine executable instruc tion may represent a procedure a function a subprogram a program a routine a subroutine a module a software pack age a script a class or any combination of instructions data structures and or program statements A code segment may be coupled to another code segment or a hardware circuit by passing and or receiving information data arguments parameters and or memory contents Information argu ments parameters data etc may
87. to be alerted of the forecasted future event and to transmit second information representative of the forecasted future event to the identified one or more entities BRIEF DESCRIPTION OF THE DRAWINGS The inventive body of work will be readily understood by referring to the following detailed description in conjunction with the accompanying drawings in which FIG 1 illustrates an example of general device components which can be included in an intelligent network connected device FIG 2 illustrates an example ofa smart home environment within which one or more of the devices methods systems services and or computer program products described fur ther herein can be applicable FIG 3 illustrates a network level view of an extensible devices and services platform with which a smart home envi ronment can be integrated FIG 4 illustrates an abstracted functional view of the extensible devices and services platform of FIG 3 FIG 5 illustrates components of processing engine accord ing to an embodiment of the invention US 8 620 841 B1 5 FIGS 6A and 6B illustrate flowcharts for processes 600a of transmitting data from a device 100 to a remote server in accordance with an embodiment of the invention FIG 7 illustrates a flowchart for a process of analyzing sensor data points to forecast event properties FIG 8 illustrates a flowchart for a process of analyzing sensor data points to detect event properties FIG 9 illustr
88. ude one or more sensors e g to detect motion of the sensor motion of an external object temperature humidity or pressure Data indicative ofthe sensor measure ments can be conditionally transmitted e g upon detection ofan abnormal event or regularly transmitted by a respective device to a central server The central server can correlate the data across a set of devices in order to estimate whether readings are due to a sensor malfunction a stationary event or a moving event For example accelerometer readings from a set of devices within a locality e g within a zip code can be used to estimate whether an earthquake is occurring tem perature readings from a set of devices within a locality e g within a city can be used to estimate weather patterns and motion detection readings from a set of devices within a locality within a set of rooms can be used to estimate a trajectory ofa person within a building The central server can then predict characteristics ofa future event e g its location and or strength and can send alerts to other devices within a region predicted to be affected The other devices can then alert users ofthe event or can automatically implement device settings to prepare for the event According to one or more preferred embodiments directed particularly to earthquake detection and prediction it has been found particularly advantageous to embed one or more accelerometers or similar movement sensors wit
89. unctionalities According to some embodiments thermostat 1000 includes a processing system 1060 display driver 1064 and a wireless communications system 1066 Processing system 1060 is adapted to cause the display driver 1064 and display area 1016 to display information to the user and to receiver user input via the rotatable ring 1012 Processing system 1060 according to some embodiments is capable of carrying out the governance of the operation of thermostat 1000 including the user interface features described herein Pro cessing system 1060 is further programmed and configured to carry out other operations as described herein For example processing system 1060 may be programmed and configured to dynamically determine when to collect sensor measure ments when to transmit sensor measurements and or how to present received alerts According to some embodiments wireless communications system 1066 is used to communi cate with e g a central server other thermostats personal computers or portable devices e g laptops or cell phones Referring next to FIG 11 an exemplary environment with which embodiments may be implemented is shown with a computer system 1100 that can be used by a user 1104 to remotely control for example one or more of the sensor equipped smart home devices according to one or more ofthe embodiments The computer system 1110 can alternatively be used for carrying out one or more of the server based processing
90. users to ensure that users are provided with notice in as much advance as possible In some instances users can pull for alerts For example a user can request a local forecast or request the probability of a nearby hail storm reaching a current location or home location While some embodiments herein indicate or imply that processing engine 306 is located within a central server it will be appreciated that in some instances other devices can include processing engine 306 Thus devices 100 can com municate in a peer to peer manner For example a device that detects a potentially concerning or important event can trans mit data point to one or more nearby devices e g in different rooms or different buildings The nearby devices could then determine whether a large scale event is occurring by com paring its data to that of the other device s and if so transmit alerts to yet more devices As another example the device can pull data points from nearby devices determine whether a large scale event is occurring and 50 transmit alerts to yet more devices As yet another example each device can rou tinely transmit data points to nearby devices such that a device can instantly estimate whether a large scale event is occurring FIG 6A illustrates a flowchart for a process 600 of trans mitting data from a device 100 to a remote server in accor dance with an embodiment of the invention At block 605 a sensor measurement is det
91. ut one meter so that the thermo stat 1000 can initiate waking up when the user is approach ing the thermostat and prior to the user touching the thermo stat Ambient light sensor 1070B can be used for a variety of intelligence gathering purposes such as for facilitating con firmation of occupancy when sharp rising or falling edges are detected because it is likely that there are occupants who are turning the lights on and off and such as for detecting long term e g 24 hour patterns of ambient light intensity for confirming and or automatically establishing the time of day According to some embodiments for the combined pur poses of inspiring user confidence and further promoting visual and functional elegance thermostat 1000 is controlled by only two types of user input the first being a rotation of the outer ring 1012 as shown in FIG 10 referenced hereafter as a rotate ring or ring rotation input and the second being an inward push on an outer cap 1008 see FIG 10B until an audible and or tactile click occurs referenced hereafter as an inward click or simply click input Upon detecting a user click new options can be presented to the user For example a menu system can be presented as detailed in U S Ser No 13 351 668 which is hereby incorporated by refer ence in its entirety for all purposes The user can then navigate through the menu options and select menu settings using the rotation and click f
92. uture event property The future event property can be forecasted based on a same or different collective analysis of the sensor measurements An alert engine can identify one or more entities to be alerted of the future event property can generate at least one alert identify 15 20 25 30 35 40 45 50 55 60 65 4 ing the future event property and can transmit the at least one alert to the identified one or more entities In some embodiments a method for forecasting events is provided A plurality of sensor measurements in a measure ment database can be stored each sensor measurement hav ing been provided by a mounted electronic device A primary purpose of at least one respective electronic device can be not related to collecting measurements from a type of sensor that collected the sensor measurement A set of sensor measure ments from the plurality of sensor measurements in the mea surement database can be selected The electronic devices associated with the set of sensor measurements be in close geographical proximity relative to their geographical prox imity to other devices The sensor measurements can be col lectively analyzed to determine whether a large scale event was occurring The determination that a large scale event was occurring can require consistency between at least two of the sensor measurements A future event property can be fore casted The future event property can be forecast
93. uw Ecobee WiFi Enabled Smart Thermostat Part 2 The Fea tures Review Retrieved from URL http www homenetworkenabled com content php 136 ecobee WiFi enabled Smart Thermostat Part 2 The Features review gt Dec 2 2011 5 pages Gao et al The Self Programming Thermostat Optimizing Setback Schedules Based on Home Occupancy Patterns in Proceedings ofthe First ACM Workshop on Embedded Sensing Systems for Energy Efficiency in Buildings Nov 3 2009 6 pages Loisos et al Buildings End Use Energy Efficiency Alternatives to Compressor Cooling California Energy Commission Public Interest Energy Research Jan 2000 80 pages Lu et al The Smart Thermostat Using Occupancy Sensors to Save Energy in Homes in Proceedings of the 8th ACM Conference on Embedded Networked Sensor Systems Nov 3 5 2010 pp 211 224 Mozer The Neural Network House An Environmental that Adapts to it s Inhabitants AAAI Technical Report SS 98 02 1998 pp 110 114 International Search Report and Written Opinion mailed Nov 2 2012 in Application No PCT US2012 053502 filed Aug 31 2012 Sakaki et al Earthquake Shakes Twitter Users Real time Event Detection by Social Sensors in Proceedings ofthe Nineteenth Inter national WWW Conference Apr 26 30 2010 10 pages White et al A Conceptual Model for Simulation Load Balancing Proc 1998 Spring Simulation Interoperability Workshop 1998 7 pages Honeywell Prestige THX9321 and TXH9421 Product D
94. ware of an existence of a secondary sensor One or more user interface components 104 in device 100 may be configured to present information to a user via a visual display e g a thin film transistor display or organic light emitting diode display and or an audio speaker User inter face component 104 can also include one or more user input components to receive information from a user such as a touchscreen buttons scroll component e g a movable or virtual ring component microphone or camera e g to detect gestures In one embodiment user input component 104 includes a click and rotate annular ring component wherein a user can interact with the component by rotating the ring e g to adjust a setting and or by clicking the ring inwards e g to select an adjusted setting or to select an option In another embodiment user input component 104 includes a camera such that gestures can be detected e g to indicate that a power or alarm state of a device is to be changed A power supply component in device 100 may include a power connection 106 and or local battery 108 For example power connection 106 can connect device 100 to a power source such as a line voltage source In some instances con nection 106 to an AC power source can be used to repeatedly charge a e g rechargeable local battery 108 such that bat US 8 620 841 B1 7 tery 108 can later be used to supply power if needed in the event of an AC power disc
95. weight to indicate that the sensor is likely uncalibrated or malfunctioning In some instances data point values over the time period are compared to data point values from other devices e g near the instant device A high weight can be assigned to a device with data point values well correlated with or predictive of data point values of the other devices Weights can be dynamically adjusted by e g repeatedly analyzing recently received data points e g by redefining an analyzed time period to bea recent time period A weight can include e g a number such as a scaled number e g between 0 1 In some instances it might be determined that the data point values are likely inaccurate but they can nonetheless be informative In some instances the data point values have little to no inaccuracy but exhibit an inconsistency with other data point values due to e g different device models sensor types or device types In these cases it can be advantageous to highly weight the data point values but also to adjust the values For example a sensor can be biased to always collect biased measurements e g 10 units or 10 above actual values or measurements with a nonlinear bias Data point value inaccuracies or inconsistencies can be due to variation across devices in a device s mounting position a device s location or a property of an enclosure surrounding or sup porting the device Weight adjustment assigner 508 can determine

Dynamic distributed-sensor thermostat network for forecasting

Contents

Download Pdf Manuals

Related Search

Related Contents