Parallel Bayesian Belief Network in Building Energy Conservation

Golrokh Mirzaei, Nima Mansouri, M. Jamali
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Abstract

It is important to control processes efficiently in commercial buildings for Energy conservation. The key element for saving energy is to obtain accurate information about the occupancy, and if there is no one in the building then services such as Heating, Ventilation, and Air-conditioning (HVAC), lighting, etc. can be turned off. Also, it is very critical that the building services respond in real-time, as it may affect the functionality of employees/equipment in the building. This paper presents a fast occupancy detection technique using parallel Bayesian Belief Network. This technique can be used as a fast, reliable, and automated occupancy detection technique in commercial buildings.
并行贝叶斯信念网络在建筑节能中的应用
在商业建筑中,有效地控制过程对节能具有重要意义。节约能源的关键因素是获得准确的占用信息,如果大楼里没有人,那么可以关闭供暖、通风、空调(HVAC)、照明等服务。此外,建筑服务的实时响应非常重要,因为它可能会影响建筑物中员工/设备的功能。提出了一种基于并行贝叶斯信念网络的快速占用检测技术。该技术可作为一种快速、可靠、自动化的商业楼宇占用检测技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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