IoT-based occupancy detection system in indoor residential environments
We propose an Internet of Things (IoT)-based occupancy detection system using change patterns of dust concentrations such as particulate matter. Previous research studies have used other features such as visual, chemical, or acoustic data. In this paper, the point extraction algorithm is proposed to...
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| Veröffentlicht in: | Building and environment 2018-03, Vol.132, p.181-204 |
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| container_title | Building and environment |
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| creator | Jeon, Yunwan Cho, Chanho Seo, Jongwoo Kwon, Kyunglag Park, Hansaem Oh, Seungkeun Chung, In-Jeong |
| description | We propose an Internet of Things (IoT)-based occupancy detection system using change patterns of dust concentrations such as particulate matter. Previous research studies have used other features such as visual, chemical, or acoustic data. In this paper, the point extraction algorithm is proposed to construct triangular shapes, and their properties are used to detect occupancy in an indoor environment. For the verification of the proposed method, an IoT-based system is implemented for the occupancy detection in real residential environments. Finally, we analyze the experimental results, and compare them with those of other conventional approaches from a qualitative point of view. |
| doi_str_mv | 10.1016/j.buildenv.2018.01.043 |
| format | Article |
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Previous research studies have used other features such as visual, chemical, or acoustic data. In this paper, the point extraction algorithm is proposed to construct triangular shapes, and their properties are used to detect occupancy in an indoor environment. For the verification of the proposed method, an IoT-based system is implemented for the occupancy detection in real residential environments. Finally, we analyze the experimental results, and compare them with those of other conventional approaches from a qualitative point of view.</description><identifier>ISSN: 0360-1323</identifier><identifier>EISSN: 1873-684X</identifier><identifier>DOI: 10.1016/j.buildenv.2018.01.043</identifier><language>eng</language><publisher>Oxford: Elsevier Ltd</publisher><subject>Airborne particulates ; Change detection ; Data processing ; Indoor air quality ; Indoor environments ; Indoor residential environment ; Information systems ; Intelligent information systems ; Internet of Things ; Occupancy detection ; Occupancy rates ; Organic chemistry ; Particulate emissions ; Particulate matter ; Pattern analysis ; Sensor data ; Shape recognition</subject><ispartof>Building and environment, 2018-03, Vol.132, p.181-204</ispartof><rights>2018 Elsevier Ltd</rights><rights>Copyright Elsevier BV Mar 15, 2018</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c379t-b69d1b054d9f0419e6e7ef7ed319a466fd63dcd26d9c858c904e27a39982a7453</citedby><cites>FETCH-LOGICAL-c379t-b69d1b054d9f0419e6e7ef7ed319a466fd63dcd26d9c858c904e27a39982a7453</cites><orcidid>0000-0002-5020-8921</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0360132318300611$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65306</link.rule.ids></links><search><creatorcontrib>Jeon, Yunwan</creatorcontrib><creatorcontrib>Cho, Chanho</creatorcontrib><creatorcontrib>Seo, Jongwoo</creatorcontrib><creatorcontrib>Kwon, Kyunglag</creatorcontrib><creatorcontrib>Park, Hansaem</creatorcontrib><creatorcontrib>Oh, Seungkeun</creatorcontrib><creatorcontrib>Chung, In-Jeong</creatorcontrib><title>IoT-based occupancy detection system in indoor residential environments</title><title>Building and environment</title><description>We propose an Internet of Things (IoT)-based occupancy detection system using change patterns of dust concentrations such as particulate matter. 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| identifier | ISSN: 0360-1323 |
| ispartof | Building and environment, 2018-03, Vol.132, p.181-204 |
| issn | 0360-1323 1873-684X |
| language | eng |
| recordid | cdi_proquest_journals_2057969991 |
| source | Elsevier ScienceDirect Journals |
| subjects | Airborne particulates Change detection Data processing Indoor air quality Indoor environments Indoor residential environment Information systems Intelligent information systems Internet of Things Occupancy detection Occupancy rates Organic chemistry Particulate emissions Particulate matter Pattern analysis Sensor data Shape recognition |
| title | IoT-based occupancy detection system in indoor residential environments |
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