{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T11:59:39Z","timestamp":1753358379222,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":35,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,11,17]],"date-time":"2021-11-17T00:00:00Z","timestamp":1637107200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,11,17]]},"DOI":"10.1145\/3486611.3486658","type":"proceedings-article","created":{"date-parts":[[2021,11,18]],"date-time":"2021-11-18T01:24:25Z","timestamp":1637198665000},"page":"71-80","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["PIRMedic"],"prefix":"10.1145","author":[{"given":"Ashish","family":"Kashinath","sequence":"first","affiliation":[{"name":"University of Illinois at Urbana-Champaign"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sibin","family":"Mohan","sequence":"additional","affiliation":[{"name":"Oregon State University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Akshay","family":"Nambi","sequence":"additional","affiliation":[{"name":"Microsoft Research, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sumukh","family":"Marathe","sequence":"additional","affiliation":[{"name":"University of Michigan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2021,11,17]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"Application Note Murata PIR Sensor. https:\/\/www.murata.eom\/~\/media\/webrenewal\/products\/sensor\/infrared\/applinote_pir.ashx?la=ja-jp.  Application Note Murata PIR Sensor. https:\/\/www.murata.eom\/~\/media\/webrenewal\/products\/sensor\/infrared\/applinote_pir.ashx?la=ja-jp."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/STA.2015.7505190"},{"key":"e_1_3_2_1_3_1","volume-title":"Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal statistical society: series B (Methodological), 57(1):289--300","author":"Benjamini Yoav","year":"1995","unstructured":"Yoav Benjamini and Yosef Hochberg . Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal statistical society: series B (Methodological), 57(1):289--300 , 1995 . Yoav Benjamini and Yosef Hochberg. Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal statistical society: series B (Methodological), 57(1):289--300, 1995."},{"key":"e_1_3_2_1_4_1","first-page":"95","volume-title":"Proceedings of the 16th ACM SenSys","author":"Chakraborty Tusher","year":"2018","unstructured":"Tusher Chakraborty , Akshay Uttama Nambi , Ranveer Chandra , Rahul Sharma , Manohar Swaminathan , Zerina Kapetanovic , and Jonathan Appavoo . Fall-curve : A novel primitive for iot fault detection and isolation . In Proceedings of the 16th ACM SenSys , page 95 -- 107 , 2018 . Tusher Chakraborty, Akshay Uttama Nambi, Ranveer Chandra, Rahul Sharma, Manohar Swaminathan, Zerina Kapetanovic, and Jonathan Appavoo. Fall-curve: A novel primitive for iot fault detection and isolation. In Proceedings of the 16th ACM SenSys, page 95--107, 2018."},{"key":"e_1_3_2_1_5_1","volume-title":"tsfresh. https:\/\/github.com\/blue-yonder\/tsfresh","author":"Christ Maximilian","year":"2018","unstructured":"Maximilian Christ . tsfresh. https:\/\/github.com\/blue-yonder\/tsfresh , 2018 . Maximilian Christ. tsfresh. https:\/\/github.com\/blue-yonder\/tsfresh, 2018."},{"key":"e_1_3_2_1_6_1","volume-title":"Shap xgboost implementation. https:\/\/github.com\/slundberg\/shap","author":"Christ Maximilian","year":"2020","unstructured":"Maximilian Christ . Shap xgboost implementation. https:\/\/github.com\/slundberg\/shap , 2020 . Maximilian Christ. Shap xgboost implementation. https:\/\/github.com\/slundberg\/shap, 2020."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2018.03.067"},{"key":"e_1_3_2_1_8_1","volume-title":"Distributed and parallel time series feature extraction for industrial big data applications. arXiv preprint arXiv:1610.07717","author":"Christ Maximilian","year":"2016","unstructured":"Maximilian Christ , Andreas W Kempa-Liehr , and Michael Feindt . Distributed and parallel time series feature extraction for industrial big data applications. arXiv preprint arXiv:1610.07717 , 2016 . Maximilian Christ, Andreas W Kempa-Liehr, and Michael Feindt. Distributed and parallel time series feature extraction for industrial big data applications. arXiv preprint arXiv:1610.07717, 2016."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2016.7472216"},{"volume-title":"Ultrasonic, Office White. https:\/\/www.hubbell.com\/hubbell\/en\/Products\/Electrical-Electronic\/Wiring-Devices\/Lighting-Controls\/CeilingWall-Sensors\/ATD2000CRP\/p\/1545054?location=&brandCode=WDK","year":"2020","key":"e_1_3_2_1_10_1","unstructured":"Hubbell. Ceiling Hard Wired Occupancy Sensor, 2,000 sq ft Passive Infrared , Ultrasonic, Office White. https:\/\/www.hubbell.com\/hubbell\/en\/Products\/Electrical-Electronic\/Wiring-Devices\/Lighting-Controls\/CeilingWall-Sensors\/ATD2000CRP\/p\/1545054?location=&brandCode=WDK , 2020 . Hubbell. Ceiling Hard Wired Occupancy Sensor, 2,000 sq ft Passive Infrared, Ultrasonic, Office White. https:\/\/www.hubbell.com\/hubbell\/en\/Products\/Electrical-Electronic\/Wiring-Devices\/Lighting-Controls\/CeilingWall-Sensors\/ATD2000CRP\/p\/1545054?location=&brandCode=WDK, 2020."},{"volume-title":"Ultrasonic, Office White. https:\/\/www.hubbell.com\/wiringdevice-kellems\/en\/Products\/Electrical-Electronic\/Wiring-Devices\/Lighting-Controls\/CeilingWall-Sensors\/ATD1600WRP\/p\/1545050","year":"2020","key":"e_1_3_2_1_11_1","unstructured":"Hubbell. Wall Hard Wired Occupancy Sensor, 1,600 sq ft Passive Infrared , Ultrasonic, Office White. https:\/\/www.hubbell.com\/wiringdevice-kellems\/en\/Products\/Electrical-Electronic\/Wiring-Devices\/Lighting-Controls\/CeilingWall-Sensors\/ATD1600WRP\/p\/1545050 , 2020 . Hubbell. Wall Hard Wired Occupancy Sensor, 1,600 sq ft Passive Infrared, Ultrasonic, Office White. https:\/\/www.hubbell.com\/wiringdevice-kellems\/en\/Products\/Electrical-Electronic\/Wiring-Devices\/Lighting-Controls\/CeilingWall-Sensors\/ATD1600WRP\/p\/1545050, 2020."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/1140104.1140114"},{"key":"e_1_3_2_1_13_1","first-page":"4765","volume-title":"Advances in Neural Information Processing Systems","volume":"30","author":"Lundberg Scott M","year":"2017","unstructured":"Scott M Lundberg and Su-In Lee . A unified approach to interpreting model predictions. In I. Guyon, U. V. Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, and R. Garnett, editors , Advances in Neural Information Processing Systems , volume 30 , pages 4765 -- 4774 . Curran Associates, Inc. , 2017 . Scott M Lundberg and Su-In Lee. A unified approach to interpreting model predictions. In I. Guyon, U. V. Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, and R. Garnett, editors, Advances in Neural Information Processing Systems, volume 30, pages 4765--4774. Curran Associates, Inc., 2017."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2018.2853660"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/3450268.3453535"},{"key":"e_1_3_2_1_16_1","volume-title":"The kolmogorov-smirnov test for goodness of fit. Journal of the American statistical Association, 46(253):68--78","author":"Massey Frank J","year":"1951","unstructured":"Frank J Massey Jr . The kolmogorov-smirnov test for goodness of fit. Journal of the American statistical Association, 46(253):68--78 , 1951 . Frank J Massey Jr. The kolmogorov-smirnov test for goodness of fit. Journal of the American statistical Association, 46(253):68--78, 1951."},{"key":"e_1_3_2_1_17_1","volume-title":"kstest2: Two sample Kolmogorov-Smirnov test. https:\/\/www.mathworks.com\/help\/stats\/kstest2.html","author":"Documentation Mathworks MATLAB","year":"2015","unstructured":"MATLAB Documentation Mathworks . kstest2: Two sample Kolmogorov-Smirnov test. https:\/\/www.mathworks.com\/help\/stats\/kstest2.html , 2015 . MATLAB Documentation Mathworks. kstest2: Two sample Kolmogorov-Smirnov test. https:\/\/www.mathworks.com\/help\/stats\/kstest2.html, 2015."},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/AUTEST.2016.7589589"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/2737095.2742561"},{"key":"e_1_3_2_1_20_1","unstructured":"PIR Fresnel Lens Infrared Fresnel Lens. https:\/\/3dlens.com\/pir-fresnel-lens.php.  PIR Fresnel Lens Infrared Fresnel Lens. https:\/\/3dlens.com\/pir-fresnel-lens.php."},{"volume-title":"AMN22111 Industrial Devices. https:\/\/bit.ly\/3Al6lvU","year":"2021","key":"e_1_3_2_1_21_1","unstructured":"Panasonic. AMN22111 Industrial Devices. https:\/\/bit.ly\/3Al6lvU , 2021 . Panasonic. AMN22111 Industrial Devices. https:\/\/bit.ly\/3Al6lvU, 2021."},{"volume-title":"AMN23111 Industrial Devices. https:\/\/bit.ly\/2VSawjM","year":"2021","key":"e_1_3_2_1_22_1","unstructured":"Panasonic. AMN23111 Industrial Devices. https:\/\/bit.ly\/2VSawjM , 2021 . Panasonic. AMN23111 Industrial Devices. https:\/\/bit.ly\/2VSawjM, 2021."},{"volume-title":"https:\/\/bit.ly\/2Y8Dj51","author":"Sensor Evaluation PIR","key":"e_1_3_2_1_23_1","unstructured":"PIR Sensor Evaluation Board (IMX-070, IMX-060), Murata. https:\/\/bit.ly\/2Y8Dj51 . PIR Sensor Evaluation Board (IMX-070, IMX-060), Murata. https:\/\/bit.ly\/2Y8Dj51."},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4419-9326-7_1"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/3365871.3365872"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939912.2942354"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/2737095.2737113"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/1754414.1754419"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/3458864.3466869"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.comnet.2016.11.019"},{"issue":"16","key":"e_1_3_2_1_31_1","first-page":"6249","article-title":"Blind drift calibration of sensor networks using sparse bayesian learning","volume":"16","author":"Wang Y.","year":"2016","unstructured":"Y. Wang , A. Yang , Z. Li , X. Chen , P. Wang , and H. Yang . Blind drift calibration of sensor networks using sparse bayesian learning . IEEE Sensors Journal , 16 ( 16 ): 6249 -- 6260 , 2016 . Y. Wang, A. Yang, Z. Li, X. Chen, P. Wang, and H. Yang. Blind drift calibration of sensor networks using sparse bayesian learning. IEEE Sensors Journal, 16(16):6249--6260, 2016.","journal-title":"IEEE Sensors Journal"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/570738.570747"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2007.1067"},{"key":"e_1_3_2_1_34_1","first-page":"73","volume-title":"Proceedings of the 11th ACM IPSN","author":"Xiang Yun","year":"2012","unstructured":"Yun Xiang , Lan Bai , Ricardo Piedrahita , Robert P. Dick , Qin Lv , Michael Hannigan , and Li Shang . Collaborative calibration and sensor placement for mobile sensor networks . In Proceedings of the 11th ACM IPSN , page 73 -- 84 , 2012 . Yun Xiang, Lan Bai, Ricardo Piedrahita, Robert P. Dick, Qin Lv, Michael Hannigan, and Li Shang. Collaborative calibration and sensor placement for mobile sensor networks. In Proceedings of the 11th ACM IPSN, page 73--84, 2012."},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.snb.2015.05.060"}],"event":{"name":"BuildSys '21: The 8th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation","sponsor":["SIGEnergy ACM Special Interest Group on Energy Systems and Informatics"],"location":"Coimbra Portugal","acronym":"BuildSys '21"},"container-title":["Proceedings of the 8th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3486611.3486658","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3486611.3486658","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T20:48:40Z","timestamp":1750193320000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3486611.3486658"}},"subtitle":["physics-driven fault diagnosis for PIR sensors"],"short-title":[],"issued":{"date-parts":[[2021,11,17]]},"references-count":35,"alternative-id":["10.1145\/3486611.3486658","10.1145\/3486611"],"URL":"https:\/\/doi.org\/10.1145\/3486611.3486658","relation":{},"subject":[],"published":{"date-parts":[[2021,11,17]]},"assertion":[{"value":"2021-11-17","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}