Bayesian Belief Network Based Occupancy Assessment Framework

被引：0
作者：
Jamali, Mohsin M. [1 ]
Mirzaei, Golrokh [2 ]
机构：
[1] Univ Texas Permian Basin, Dept Elect Engn, Odessa, TX 79762 USA
[2] Ohio State Univ, Dept Comp Sci & Engn, Marion, OH USA
来源：
2018 CONFERENCE RECORD OF 52ND ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS, AND COMPUTERS | 2018年
关键词：
BUILDINGS; SENSORS; SYSTEM;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Heating, Ventilation, Air Conditions (HVAC) consumes up to 59% of energy in residential, commercial, warehouse and large laboratories. Lighting would be the second highest consumer of electricity. If buildings are not occupied then some of the HVAC units and lighting can be turned off resulting in enormous savings in the energy cost. This work creates a framework for situation awareness using Bayesian Based Network with cooperative and non-cooperative sensors. It provides occupancy information useful for turning on/off HVAC system or inform authorities of any emergency.
引用
收藏
页码：792 / 796
页数：5
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