Abstract
As energy consumption for building engineering systems is a major part of the total energy spent, it is necessary to reduce it. This leads to the need for the development of new solutions for the control of heating, ventilation, and conditioning (HVAC) systems that are responsive to humans and their demands. In this review article, the existing research and technology advancements of the modern technologies of computer vision and neural networks for application in HVAC control systems are studied. Objectives such as human detection and location, human activity monitoring, skin temperature detection, and clothing level detection systems are important for the operation of precise, high-tech HVAC systems. This article tries to compile the latest achievements and principal solutions on how this information is acquired. Moreover, it how parameters such as indoor air quality (IAQ), variable air volume ventilation, computer vision, metabolic rate, and human clothing isolation can affect final energy consumption is studied. The research studies discussed in this review article have been tested in real application scenarios and prove the benefits of using a particular technology in ventilation systems. As a result, the modernized control systems have shown advantages over the currently applied typical non-automated systems by providing higher IAQ and reducing unnecessary energy consumption.
Funder
European Regional Development Fund
Subject
Energy (miscellaneous),Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment,Electrical and Electronic Engineering,Control and Optimization,Engineering (miscellaneous),Building and Construction
Cited by
6 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献