Poster Abstract: Intelligent Heating Monitoring Method Based on Infrared Image Segmentation and Target Detection

Dongbo Li; Tong Yu; Yu Yang; Yuze Zhao; Zihan Chen; Jie Liu

doi:10.1145/3563357.3567755

Poster Abstract: Intelligent Heating Monitoring Method Based on Infrared Image Segmentation and Target Detection

Dongbo Li
, Tong Yu
, Yu Yang
, Yuze Zhao
, Zihan Chen
, Jie Liu

Faculty of Computing, Harbin Institute of Technology
Harbin Institute of Technology Shenzhen

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

With the development of smart cities, the information of the heating system of buildings can be highly integrated and shared. However, the current intelligent heating system adopts the scheme of installing temperature sensors in users' rooms to collect data, which has problems such as low acceptance by users, high equipment cost, difficult management, and poor robustness. To solve these problems, this paper proposes a new type of intelligent heating system: an intelligent heating monitoring method based on infrared image segmentation and target detection. An infrared camera-equipped unmanned aerial vehicle is used to acquire thermal images of buildings and create datasets. SegNet semantic segmentation model is used to semantically segment the infrared image and segment windows that can infer the indoor temperature. A portion of the indoor temperature is collected using a temperature sensor to analyze the temperature acquisition points that can represent the indoor temperature. In this way, we can achieve the purpose of inferring the indoor temperature based on the infrared images acquired through the outdoors.

Original language	English
Title of host publication	BuildSys 2022 - Proceedings of the 2022 9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation
Publisher	Association for Computing Machinery, Inc
Pages	301-302
Number of pages	2
ISBN (Electronic)	9781450398909
DOIs	https://doi.org/10.1145/3563357.3567755
State	Published - 9 Nov 2022
Externally published	Yes
Event	9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation, BuildSys 2022 - Boston, United States Duration: 9 Nov 2022 → 10 Nov 2022

Publication series

Name	BuildSys 2022 - Proceedings of the 2022 9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation

Conference

Conference	9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation, BuildSys 2022
Country/Territory	United States
City	Boston
Period	9/11/22 → 10/11/22

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy
SDG 11 Sustainable Cities and Communities

Keywords

infrared image
intelligent heating
internet of things
semantic segmentation
smart building

Access to Document

10.1145/3563357.3567755

Cite this

Li, D., Yu, T., Yang, Y., Zhao, Y., Chen, Z., & Liu, J. (2022). Poster Abstract: Intelligent Heating Monitoring Method Based on Infrared Image Segmentation and Target Detection. In BuildSys 2022 - Proceedings of the 2022 9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation (pp. 301-302). (BuildSys 2022 - Proceedings of the 2022 9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation). Association for Computing Machinery, Inc. https://doi.org/10.1145/3563357.3567755

Li, Dongbo ; Yu, Tong ; Yang, Yu et al. / Poster Abstract : Intelligent Heating Monitoring Method Based on Infrared Image Segmentation and Target Detection. BuildSys 2022 - Proceedings of the 2022 9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation. Association for Computing Machinery, Inc, 2022. pp. 301-302 (BuildSys 2022 - Proceedings of the 2022 9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation).

@inproceedings{9a0bc64a7a4b4f14ab61939488c088bd,

title = "Poster Abstract: Intelligent Heating Monitoring Method Based on Infrared Image Segmentation and Target Detection",

abstract = "With the development of smart cities, the information of the heating system of buildings can be highly integrated and shared. However, the current intelligent heating system adopts the scheme of installing temperature sensors in users' rooms to collect data, which has problems such as low acceptance by users, high equipment cost, difficult management, and poor robustness. To solve these problems, this paper proposes a new type of intelligent heating system: an intelligent heating monitoring method based on infrared image segmentation and target detection. An infrared camera-equipped unmanned aerial vehicle is used to acquire thermal images of buildings and create datasets. SegNet semantic segmentation model is used to semantically segment the infrared image and segment windows that can infer the indoor temperature. A portion of the indoor temperature is collected using a temperature sensor to analyze the temperature acquisition points that can represent the indoor temperature. In this way, we can achieve the purpose of inferring the indoor temperature based on the infrared images acquired through the outdoors.",

keywords = "infrared image, intelligent heating, internet of things, semantic segmentation, smart building",

author = "Dongbo Li and Tong Yu and Yu Yang and Yuze Zhao and Zihan Chen and Jie Liu",

note = "Publisher Copyright: {\textcopyright} 2022 ACM.; 9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation, BuildSys 2022 ; Conference date: 09-11-2022 Through 10-11-2022",

year = "2022",

month = nov,

day = "9",

doi = "10.1145/3563357.3567755",

language = "英语",

series = "BuildSys 2022 - Proceedings of the 2022 9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation",

publisher = "Association for Computing Machinery, Inc",

pages = "301--302",

booktitle = "BuildSys 2022 - Proceedings of the 2022 9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation",

}

Li, D, Yu, T, Yang, Y, Zhao, Y, Chen, Z & Liu, J 2022, Poster Abstract: Intelligent Heating Monitoring Method Based on Infrared Image Segmentation and Target Detection. in BuildSys 2022 - Proceedings of the 2022 9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation. BuildSys 2022 - Proceedings of the 2022 9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation, Association for Computing Machinery, Inc, pp. 301-302, 9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation, BuildSys 2022, Boston, United States, 9/11/22. https://doi.org/10.1145/3563357.3567755

Poster Abstract: Intelligent Heating Monitoring Method Based on Infrared Image Segmentation and Target Detection. / Li, Dongbo; Yu, Tong; Yang, Yu et al.
BuildSys 2022 - Proceedings of the 2022 9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation. Association for Computing Machinery, Inc, 2022. p. 301-302 (BuildSys 2022 - Proceedings of the 2022 9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Poster Abstract

T2 - 9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation, BuildSys 2022

AU - Li, Dongbo

AU - Yu, Tong

AU - Yang, Yu

AU - Zhao, Yuze

AU - Chen, Zihan

AU - Liu, Jie

PY - 2022/11/9

Y1 - 2022/11/9

N2 - With the development of smart cities, the information of the heating system of buildings can be highly integrated and shared. However, the current intelligent heating system adopts the scheme of installing temperature sensors in users' rooms to collect data, which has problems such as low acceptance by users, high equipment cost, difficult management, and poor robustness. To solve these problems, this paper proposes a new type of intelligent heating system: an intelligent heating monitoring method based on infrared image segmentation and target detection. An infrared camera-equipped unmanned aerial vehicle is used to acquire thermal images of buildings and create datasets. SegNet semantic segmentation model is used to semantically segment the infrared image and segment windows that can infer the indoor temperature. A portion of the indoor temperature is collected using a temperature sensor to analyze the temperature acquisition points that can represent the indoor temperature. In this way, we can achieve the purpose of inferring the indoor temperature based on the infrared images acquired through the outdoors.

AB - With the development of smart cities, the information of the heating system of buildings can be highly integrated and shared. However, the current intelligent heating system adopts the scheme of installing temperature sensors in users' rooms to collect data, which has problems such as low acceptance by users, high equipment cost, difficult management, and poor robustness. To solve these problems, this paper proposes a new type of intelligent heating system: an intelligent heating monitoring method based on infrared image segmentation and target detection. An infrared camera-equipped unmanned aerial vehicle is used to acquire thermal images of buildings and create datasets. SegNet semantic segmentation model is used to semantically segment the infrared image and segment windows that can infer the indoor temperature. A portion of the indoor temperature is collected using a temperature sensor to analyze the temperature acquisition points that can represent the indoor temperature. In this way, we can achieve the purpose of inferring the indoor temperature based on the infrared images acquired through the outdoors.

KW - infrared image

KW - intelligent heating

KW - internet of things

KW - semantic segmentation

KW - smart building

UR - https://www.scopus.com/pages/publications/85144616896

U2 - 10.1145/3563357.3567755

DO - 10.1145/3563357.3567755

M3 - 会议稿件

AN - SCOPUS:85144616896

T3 - BuildSys 2022 - Proceedings of the 2022 9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation

SP - 301

EP - 302

BT - BuildSys 2022 - Proceedings of the 2022 9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation

PB - Association for Computing Machinery, Inc

Y2 - 9 November 2022 through 10 November 2022

ER -

Li D, Yu T, Yang Y, Zhao Y, Chen Z, Liu J. Poster Abstract: Intelligent Heating Monitoring Method Based on Infrared Image Segmentation and Target Detection. In BuildSys 2022 - Proceedings of the 2022 9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation. Association for Computing Machinery, Inc. 2022. p. 301-302. (BuildSys 2022 - Proceedings of the 2022 9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation). doi: 10.1145/3563357.3567755

Poster Abstract: Intelligent Heating Monitoring Method Based on Infrared Image Segmentation and Target Detection

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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