Intelligent buildings monitoring and management system based on computer technology
China’s relentless urbanization has significantly propelled the construction sector forward, simultaneously unlocking vast potential and posing complex challenges for the development of intelligent building systems. This paper introduces an architecture for an intelligent building integration platform that hinges on the connectivity between server and client. The server sends the collected data to the system, while the client displays, monitors, and manages the data. The whole intelligent building management system includes business system management module, authorization management module, client module, and data linkage module. The client module visually displays the data in the building through charts and other means. The data linkage module uses sensors, devices, and communication technologies to collect various environmental parameters in the building and equipment operating status and other information, and sends the information to the data center or the cloud for subsequent processing. In the monitoring of energy consumption information, the electricity consumption of Building C was 181 KWH; the water consumption was 98 tons, and the gas consumption was 75 cubic meters. This research significantly advances the field of intelligent building management by demonstrating how computer technology can be effectively utilized to monitor building energy consumption. The findings of this paper provide crucial theoretical and technical support for the ongoing development and refinement of intelligent building systems. This not only enhances our understanding of smart infrastructure but also opens up new avenues for innovation in building management and energy efficiency.
Authors
- Jia Li (ORCID: https://orcid.org/0000-0003-2900-9108)
Institutions
- Anyang Normal University (CN)
Publication Details
- Journal
- Journal of Computational Methods in Sciences and Engineering
- Published
- 2025-03-27
- DOI
- https://doi.org/10.1177/14727978251322043
- Primary Topic
- Wireless Sensor Networks and IoT
- Type
- article
- Field-Weighted Citation Impact
- 0.00