{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T04:51:12Z","timestamp":1750308672097,"version":"3.41.0"},"reference-count":55,"publisher":"Association for Computing Machinery (ACM)","issue":"1","license":[{"start":{"date-parts":[[2014,11,7]],"date-time":"2014-11-07T00:00:00Z","timestamp":1415318400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/100000144","name":"Division of Computer and Network Systems","doi-asserted-by":"publisher","award":["CNS-1253506 and CNS-1250180"],"award-info":[{"award-number":["CNS-1253506 and CNS-1250180"]}],"id":[{"id":"10.13039\/100000144","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Sen. Netw."],"published-print":{"date-parts":[[2014,11,7]]},"abstract":"<jats:p>Wireless sensor network applications, such as those for natural disaster warning, vehicular traffic monitoring, and surveillance, have stringent accuracy requirements for detecting or classifying events and demand long system lifetimes. Through quantitative study, we show that existing event detection approaches are challenged to explore the sensing capability of a deployed system and choose the right sensors to meet user-specified accuracy. Event detection systems are also challenged to provide a generic system that efficiently adapts to environmental dynamics and works easily with a range of applications, machine learning approaches, and sensor modalities. Consequently, we propose Watchdog, a modality-agnostic event detection framework that clusters the right sensors to meet user-specified detection accuracy during runtime while significantly reducing energy consumption. Watchdog can use different machine learning techniques to learn the sensing capability of a heterogeneous sensor deployment and meet accuracy requirements. To address environmental dynamics and ensure energy savings, Watchdog wakes up and puts to sleep sensors as needed to meet user-specified accuracy. Through evaluation with real vehicle detection trace data and a building traffic monitoring testbed of IRIS motes, we demonstrate the superior performance of Watchdog over existing solutions in terms of meeting user-specified detection accuracy, energy savings, and environmental adaptability.<\/jats:p>","DOI":"10.1145\/2575788","type":"journal-article","created":{"date-parts":[[2014,11,18]],"date-time":"2014-11-18T14:21:03Z","timestamp":1416320463000},"page":"1-28","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":8,"title":["A Learning-Based Approach to Confident Event Detection in Heterogeneous Sensor Networks"],"prefix":"10.1145","volume":"11","author":[{"given":"Matthew","family":"Keally","sequence":"first","affiliation":[{"name":"College of William and Mary, Williamsburg, VA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gang","family":"Zhou","sequence":"additional","affiliation":[{"name":"College of William and Mary, Williamsburg, VA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guoliang","family":"Xing","sequence":"additional","affiliation":[{"name":"Michigan State University, East Lansing, MI"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David T.","family":"Nguyen","sequence":"additional","affiliation":[{"name":"College of William and Mary, Williamsburg, VA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xin","family":"Qi","sequence":"additional","affiliation":[{"name":"College of William and Mary, Williamsburg, VA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2014,11,7]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/984622.984684"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/1322263.1322285"},{"volume-title":"Pattern Recognition and Machine Learning","author":"Bishop C.","key":"e_1_2_1_3_1","unstructured":"C. Bishop . 2006. Pattern Recognition and Machine Learning . Springer . C. Bishop. 2006. Pattern Recognition and Machine Learning. Springer."},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/1161089.1161102"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1007\/BF00940812"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/TC.2002.1146711"},{"key":"e_1_2_1_7_1","volume-title":"Retrieved","author":"0","year":"2014","unstructured":"Chipcon Products. CC242 0 2. 4 GHz IEEE 802.15.4\/ZigBee-Ready RF Transceiver . Retrieved June 23, 2014 , from http:\/\/www.ti.com\/lit\/ds\/symlink\/cc2420.pdf. Chipcon Products. CC2420 2.4 GHz IEEE 802.15.4\/ZigBee-Ready RF Transceiver. Retrieved June 23, 2014, from http:\/\/www.ti.com\/lit\/ds\/symlink\/cc2420.pdf."},{"volume-title":"Proceedings of the 30th International Conference on Very Large Databases (VLDB'04)","author":"Deshpande A.","key":"e_1_2_1_8_1","unstructured":"A. Deshpande , C. Carlos , S. Madden , J. Hellerstein , and W. Hong . 2004. Model-driven data acquisition in sensor networks . In Proceedings of the 30th International Conference on Very Large Databases (VLDB'04) . 588--599. A. Deshpande, C. Carlos, S. Madden, J. Hellerstein, and W. Hong. 2004. Model-driven data acquisition in sensor networks. In Proceedings of the 30th International Conference on Very Large Databases (VLDB'04). 588--599."},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jpdc.2004.03.020"},{"volume-title":"Proceedings of the 4th International Symposium on Information Processing in Sensor Networks (IPSN'05)","author":"Dutta P.","key":"e_1_2_1_10_1","unstructured":"P. Dutta , M. Grimmer , A. Arora , S. Bibyk , and D. Culler . 2005. Design of a wireless sensor network platform for detecting rare, random, and ephemeral events . In Proceedings of the 4th International Symposium on Information Processing in Sensor Networks (IPSN'05) . 497--502. P. Dutta, M. Grimmer, A. Arora, S. Bibyk, and D. Culler. 2005. Design of a wireless sensor network platform for detecting rare, random, and ephemeral events. In Proceedings of the 4th International Symposium on Information Processing in Sensor Networks (IPSN'05). 497--502."},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/1869983.1869997"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/1378600.1378605"},{"volume-title":"Proceedings of the 4th International Symposium on Information Processing in Sensor Networks (IPSN'05)","author":"Ermis E. B.","key":"e_1_2_1_13_1","unstructured":"E. B. Ermis and V. Saligrama . 2005. Adaptive statistical sampling methods for decentralized estimation and detection of localized phenomena . In Proceedings of the 4th International Symposium on Information Processing in Sensor Networks (IPSN'05) . 143--150. E. B. Ermis and V. Saligrama. 2005. Adaptive statistical sampling methods for decentralized estimation and detection of localized phenomena. In Proceedings of the 4th International Symposium on Information Processing in Sensor Networks (IPSN'05). 143--150."},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/2461381.2461387"},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/1134680.1134693"},{"key":"e_1_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-00224-3_11"},{"key":"e_1_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/1182807.1182835"},{"key":"e_1_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/1098918.1098941"},{"key":"e_1_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/RTSS.2008.40"},{"key":"e_1_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/1138127.1138128"},{"volume-title":"Proceedings of the 32nd Conference of the IAHR.","author":"Hill D. J.","key":"e_1_2_1_21_1","unstructured":"D. J. Hill , B. S. Minsker , and E. Amir . 2007. Real-time Bayesian anomaly detection for environmental sensor data . In Proceedings of the 32nd Conference of the IAHR. D. J. Hill, B. S. Minsker, and E. Amir. 2007. Real-time Bayesian anomaly detection for environmental sensor data. In Proceedings of the 32nd Conference of the IAHR."},{"key":"e_1_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1029\/2008WR006956"},{"key":"e_1_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/984622.984685"},{"key":"e_1_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/1322263.1322291"},{"volume-title":"Proceedings of the 4th International Symposium on Sensor Networks (IPSN'05)","author":"Isler V.","key":"e_1_2_1_25_1","unstructured":"V. Isler and R. Bajcsy . 2005. The sensor selection problem for bounded uncertainty sensing models . In Proceedings of the 4th International Symposium on Sensor Networks (IPSN'05) . 151--158. V. Isler and R. Bajcsy. 2005. The sensor selection problem for bounded uncertainty sensing models. In Proceedings of the 4th International Symposium on Sensor Networks (IPSN'05). 151--158."},{"key":"e_1_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/1378600.1378630"},{"key":"e_1_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1109\/RTAS.2010.15"},{"key":"e_1_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/2070942.2070968"},{"key":"e_1_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/1791212.1791227"},{"key":"e_1_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1126\/science.220.4598.671"},{"key":"e_1_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/1921621.1921625"},{"key":"e_1_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/1080829.1080859"},{"key":"e_1_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1145\/1460412.1460434"},{"key":"e_1_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/1322263.1322278"},{"key":"e_1_2_1_36_1","volume-title":"IRIS Mote Specifications","author":"MSIC","year":"2014","unstructured":"ME MSIC IRIS. IRIS Mote Specifications . 2014 . Available at http:\/\/www.memsic.com\/userfiles\/files\/Datasheets\/WSN\/IRIS_Datasheet.pdf. MEMSIC IRIS. IRIS Mote Specifications. 2014. Available at http:\/\/www.memsic.com\/userfiles\/files\/Datasheets\/WSN\/IRIS_Datasheet.pdf."},{"key":"e_1_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1145\/1644038.1644049"},{"key":"e_1_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2007.30"},{"volume-title":"Proceedings of the 4th International Symposium on Information Processing in Sensor Networks (IPSN'05)","author":"Rachlin Y.","key":"e_1_2_1_39_1","unstructured":"Y. Rachlin , R. Negi , and P. Khosla . 2005. Sensing capacity for discrete sensor network applications . In Proceedings of the 4th International Symposium on Information Processing in Sensor Networks (IPSN'05) . 126--132. Y. Rachlin, R. Negi, and P. Khosla. 2005. Sensing capacity for discrete sensor network applications. In Proceedings of the 4th International Symposium on Information Processing in Sensor Networks (IPSN'05). 126--132."},{"key":"e_1_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/1031495.1031518"},{"key":"e_1_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1145\/1182807.1182833"},{"key":"e_1_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1145\/1031495.1031497"},{"key":"e_1_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1145\/1460412.1460432"},{"key":"e_1_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1109\/RTSS.2006.19"},{"volume-title":"Distributed Detection and Data Fusion","author":"Varshney P.","key":"e_1_2_1_45_1","unstructured":"P. Varshney . 1996. Distributed Detection and Data Fusion . Springer . P. Varshney. 1996. Distributed Detection and Data Fusion. Springer."},{"key":"e_1_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1145\/1247660.1247676"},{"key":"e_1_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.1145\/984622.984628"},{"key":"e_1_2_1_48_1","doi-asserted-by":"publisher","DOI":"10.1145\/1127777.1127799"},{"key":"e_1_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.1145\/1614320.1614338"},{"key":"e_1_2_1_50_1","doi-asserted-by":"publisher","DOI":"10.1145\/1077391.1077394"},{"key":"e_1_2_1_51_1","doi-asserted-by":"publisher","DOI":"10.1145\/958491.958498"},{"key":"e_1_2_1_52_1","volume-title":"Proceedings of the 27th Conference on Computer Communications (INFOCOM'08)","author":"Yang G.","year":"2020","unstructured":"G. Yang , V. Shukla , and D. Qiao . 2008. A novel on-demand framework for collaborative object detection in sensor networks . In Proceedings of the 27th Conference on Computer Communications (INFOCOM'08) . IEEE, Los Alamitos, CA , 2020 --2028. G. Yang, V. Shukla, and D. Qiao. 2008. A novel on-demand framework for collaborative object detection in sensor networks. In Proceedings of the 27th Conference on Computer Communications (INFOCOM'08). IEEE, Los Alamitos, CA, 2020--2028."},{"key":"e_1_2_1_53_1","doi-asserted-by":"publisher","DOI":"10.1109\/RTSS.2008.39"},{"volume-title":"Proceedings of the 5th European Conference on Wireless Sensor Networks (EWSN'08)","author":"Zappi P.","key":"e_1_2_1_54_1","unstructured":"P. Zappi , C. Lombriser , T. Steifmeier , E. Farella , D. Roggen , L. Benini , and G. Troster . 2008. Activity recognition from on-body sensors: Accuracy-power trade-off by dynamic sensor selection . In Proceedings of the 5th European Conference on Wireless Sensor Networks (EWSN'08) . 17--33. P. Zappi, C. Lombriser, T. Steifmeier, E. Farella, D. Roggen, L. Benini, and G. Troster. 2008. Activity recognition from on-body sensors: Accuracy-power trade-off by dynamic sensor selection. In Proceedings of the 5th European Conference on Wireless Sensor Networks (EWSN'08). 17--33."},{"key":"e_1_2_1_55_1","doi-asserted-by":"publisher","DOI":"10.1109\/79.985685"},{"key":"e_1_2_1_56_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDCS.2007.83"}],"container-title":["ACM Transactions on Sensor Networks"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/2575788","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/2575788","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T20:00:44Z","timestamp":1750276844000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/2575788"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,11,7]]},"references-count":55,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2014,11,7]]}},"alternative-id":["10.1145\/2575788"],"URL":"https:\/\/doi.org\/10.1145\/2575788","relation":{},"ISSN":["1550-4859","1550-4867"],"issn-type":[{"type":"print","value":"1550-4859"},{"type":"electronic","value":"1550-4867"}],"subject":[],"published":{"date-parts":[[2014,11,7]]},"assertion":[{"value":"2012-05-01","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2013-12-01","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2014-11-07","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}