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Design of Building Environment Detection System for Architectures Based on Internet of Things.

Authors :
Zhang, Dongfang
Ji, Hui
Li, Zhennan
Ge, Hui
Source :
Computational Intelligence & Neuroscience. 3/28/2022, p1-11. 11p.
Publication Year :
2022

Abstract

In the process of urban building design, a new integrated system for monitoring the environment is developed and designed by using embedded development technology and sensor technology. The system uses a wireless sensor network environment monitoring system IoT platform with embedded internal processors. Analyze and design the system as a whole, including the construction of the basic platform of the system, the design of the internal plates and circuits of the system, the monitoring design of the input node, and the monthly design of the output interface calculation. Finally, a physical model is built, and data measurement and analysis are carried out under different conditions, and the evaluation and advantage analysis of the system's operating status are given. The system can carry out all-round, multilevel, and three-dimensional real-time monitoring of the construction site environment, including dust, PM2.5, temperature, humidity, wind speed, carbon dioxide, and other indicators in the construction site environment. In addition, the system can upload various monitoring data to the detection system through the internal network. The system has the functions of monitoring, alarming, recording, querying, and counting of the target monitoring station and can also be linked with the environmental control device. The construction site staff can conduct real-time supervision through the mobile terminal and computer terminal management platform. In addition, it can also meet the role of real-time remote monitoring and online guidance and regulation. It has reference value for the safety and management of the actual operation process of the project. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
16875265
Database :
Academic Search Index
Journal :
Computational Intelligence & Neuroscience
Publication Type :
Academic Journal
Accession number :
155972659
Full Text :
https://doi.org/10.1155/2022/5438305