{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,31]],"date-time":"2025-12-31T18:22:29Z","timestamp":1767205349510,"version":"build-2238731810"},"reference-count":37,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2009,7,17]],"date-time":"2009-07-17T00:00:00Z","timestamp":1247788800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Positioning and tracking technologies can detect the location and the movement of mobile nodes (MNs), such as cellular phone, vehicular and mobile sensor, to predict potential handoffs. However, most motion detection mechanisms require additional hardware (e.g., GPS and directed antenna), costs (e.g., power consumption and monetary cost) and supply systems (e.g., network fingerprint server). This paper proposes a Momentum of Received Signal Strength (MRSS) based motion detection method and its application on handoff. MRSS uses the exponentially weighted moving average filter with multiple moving average window size to analyze the received radio signal. With MRSS, an MN can predict its motion state and make a handoff trigger at the right time without any assistance from positioning systems. Moreover, a novel motion state dependent MRSS scheme called Dynamic MRSS (DMRSS) algorithm is proposed to adjust the motion detection sensitivity. In our simulation, the MRSSand DMRSS-based handoff algorithms can reduce the number of unnecessary handoffs up to 44% and save battery power up to 75%.<\/jats:p>","DOI":"10.3390\/s90705715","type":"journal-article","created":{"date-parts":[[2011,9,27]],"date-time":"2011-09-27T20:09:10Z","timestamp":1317154150000},"page":"5715-5739","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Adaptive Momentum-Based Motion Detection Approach and Its Application on Handoff in Wireless Networks"],"prefix":"10.3390","volume":"9","author":[{"given":"Tein-Yaw","family":"Chung","sequence":"first","affiliation":[{"name":"Department of Computer Science & Engineering, Yuan Ze University, No. 135 Yuan-Tung Rd., Chung-Li, Taoyuan, 32003, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yung-Mu","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Computer Science & Engineering, Yuan Ze University, No. 135 Yuan-Tung Rd., Chung-Li, Taoyuan, 32003, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chih-Hung","family":"Hsu","sequence":"additional","affiliation":[{"name":"Department of Computer Science & Engineering, Yuan Ze University, No. 135 Yuan-Tung Rd., Chung-Li, Taoyuan, 32003, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2009,7,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"488","DOI":"10.3390\/s5110488","article-title":"Robust Multivariable Estimation of the Relevant Information Coming from a Wheel Speed Sensor and an Accelerometer Embedded in a Car under Performance Tests","volume":"5","author":"Hernandez","year":"2005","journal-title":"Sensors"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"84","DOI":"10.3390\/s7010084","article-title":"A Survey on Optimal Signal Processing Techniques Applied to Improve the Performance of Mechanical Sensors in Automotive Applications","volume":"7","author":"Hernandez","year":"2007","journal-title":"Sensors"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Wang, Y.-F., and Liu, L.-L. 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