{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,25]],"date-time":"2025-12-25T12:38:27Z","timestamp":1766666307329},"reference-count":21,"publisher":"SAGE Publications","issue":"11","license":[{"start":{"date-parts":[[2015,11,1]],"date-time":"2015-11-01T00:00:00Z","timestamp":1446336000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["International Journal of Distributed Sensor Networks"],"published-print":{"date-parts":[[2015,11,1]]},"abstract":"<jats:p> In smart home, location estimation based on PIR sensors is very popular. Existing methods by various sensors technologies and intelligent algorithms are used to achieve a high accuracy. In fact, how to deploy the PIR sensor is directly related to the accuracy. In this paper, we present an approach to deploying the PIR sensor based on the accessible priority by genetic algorithm. This paper presents a genetic algorithm that searches for an optimal or near optimal solution to the PIR sensor deployment for smart home. The fitness function of GA is based on the accessible priority of indoor areas. The accessible priority value of different area is set according to the indoor environment and daily accessible habits. The performance of the genetic algorithm was evaluated using several metrics, and the simulation results demonstrated that the proposed algorithm can optimize the network coverage in terms of accessible frequency. <\/jats:p>","DOI":"10.1155\/2015\/146270","type":"journal-article","created":{"date-parts":[[2015,11,26]],"date-time":"2015-11-26T21:00:47Z","timestamp":1448571647000},"page":"146270","update-policy":"http:\/\/dx.doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":2,"title":["PIR Sensors Deployment with the Accessible Priority in Smart Home Using Genetic Algorithm"],"prefix":"10.1177","volume":"11","author":[{"given":"Dan","family":"Yang","sequence":"first","affiliation":[{"name":"School of Information Science and Engineering, Northeastern University, Shenyang 110819, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kaiyou","family":"Rao","sequence":"additional","affiliation":[{"name":"School of Physics, Northeast 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