Understanding occupancy pattern and improving building energy efficiency through Wi-Fi based indoor positioning
Understanding occupancy pattern and improving building energy efficiency through Wi-Fi based indoor positioning
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DOI：
10.1016/j.buildenv.2016.12.015
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发表时间：
2017-03-01
影响因子：
7.4
通讯作者：
Shao, L.
中科院分区：
文献类型：
--
作者：
Wang, Y.;Shao, L.
对占用模式（包括空间分布和时间变化）进行详细的可视化和数据分析，对于提供节能和高效的建筑非常重要。在一所大学的图书馆大楼进行了一项实验研究，包括24小时监测超过30整天。已对占用情况进行监测和分析。这项监测研究的核心是基于Wi-Fi的室内定位系统，该系统基于测量的Wi-Fi设备的数量和位置以及数据挖掘方法。与传统的占用和能源研究不同，与室内位置和占用者数量相关的更详细的信息提供了对建筑用户行为的更好理解。使用模式对能源（例如照明和其他建筑服务）效率的影响是评估的，并在需要时利用来自照明传感器的数据进行辅助。它被发现占用模式随时间变化显着。同时，通过数据关联规则挖掘的方法识别了能源浪费模式。若能消除已识别的能源浪费，总能源消耗可减少26.1%。室内定位信息还对优化空间使用、开放时间以及员工部署具有影响。这项工作可以扩展到更多不同功能的房间、其他季节和其他类型的非住宅建筑物，以便更全面地了解建筑物使用者的行为和能源效益。(C)2016爱思唯尔有限公司版权所有
Detailed visualisation and data analysis of occupancy patterns including spatial distribution and temporal variations are of great importance to delivering energy efficient and productive buildings. An experimental study comprising 24-h monitoring over 30 full days was conducted in a university library building. Occupancy profiles have been monitored and analysis has been carried out. Central to this monitoring study is the Wi-Fi based indoor positioning system based on the measured Wi-Fi devices' number and locations and data mining methods. Distinct from traditional occupancy and energy studies, more detailed information related to the indoor positions and number of occupants has offered a better understanding of building user behaviour. The implication of the occupancy patterns for energy (e.g. lighting and other building services) efficiency is, assessed, assisted with data from lighting sensors where needed. It is found occupancy patterns change dramatically with time. Also, the energy waste patterns have been identified through the method of data association rule mining. If the identified energy waste is removed, the total energy consumption can be reduced by 26.1%. The indoor positioning information also has implications for optimizing space use, opening hours as well as staff deployment. The work could be extended to more rooms with diverse functions, other seasons and other types of non domestic buildings for a more comprehensive understanding of building user behaviour and energy efficiency. (C) 2016 Elsevier Ltd. All rights reserved.