能源管理
能源消耗
可再生能源
能源管理系统
楼宇自动化
重新使用
能源工程
高效能源利用
楼宇管理系统
智能电网
管理制度
建筑工程
过程(计算)
智慧城市
环境经济学
计算机科学
能量(信号处理)
工程类
计算机安全
运营管理
人工智能
物联网
废物管理
控制(管理)
电气工程
物理
数学
经济
操作系统
统计
热力学
作者
Rajalakshmi Selvaraj,Venu Madhav Kuthadi,S. Baskar
标识
DOI:10.1016/j.seta.2023.103090
摘要
In the present scenario, the fastest-growing environmental concerns are energy management and monitoring. In-efficient energy recycling, energy consumption, energy utilization, and drain characteristic are smart building energy management challenges. Hence to examine the connection between smart city management policies and energy management, this research proposed an Artificial Intelligence Technique for Monitoring Systems in Smart Buildings (AIMS-SB) to manage energy consumption and produce and recycle energy required for a smart building. AIMS-SB helps to predict energy analysis, renewable energy production, and recycling evaluation based on prediction model strategies. AIMS-SB developed eco-design monitoring systems for smart buildings to optimize energy consumption, utilization, and drain characteristics. These efficient implementation strategies and methods for harnessing renewable energy help to improve the safety process, recycling, and reuse of our energy resources for smart building energy management. AIMS-SB provides viable solutions to the growing number of challenges associated with smart city energy management. Therefore, the system's findings demonstrate increased accuracy and efficiency compared to conventional methods.
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