{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T19:47:47Z","timestamp":1775072867437,"version":"3.50.1"},"reference-count":92,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2021,12,6]],"date-time":"2021-12-06T00:00:00Z","timestamp":1638748800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100006133","name":"Advanced Research Projects Agency-Energy","doi-asserted-by":"publisher","award":["DE-AR0000938"],"award-info":[{"award-number":["DE-AR0000938"]}],"id":[{"id":"10.13039\/100006133","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JSAN"],"abstract":"<jats:p>Many regions of the world benefit from heating, ventilating, and air-conditioning (HVAC) systems to provide productive, comfortable, and healthy indoor environments, which are enabled by automatic building controls. Due to climate change, population growth, and industrialization, HVAC use is globally on the rise. Unfortunately, these systems often operate in a continuous fashion without regard to actual human presence, leading to unnecessary energy consumption. As a result, the heating, ventilation, and cooling of unoccupied building spaces makes a substantial contribution to the harmful environmental impacts associated with carbon-based electric power generation, which is important to remedy. For our modern electric power system, transitioning to low-carbon renewable energy is facilitated by integration with distributed energy resources. Automatic engagement between the grid and consumers will be necessary to enable a clean yet stable electric grid, when integrating these variable and uncertain renewable energy sources. We present the WHISPER (Wireless Home Identification and Sensing Platform for Energy Reduction) system to address the energy and power demand triggered by human presence in homes. The presented system includes a maintenance-free and privacy-preserving human occupancy detection system wherein a local wireless network of battery-free environmental, acoustic energy, and image sensors are deployed to monitor homes, record empirical data for a range of monitored modalities, and transmit it to a base station. Several machine learning algorithms are implemented at the base station to infer human presence based on the received data, harnessing a hierarchical sensor fusion algorithm. Results from the prototype system demonstrate an accuracy in human presence detection in excess of 95%; ongoing commercialization efforts suggest approximately 99% accuracy. Using machine learning, WHISPER enables various applications based on its binary occupancy prediction, allowing situation-specific controls targeted at both personalized smart home and electric grid modernization opportunities.<\/jats:p>","DOI":"10.3390\/jsan10040071","type":"journal-article","created":{"date-parts":[[2021,12,7]],"date-time":"2021-12-07T03:21:05Z","timestamp":1638847265000},"page":"71","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["WHISPER: Wireless Home Identification and Sensing Platform for Energy Reduction"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9394-5393","authenticated-orcid":false,"given":"Margarite","family":"Jacoby","sequence":"first","affiliation":[{"name":"Department of Civil, Environmental and Architectural Engineering, University of Colorado, Boulder, CO 80309, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4318-7026","authenticated-orcid":false,"given":"Sin Yong","family":"Tan","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, Iowa State University, Ames, IA 50011, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5410-4452","authenticated-orcid":false,"given":"Mohamad","family":"Katanbaf","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, University of Washington, Seattle, WA 98195, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3466-445X","authenticated-orcid":false,"given":"Ali","family":"Saffari","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, University of Washington, Seattle, WA 98195, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9688-2268","authenticated-orcid":false,"given":"Homagni","family":"Saha","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, Iowa State University, Ames, IA 50011, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6240-5511","authenticated-orcid":false,"given":"Zerina","family":"Kapetanovic","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, University of Washington, Seattle, WA 98195, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7966-8462","authenticated-orcid":false,"given":"Jasmine","family":"Garland","sequence":"additional","affiliation":[{"name":"Department of Civil, Environmental and Architectural Engineering, University of Colorado, Boulder, CO 80309, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8998-6106","authenticated-orcid":false,"given":"Anthony","family":"Florita","sequence":"additional","affiliation":[{"name":"National Renewable Energy Laboratory, Golden, CO 80401, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4084-9709","authenticated-orcid":false,"given":"Gregor","family":"Henze","sequence":"additional","affiliation":[{"name":"Department of Civil, Environmental and Architectural Engineering, University of Colorado, Boulder, CO 80309, USA"},{"name":"National Renewable Energy Laboratory, Golden, CO 80401, USA"},{"name":"Renewable and Sustainable Energy Institute, Boulder, CO 80309, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2613-5291","authenticated-orcid":false,"given":"Soumik","family":"Sarkar","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, Iowa State University, Ames, IA 50011, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5331-4770","authenticated-orcid":false,"given":"Joshua","family":"Smith","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, University of Washington, Seattle, WA 98195, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,12,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1038\/s41558-019-0666-7","article-title":"Climate change now detectable from any single day of weather at global scale","volume":"10","author":"Sippel","year":"2020","journal-title":"Nat. Clim. Chang."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"eaaw6974","DOI":"10.1126\/science.aaw6974","article-title":"The human imperative of stabilizing global climate change at 1.5 \u00b0C","volume":"365","author":"Jacob","year":"2019","journal-title":"Science"},{"key":"ref_3","unstructured":"IPCC (2019). Climate Change and Land: An IPCC Special Report on Climate Change, Desertification, Land Degradation, Sustainable Land Management, Food Security, and Greenhouse Gas Fluxes in Terrestrial Ecosystems, IPCC."},{"key":"ref_4","unstructured":"Berry, C., Lawson, G., and Woodward, M. (2018). Highlights from the 2015 RECS: Energy Consumption, Expenditures, and End-Use Modeling, Technical Report."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Lu, J., Sookoor, T., Srinivasan, V., Gao, G., Holben, B., Stankovic, J., Field, E., and Whitehouse, K. (2010). The Smart Thermostat: Using Occupancy Sensors to Save Energy in Homes. Proceedings of the 8th ACM Conference on Embedded Networked Sensor Systems, Association for Computing Machinery. SenSys \u201910.","DOI":"10.1145\/1869983.1870005"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Gao, G., and Whitehouse, K. (2009). The Self-Programming Thermostat: Optimizing Setback Schedules Based on Home Occupancy Patterns. Proceedings of the First ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Buildings, Association for Computing Machinery. BuildSys \u201909.","DOI":"10.1145\/1810279.1810294"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Soltanaghaei, E., and Whitehouse, K. (2016). WalkSense: Classifying Home Occupancy States Using Walkway Sensing. Proceedings of the 3rd ACM International Conference on Systems for Energy-Efficient Built Environments, Association for Computing Machinery. BuildSys \u201916.","DOI":"10.1145\/2993422.2993576"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"190","DOI":"10.1016\/j.erss.2015.06.002","article-title":"Energy efficiency and the misuse of programmable thermostats: The effectiveness of crowdsourcing for understanding household behavior","volume":"8","author":"Pritoni","year":"2015","journal-title":"Energy Res. Soc. Sci."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2529","DOI":"10.1016\/j.buildenv.2011.06.002","article-title":"How people use thermostats in homes: A review","volume":"46","author":"Peffer","year":"2011","journal-title":"Build. Environ."},{"key":"ref_10","unstructured":"Meier, A. (2010, January 14\u201317). How people actually use thermostats. Proceedings of the American Council for an Energy-Efficient Economy Conference, ACEEE (2010), Sacramento, CA, USA."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Ayan, O., and Turkay, B. (2018, January 25\u201327). Smart Thermostats for Home Automation Systems and Energy Savings from Smart Thermostats. Proceedings of the 2018 6th International Conference on Control Engineering Information Technology (CEIT), Istanbul, Turkey.","DOI":"10.1109\/CEIT.2018.8751790"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"062013","DOI":"10.1088\/1757-899X\/609\/6\/062013","article-title":"Reduction of HVAC system runtime due to occupancy-controlled smart thermostats in contemporary multi-unit residential building suites","volume":"609","author":"Stopps","year":"2019","journal-title":"IOP Conf. Ser. Mater. Sci. Eng."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"101228","DOI":"10.1016\/j.erss.2019.101228","article-title":"Going smart, staying confused: Perceptions and use of smart thermostats in British homes","volume":"57","author":"Miu","year":"2019","journal-title":"Energy Res. Soc. Sci."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"469","DOI":"10.1016\/j.enbuild.2016.05.024","article-title":"Do occupancy-responsive learning thermostats save energy? A field study in university residence halls","volume":"127","author":"Pritoni","year":"2016","journal-title":"Energy Build."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Bustamante, S., Castro, P., Laso, A., Manana, M., and Arroyo, A. (2017). Smart thermostats: An experimental facility to test their capabilities and savings potential. Sustainability, 9.","DOI":"10.3390\/su9081462"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Wang, J., Garifi, K., Baker, K., Zuo, W., Zhang, Y., Huang, S., and Vrabie, D. (2020). Optimal Renewable Resource Allocation and Load Scheduling of Resilient Communities. Energies, 13.","DOI":"10.3390\/en13215683"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Garifi, K., Baker, K., Touri, B., and Christensen, D. (2018, January 5\u20139). Stochastic Model Predictive Control for Demand Response in a Home Energy Management System. Proceedings of the 2018 IEEE Power Energy Society General Meeting (PESGM), Portland, OR, USA.","DOI":"10.1109\/PESGM.2018.8586485"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Roth, A., and Reyna, J. (2019). Grid-Interactive Efficient Buildings Technical Report Series: Whole-Building Controls, Sensors, Modeling, and Analytics, USDOE Office of Energy Efficiency and Renewable Energy (EERE); Energy Efficiency Office and National Renewable Energy Laboratory (NREL). Technical Report.","DOI":"10.2172\/1580329"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1007\/s40518-019-00140-5","article-title":"Potential Impacts of Transportation and Building Electrification on the Grid: A Review of Electrification Projections and Their Effects on Grid Infrastructure, Operation, and Planning","volume":"6","author":"Blonsky","year":"2019","journal-title":"Curr. Sustain. Energy Rep."},{"key":"ref_20","unstructured":"U.S. Energy Information Administration (2021, December 02). Monthly Energy Review, Available online: https:\/\/www.eia.gov\/totalenergy\/data\/monthly\/archive\/00352104.pdf."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Turley, C., Jacoby, M., Pavlak, G., and Henze, G. (2020). Development and evaluation of occupancy-aware HVAC control for residential building energy efficiency and occupant comfort. Energies, 13.","DOI":"10.3390\/en13205396"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Melfi, R., Rosenblum, B., Nordman, B., Christensen, K., Nordman, B., and Meier, A. (2011, January 25\u201328). Measuring Building Occupancy Using Existing Network Infrastructure. Proceedings of the 2011 International Green Computing Conference and Workshops, Orlando, FL, USA.","DOI":"10.1109\/IGCC.2011.6008560"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1016\/j.enbuild.2015.02.028","article-title":"Occupancy measurement in commercial office buildings for demand-driven control applications\u2014A survey and detection system evaluation","volume":"93","author":"Labeodan","year":"2015","journal-title":"Energy Build."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1564","DOI":"10.1109\/TIA.1984.4504642","article-title":"Ultrasonic Technology Provides for Control of Lighting","volume":"IA-20","author":"Stolshek","year":"1984","journal-title":"IEEE Trans. Ind. Appl."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Yang, D., Xu, B., Rao, K., and Sheng, W. (2018). Passive infrared (PIR)-based indoor position tracking for smart homes using accessibility maps and a-star algorithm. Sensors, 18.","DOI":"10.3390\/s18020332"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"849","DOI":"10.1109\/JSEN.2011.2161667","article-title":"Ultrasonic arrays for localized presence sensing","volume":"12","author":"Caicedo","year":"2012","journal-title":"IEEE Sens. J."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"415","DOI":"10.1177\/1477153510376225","article-title":"The performance of occupancy-based lighting control systems: A review","volume":"42","author":"Guo","year":"2010","journal-title":"Light. Res. Technol."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"230","DOI":"10.1016\/j.aei.2016.12.008","article-title":"Leveraging existing occupancy-related data for optimal control of commercial office buildings: A review","volume":"33","author":"Shen","year":"2017","journal-title":"Adv. Eng. Inform."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"106154","DOI":"10.1016\/j.buildenv.2019.05.032","article-title":"Opportunistic occupancy-count estimation using sensor fusion: A case study","volume":"159","author":"Hobson","year":"2019","journal-title":"Build. Environ."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1033","DOI":"10.1016\/j.enbuild.2005.12.001","article-title":"Building occupancy detection through sensor belief networks","volume":"38","author":"Dodier","year":"2006","journal-title":"Energy Build."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"268","DOI":"10.1016\/j.rser.2014.01.090","article-title":"A review on lighting control technologies in commercial buildings, their performance and affecting factors","volume":"33","author":"Haq","year":"2014","journal-title":"Renew. Sustain. Energy Rev."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Liu, X., Ghosh, P., Ulutan, O., Manjunath, B.S., Chan, K., and Govindan, R. (2019, January 10\u201313). Caesar: Cross-camera complex activity recognition. Proceedings of the 17th Conference on Embedded Networked Sensor Systems, SenSys 2019, New York, NY, USA.","DOI":"10.1145\/3356250.3360041"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"736","DOI":"10.1016\/j.compeleceng.2017.11.011","article-title":"Video surveillance systems-current status and future trends","volume":"70","author":"Tsakanikas","year":"2018","journal-title":"Comput. Electr. Eng."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Dalal, N., Triggs, B., Schmid, C., Dalal, N., Triggs, B., Schmid, C., Detection, H., and Oriented, U. (2006, January 7\u201313). Human Detection using Oriented Histograms of Flow and Appearance. Proceedings of the European Conference on Computer Vision (ECCV \u201906), Graz, Austria.","DOI":"10.1007\/11744047_33"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1016\/j.buildenv.2019.04.015","article-title":"Implicit Sensing of Building Occupancy Count with Information and Communication Technology Data Sets","volume":"157","author":"Howard","year":"2019","journal-title":"Build. Environ."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"109965","DOI":"10.1016\/j.enbuild.2020.109965","article-title":"A review of building occupancy measurement systems","volume":"216","author":"Sun","year":"2020","journal-title":"Energy Build."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3275520","article-title":"A framework for privacy-preserving data publishing with enhanced utility for cyber-physical systems","volume":"14","author":"Jia","year":"2018","journal-title":"ACM Trans. Sens. Netw."},{"key":"ref_38","unstructured":"Beymer, D. (2000, January 7\u20138). Person counting using stereo. Proceedings of the Workshop on Human Motion, Austin, TX, USA."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Yang, C.E., Shen, Y.T., and Liao, S.H. (2020, January 23\u201325). Integration of Real-time Facial Recognition and Visualization in BIM. Proceedings of the 2020 IEEE Eurasia Conference on IOT, Communication and Engineering (ECICE), Yunlin, Taiwan.","DOI":"10.1109\/ECICE50847.2020.9301999"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Wang, X., and Tague, P. (2014). Non-Invasive User Tracking via Passive Sensing: Privacy Risks of Time-Series Occupancy Measurement. Proceedings of the 2014 Workshop on Artificial Intelligent and Security Workshop, Association for Computing Machinery. AISec \u201914.","DOI":"10.1145\/2666652.2666655"},{"key":"ref_41","unstructured":"Ahmad, J., Larijani, H., Emmanuel, R., Mannion, M., and Javed, A. (2018). Occupancy detection in non-residential buildings\u2014A survey and novel privacy preserved occupancy monitoring solution. Appl. Comput. Inform., 1\u20139."},{"key":"ref_42","unstructured":"Schwee, J.H., Sangogboye, F.C., and Kj\u00e6rgaard, M.B. (2019, January 15). Evaluating Practical Privacy Attacks for Building Data Anonymized by Standard Methods. Proceedings of the 2nd InternationalWorkshop on Security and Privacy for the Internet-of-Things (IoTSec), London, UK."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Jia, R., Dong, R., Sastry, S.S., and Spanos, C.J. (2017, January 18\u201321). Privacy-enhanced architecture for occupancy-based HVAC Control. Proceedings of the 8th International Conference on Cyber-Physical Systems, Pittsburgh, PA, USA.","DOI":"10.1145\/3055004.3055007"},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Pappachan, P., Degeling, M., Yus, R., Das, A., Bhagavatula, S., Melicher, W., Naeini, P.E., Zhang, S., Bauer, L., and Kobsa, A. (2017, January 5\u20138). Towards Privacy-Aware Smart Buildings: Capturing, Communicating, and Enforcing Privacy Policies and Preferences. Proceedings of the 2017 IEEE 37th International Conference on Distributed Computing Systems Workshops (ICDCSW), Atlanta, GA, USA.","DOI":"10.1109\/ICDCSW.2017.52"},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Raij, A., Ghosh, A., Kumar, S., and Srivastava, M. (2011, January 7\u201312). Privacy risks emerging from the adoption of innocuous wearable sensors in the mobile environment. Proceedings of the ACM CHI Conference on Human Factors in Computing System, Vancouver, BC, Canada.","DOI":"10.1145\/1978942.1978945"},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Nicolai, T., and Kenn, H. (2007, January 10\u201312). About the relationship between people and discoverable Bluetooth devices in urban environments. Proceedings of the Mobility Conference 2007\u2014The 4th Int. Conf. Mobile Technology, Applications and Systems, Mobility 2007, Incorporating the 1st Int. Symp. Computer Human Interaction in Mobile Technology, IS-CHI 2007, Singapore.","DOI":"10.1145\/1378063.1378076"},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Park, J.Y., Mbata, E., and Nagy, Z. (2019, January 13\u201314). Good to see you again: Capture and recapture method on mobile devices to estimate occupancy profiles. Proceedings of the BuildSys 2019\u2014The 6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation, New York, NY, USA.","DOI":"10.1145\/3360322.3360869"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"344","DOI":"10.1016\/j.enbuild.2015.12.019","article-title":"Review of occupancy sensing systems and occupancy modeling methodologies for the application in institutional buildings","volume":"121","author":"Yang","year":"2016","journal-title":"Energy Build."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"278","DOI":"10.1016\/j.enbuild.2019.02.030","article-title":"Occupancy sensing in buildings: A review of data analytics approaches","volume":"188\u2013189","author":"Saha","year":"2019","journal-title":"Energy Build."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"106177","DOI":"10.1016\/j.buildenv.2019.106177","article-title":"Comparison of machine learning models for occupancy prediction in residential buildings using connected thermostat data","volume":"160","author":"Huchuk","year":"2019","journal-title":"Build. Environ."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1016\/j.enbuild.2007.01.018","article-title":"A generalised stochastic model for the simulation of occupant presence","volume":"40","author":"Page","year":"2008","journal-title":"Energy Build."},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Mosiman, C., Henze, G., and Els, H. (2021). Development and Application of Schema Based Occupant-Centric Building Performance Metrics. Energies, 14.","DOI":"10.3390\/en14123513"},{"key":"ref_53","first-page":"17","article-title":"A Review of the Energy Performance Gap and Its Underlying Causes in Non-Domestic Buildings","volume":"1","author":"Dowson","year":"2016","journal-title":"Front. Mech. Eng."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"260","DOI":"10.1016\/j.enbuild.2018.03.084","article-title":"Building occupancy estimation and detection: A review","volume":"169","author":"Chen","year":"2018","journal-title":"Energy Build."},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Arvidsson, S., Gullstrand, M., Sirmacek, B., and Riveiro, M. (2021). Sensor Fusion and Convolutional Neural Networks for Indoor Occupancy Prediction Using Multiple Low-Cost Low-Resolution Heat Sensor Data. Sensors, 21.","DOI":"10.3390\/s21041036"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"110863","DOI":"10.1016\/j.enbuild.2021.110863","article-title":"Real-time occupancy detection with physics-informed pattern-recognition machines based on limited CO2 and temperature sensors","volume":"242","author":"Kampezidou","year":"2021","journal-title":"Energy Build."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"106966","DOI":"10.1016\/j.buildenv.2020.106966","article-title":"A comprehensive review of approaches to building occupancy detection","volume":"180","author":"Rueda","year":"2020","journal-title":"Build. Environ."},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Khan, A., Pl\u00f6tz, T., Nicholson, J., Mellor, S., Jackson, D., Ladha, K., Ladha, C., Hand, J., Clarke, J., and Olivier, P. (2014, January 5\u20136). Occupancy monitoring using environmental & context sensors and a hierarchical analysis framework. Proceedings of the BuildSys \u201914: 1st ACM Conference on Embedded Systems for Energy-Efficient Buildings, Memphis, TN, USA.","DOI":"10.1145\/2674061.2674080"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1080\/19401493.2011.577810","article-title":"Building energy and comfort management through occupant behaviour pattern detection based on a large-scale environmental sensor network","volume":"4","author":"Dong","year":"2011","journal-title":"J. Build. Perform. Simul."},{"key":"ref_60","unstructured":"Google Store (2020, December 02). Nest Learning Thermostat. Available online: https:\/\/store.google.com\/us\/product\/nest_learning_thermostat_3rd_gen."},{"key":"ref_61","unstructured":"Malinick, T., Wilairat, N., Holmes, J., and Perry, L. (2012, January 12\u201317). Destined to Disappoint: Programmable Thermostat Savings are Only as Good as the Assumptions about Their Operating Characteristics. Proceedings of the 2012 ACEEE Summer Study on Energy Efficiency in Buildings, Pacific Grove, CA, USA."},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"Yang, R., and Newman, M.W. (2013, January 8\u201312). Learning from a learning thermostat. Proceedings of the UbiComp: Home Heating, Zurich, Switzerland.","DOI":"10.1145\/2493432.2493489"},{"key":"ref_63","unstructured":"Hernandez, G., Arias, O., Buentello, D., and Jin, Y. (2014). Smart Nest Thermostat: A Smart Spy in Your Home. Black Hat USA, Available online: https:\/\/scholar.google.com\/scholar?as_q=From+today\u2019s+Intranet+of+things+to+a%0A+future+Internet+of+Things%3A+A+wireless-and+mobility-related+view&as_occt=title&hl=en&as_sdt=0%2C31."},{"key":"ref_64","unstructured":"Albergotti, R. (The Washington Post, 2019). How Nest, designed to keep intruders out of people\u2019s homes, effectively allowed hackers to get in, The Washington Post."},{"key":"ref_65","doi-asserted-by":"crossref","unstructured":"Moody, M., and Hunter, A. (2016, January 12\u201314). Exploiting known vulnerabilities of a smart thermostat. Proceedings of the 2016 14th Annual Conference on Privacy, Security and Trust (PST), Auckland, New Zealand.","DOI":"10.1109\/PST.2016.7906936"},{"key":"ref_66","doi-asserted-by":"crossref","unstructured":"Gulati, M., Ram, S.S., and Singh, A. (2014, January 3\u20136). An in depth study into using EMI signatures for appliance identification. Proceedings of the BuildSys 2014\u20141st ACM Conference on Embedded Systems for Energy-Efficient Buildings, Memphis, TN, USA.","DOI":"10.1145\/2674061.2674070"},{"key":"ref_67","doi-asserted-by":"crossref","unstructured":"Gupta, S., Reynolds, M.S., and Patel, S.N. (2010, January 26\u201329). ElectriSense. Proceedings of the 12th ACM International Conference on Ubiquitous Computing\u2014Ubicomp \u201910, Copenhagen, Denmark.","DOI":"10.1145\/1864349.1864375"},{"key":"ref_68","doi-asserted-by":"crossref","unstructured":"Kleiminger, W., Beckel, C., and Santini, S. (2015, January 7\u201311). Household Occupancy Monitoring Using Electricity Meters. Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2015), Osaka, Japan.","DOI":"10.1145\/2750858.2807538"},{"key":"ref_69","first-page":"1","article-title":"LoRa Backscatter: Enabling The Vision of Ubiquitous Connectivity","volume":"1","author":"Talla","year":"2017","journal-title":"Proc. ACM Interact. Mob. Wearable Ubiquitous Technol."},{"key":"ref_70","doi-asserted-by":"crossref","unstructured":"Saffari, A., Hessar, M., Naderiparizi, S., and Smith, J.R. (2019, January 25\u201327). Battery-Free Wireless Video Streaming Camera System. Proceedings of the 2019 IEEE International Conference on RFID (RFID), Pisa, Italy.","DOI":"10.1109\/RFID.2019.8719264"},{"key":"ref_71","doi-asserted-by":"crossref","unstructured":"Liu, V., Parks, A., Talla, V., Gollakota, S., Wetherall, D., and Smith, J.R. (2013). Ambient Backscatter: Wireless Communication out of Thin Air. Proceedings of the ACM SIGCOMM 2013 Conference on SIGCOMM, ACM. SIGCOMM \u201913.","DOI":"10.1145\/2486001.2486015"},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"2608","DOI":"10.1109\/TIM.2008.925019","article-title":"Design of an RFID-Based Battery-Free Programmable Sensing Platform","volume":"57","author":"Sample","year":"2008","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_73","doi-asserted-by":"crossref","unstructured":"Hessar, M., Naderiparizi, S., Wang, Y., Saffari, A., Gollakota, S., and Smith, J.R. (2018, January 10\u201315). Wireless Video Streaming for Ultra-low-power Cameras. Proceedings of the 16th Annual International Conference on Mobile Systems, Applications, and Services, Munich, Germany.","DOI":"10.1145\/3210240.3211109"},{"key":"ref_74","doi-asserted-by":"crossref","unstructured":"Katanbaf, M., Saffari, A., and Smith, J.R. (October, January 28). Receiver Selectivity Limits on Bistatic Backscatter Range. Proceedings of the 2020 IEEE International Conference on RFID (RFID), Orlando, FL, USA.","DOI":"10.1109\/RFID49298.2020.9244826"},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3397314","article-title":"Relacks: Reliable Backscatter Communication in Indoor Environments","volume":"4","author":"Katanbaf","year":"2020","journal-title":"Proc. ACM Interact. Mob. Wearable Ubiquitous Technol."},{"key":"ref_76","unstructured":"Saffari, A. (2021). WideScatter: Toward Wide Area Battery-Free Wireless Sensor Networks. [Master\u2019s Thesis, University of Washington]."},{"key":"ref_77","doi-asserted-by":"crossref","unstructured":"Tan, S.Y., Saha, H., Florita, A.R., Henze, G.P., and Sarkar, S. (2019, January 10\u201312). A flexible framework for building occupancy detection using spatiotemporal pattern networks. Proceedings of the 2019 American Control Conference (ACC), Philadelphia, PA, USA.","DOI":"10.23919\/ACC.2019.8815089"},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"625","DOI":"10.1016\/j.sigpro.2011.08.013","article-title":"Optimization of symbolic feature extraction for pattern classification","volume":"92","author":"Sarkar","year":"2012","journal-title":"Signal Process."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"524","DOI":"10.1016\/j.ifacol.2020.12.324","article-title":"Granger Causality Based Hierarchical Time Series Clustering for State Estimation","volume":"53","author":"Tan","year":"2020","journal-title":"IFAC-PapersOnLine"},{"key":"ref_80","doi-asserted-by":"crossref","unstructured":"Saffari, A., Tan, S.Y., Katanbaf, M., Saha, H., Smith, J.R., and Sarkar, S. (2021). Battery-Free Camera Occupancy Detection System. Proceedings of the 5th International Workshop on Embedded and Mobile Deep Learning, Association for Computing Machinery. EMDL\u201921.","DOI":"10.1145\/3469116.3470013"},{"key":"ref_81","doi-asserted-by":"crossref","unstructured":"Andrews, J., Kowsika, M., Vakil, A., and Li, J. (2020, January 20\u201323). A motion induced passive infrared (PIR) sensor for stationary human occupancy detection. Proceedings of the 2020 IEEE\/ION Position, Location and Navigation Symposium (PLANS), Portland, OR, USA.","DOI":"10.1109\/PLANS46316.2020.9109909"},{"key":"ref_82","doi-asserted-by":"crossref","unstructured":"Leech, C., Raykov, Y.P., Ozer, E., and Merrett, G.V. (2017, January 13\u201315). Real-time room occupancy estimation with Bayesian machine learning using a single PIR sensor and microcontroller. Proceedings of the 2017 IEEE Sensors Applications Symposium (SAS), Glassboro, NJ, USA.","DOI":"10.1109\/SAS.2017.7894091"},{"key":"ref_83","doi-asserted-by":"crossref","unstructured":"Raykov, Y.P., Ozer, E., Dasika, G., Boukouvalas, A., and Little, M.A. (2016, January 12\u201316). Predicting room occupancy with a single passive infrared (PIR) sensor through behavior extraction. Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, Heidelberg, Germany.","DOI":"10.1145\/2971648.2971746"},{"key":"ref_84","doi-asserted-by":"crossref","unstructured":"Zhang, Y.D., Mandal, J.K., So-In, C., and Thakur, N.V. (2020). Problems with PIR Sensors in Smart Lighting+Security Solution and Solutions of Problems. Smart Trends in Computing and Communications, Springer.","DOI":"10.1007\/978-981-15-0077-0"},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"188","DOI":"10.1016\/j.enbuild.2016.03.038","article-title":"Occupant behavior in building energy simulation: Towards a fit-for-purpose modeling strategy","volume":"121","author":"Gaetani","year":"2016","journal-title":"Energy Build."},{"key":"ref_86","first-page":"2825","article-title":"Scikit-learn: Machine Learning in Python","volume":"12","author":"Pedregosa","year":"2011","journal-title":"J. Mach. Learn. Res."},{"key":"ref_87","unstructured":"Seabold, S., and Perktold, J. (July, January 28). statsmodels: Econometric and statistical modeling with python. Proceedings of the 9th Python in Science Conference, Austin, TX, USA."},{"key":"ref_88","doi-asserted-by":"crossref","unstructured":"Brockwell, P.J., and Davis, R.A. (2016). Introduction to Time Series and Forecasting, Springer International Publishing.","DOI":"10.1007\/978-3-319-29854-2"},{"key":"ref_89","unstructured":"ARPA-E (2021, December 05). SENSOR: Saving Energy Nationwide in Structures with Occupancy Recognition, Available online: https:\/\/arpa-e.energy.gov\/?q=arpa-e-programs\/sensor."},{"key":"ref_90","doi-asserted-by":"crossref","first-page":"119539","DOI":"10.1016\/j.energy.2020.119539","article-title":"Data driven occupancy information for energy simulation and energy use assessment in residential buildings","volume":"218","author":"Panchabikesan","year":"2021","journal-title":"Energy"},{"key":"ref_91","doi-asserted-by":"crossref","first-page":"164","DOI":"10.1109\/MCOM.2017.1700791","article-title":"Enabling Healthcare in Smart Homes: The SPHERE IoT Network Infrastructure","volume":"56","author":"Elsts","year":"2018","journal-title":"IEEE Commun. Mag."},{"key":"ref_92","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1371\/journal.pone.0141694","article-title":"A Validated Smartphone-Based Assessment of Gait and Gait Variability in Parkinson\u2019s Disease","volume":"10","author":"Ellis","year":"2015","journal-title":"PLoS ONE"}],"container-title":["Journal of Sensor and Actuator Networks"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2224-2708\/10\/4\/71\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:40:06Z","timestamp":1760168406000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2224-2708\/10\/4\/71"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,12,6]]},"references-count":92,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2021,12]]}},"alternative-id":["jsan10040071"],"URL":"https:\/\/doi.org\/10.3390\/jsan10040071","relation":{},"ISSN":["2224-2708"],"issn-type":[{"value":"2224-2708","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,12,6]]}}}