IoT-based data collection system for central air conditioning

Guofu Luo; Jiaqi Wang; Haoqi Wang; Hao Li; Tianxing Sun; Mi'ao Zhuang; Honglei Zi; Fuliang Che; Gen Liu; Rongjie Huang

doi:10.1117/12.3011059

20 October 2023 IoT-based data collection system for central air conditioning

Guofu Luo, Jiaqi Wang, Haoqi Wang, Hao Li, Tianxing Sun, Mi'ao Zhuang, Honglei Zi, Fuliang Che, Gen Liu, Rongjie Huang

Proceedings Volume 12814, Third International Conference on Green Communication, Network, and Internet of Things (CNIoT 2023); 128141O (2023) https://doi.org/10.1117/12.3011059
Event: Third International Conference on Green Communication, Network, and Internet of Things (CNIoT 2023), 2023, Chongqing, China

Abstract

Effective data collection is a prerequisite for energy saving, emission reduction and other sustainable operation of central air conditioning. However, current central air-conditioning data collection systems are costly to develop and difficult to integrate. To promote energy saving and emission reduction, this paper proposes an IoT-based data collection system for central air conditioning. Based on IoT and wireless sensor technology, this data acquisition system mainly consists of sub-systems such as host data acquisition sub-system, cooling tower data acquisition sub-system and pipeline pressure data acquisition sub-system to achieve multi-point acquisition of the central air-conditioning system. It also uses Kalman filtering technology to reject abnormal sensor data and optimise the data; it uses a combination of deep sleep and multiple power supplies to extend the service life of the cooling tower data acquisition subsystem; and it uses deep learning in the pipeline pressure data acquisition subsystem to greatly improve the accuracy and efficiency of meter reading. After experiments, the acquisition system can monitor and analyse real-time operational data of central air-conditioners for intelligent regulation and predictive maintenance. Finally, the proposed system was experimentally demonstrated to be feasible in a postal building in Zhengzhou.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Guofu Luo, Jiaqi Wang, Haoqi Wang, Hao Li, Tianxing Sun, Mi'ao Zhuang, Honglei Zi, Fuliang Che, Gen Liu, and Rongjie Huang "IoT-based data collection system for central air conditioning", Proc. SPIE 12814, Third International Conference on Green Communication, Network, and Internet of Things (CNIoT 2023), 128141O (20 October 2023); https://doi.org/10.1117/12.3011059

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KEYWORDS

Signal filtering

Data acquisition

Sensors

Electronic filtering

Tunable filters

Education and training

Data processing

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