Fall Detection by Using K-Nearest Neighbor Algorithm on WSN Data

Erdogan, Senol ZaferBilgin, Turgay TugayCho, Juphil2024-07-122024-07-122010978-1-4244-8865-02166-006910.1109/GLOCOMW.2010.57003062-s2.0-79951880259https://dx.doi.org/10.1109/GLOCOMW.2010.5700306https://hdl.handle.net/20.500.12415/8964Globecom Workshops -- DEC 05-10, 2010 -- Miami, FLFalls are serious problem especially for elderly people. Day by day the elderly people are living alone and the children of these people want to get information in dangerous situations. With the alarm systems, someone in difficulty can be detected and emergency aid can be sent. We propose a system to detect falls by using a data mining approach on WSN data. The proposed system evaluated using data stream collected from sensor device and fall detection accuracy and precision are calculated. Our solution demonstrated promising results on WSN data stream.eninfo:eu-repo/semantics/closedAccessWireless sensor networksfall detectiondata miningKNN algorithmFall Detection by Using K-Nearest Neighbor Algorithm on WSN DataConference Object2058N/A2054WOS:000291611300389N/A