Poster Abstract: Low-Cost, Perspective Invariant and Personalized Thermal Comfort Estimation

被引：0

作者：

Wei, Peter ^{[1
]}

Liu, Yanchen ^{[1
]}

Jiang, Xiaofan ^{[1
]}

机构：

[1] Columbia Univ, New York, NY 10027 USA

来源：

IPSN'21: PROCEEDINGS OF THE 20TH ACM/IEEE CONFERENCE ON INFORMATION PROCESSING IN SENSOR NETWORKS | 2021年

基金：

美国国家科学基金会;

关键词：

D O I：

10.1145/3412382.3458781

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this poster abstract, we present a thermal comfort estimation system using low-cost thermal camera based sensor nodes. This system extracts perspective invariant, non-intrusive thermal measurements, is easily deployable and low-cost, and can incorporate individual thermal feedback for more personalized thermal comfort estimates. In comparison with baseline methods, our system is able to improve thermal comfort estimates on the ASHRAE 7-point thermal sensation scale by up to 64% over baseline methods.

引用

页码：396 / 397

页数：2

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