IoT-based occupancy detection system in indoor residential environments

被引：44

作者：

Jeon, Yunwan ^{[1
]}

Cho, Chanho ^{[1
]}

Seo, Jongwoo ^{[1
]}

Kwon, Kyunglag ^{[1
]}

Park, Hansaem ^{[2
]}

Oh, Seungkeun ^{[3
]}

Chung, In-Jeong ^{[1
]}

机构：

[1] Korea Univ, Grad Sch, Dept Comp & Informat Sci, Sejong City, South Korea

[2] Korea Adv Inst Sci & Technol, Dept Civil & Environm Engn, Daejeon, South Korea

[3] Hyundai Steel, IT Planning Team, Incheon, South Korea

来源：

BUILDING AND ENVIRONMENT | 2018年 / 132卷

基金：

新加坡国家研究基金会;

关键词：

Occupancy detection; Pattern analysis; Particulate matter; Indoor residential environment; Sensor data; Data processing; Intelligent information systems; OFFICE BUILDINGS; SENSOR; INTERNET; VISION; THINGS; ROOM;

D O I：

10.1016/j.buildenv.2018.01.043

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

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.

引用

页码：181 / 204

页数：24

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