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Auton. Adapt. Syst."],"published-print":{"date-parts":[[2017,3,31]]},"abstract":"<jats:p>Sampling rate adaptation is a critical issue in many resource-constrained networked systems, including Wireless Sensor Networks (WSNs). Existing algorithms are primarily employed to detect events such as objects or physical changes at a high, low, or fixed frequency sampling usually adapted by a central unit or a sink, therefore requiring additional resource usage. Additionally, this algorithm potentially makes a network unable to capture a dynamic change or event of interest, which therefore affects monitoring quality. This article studies the problem of a fully autonomous adaptive sampling regarding the presence of a change or event. We propose a novel scheme, termed \u201cevent-sensitive adaptive sampling and low-cost monitoring (e-Sampling)\u201d by addressing the problem in two stages, which leads to reduced resource usage (e.g., energy, radio bandwidth). First, e-Sampling provides the embedded algorithm to adaptive sampling that automatically switches between high- and low-frequency intervals to reduce the resource usage, while minimizing false negative detections. Second, by analyzing the frequency content, e-Sampling presents an event identification algorithm suitable for decentralized computing in resource-constrained networks. In the absence of an event, the \u201cuninteresting\u201d data is not transmitted to the sink. Thus, the energy cost is further reduced. e-Sampling can be useful in a broad range of applications. We apply e-Sampling to Structural Health Monitoring (SHM) and Fire Event Monitoring (FEM), which are typical applications of high-frequency events. Evaluation via both simulations and experiments validates the advantages of e-Sampling in low-cost event monitoring, and in effectively expanding the capacity of WSNs for high data rate applications.<\/jats:p>","DOI":"10.1145\/2994150","type":"journal-article","created":{"date-parts":[[2017,3,27]],"date-time":"2017-03-27T08:25:10Z","timestamp":1490603110000},"page":"1-29","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":79,"title":["e-Sampling"],"prefix":"10.1145","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9513-9990","authenticated-orcid":false,"given":"Md Zakirul Alam","family":"Bhuiyan","sequence":"first","affiliation":[{"name":"Guangzhou University and Fordham University, New York, NY"}]},{"given":"Jie","family":"Wu","sequence":"additional","affiliation":[{"name":"Temple University, Philadelphia, PA"}]},{"given":"Guojun","family":"Wang","sequence":"additional","affiliation":[{"name":"Guangzhou University, Guangzhou, China"}]},{"given":"Tian","family":"Wang","sequence":"additional","affiliation":[{"name":"Huaqiao University, Xiamen, China"}]},{"given":"Mohammad Mehedi","family":"Hassan","sequence":"additional","affiliation":[{"name":"King Saud University, Saudi Arabia"}]}],"member":"320","published-online":{"date-parts":[[2017,3,27]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"2-Bit Sampling Analog to Digital Converter Conserves Power","author":"Application Notes Maxim Corporation","year":"2004","unstructured":"Application Notes Maxim Corporation, 2-Bit Sampling Analog to Digital Converter Conserves Power 2004. 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