很高兴再次见到你:移动设备上的捕获和重新捕获方法,以估计占用情况

J. Park, E. Mbata, Z. Nagy
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引用次数: 7

摘要

基于占用的控制可以节省20-50%的能源使用。因此,开发了各种数据采集技术来收集占用信息。最近的发展重点是利用具有网络功能的住户移动设备的普遍性,即WiFi和蓝牙(BT)来推断建筑物的占用情况。这种方法的挑战在于,仍有未知数量的人在其移动设备上禁用了网络功能。本文提出了一种基于BT信号的占用估计器,该估计器采用捕获和重捕获(CRC)技术。在生态学中,CRC是估计动物种群规模的常用方法。我们研究了将CRC与BT设备结合使用以推断建筑物占用密度概况的可行性。我们的模拟结果表明,CRC估计器在某些情况下(即BT比率> 0.3)计算出准确的占用情况。根据结果,我们提出了实验研究的建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Good to see you again: Capture and recapture method on mobile devices to estimate occupancy profiles
Occupancy based controls can save 20-50% of the energy use in buildings. Thus, various data acquisition techniques to gather occupancy information have been developed. Recent developments focus on utilizing the pervasiveness of occupants' mobile devices with enabled networking capability, i.e., WiFi and Bluetooth (BT) to infer building occupancy. The challenge with this approach is that there is still an unknown number of people with deactivated networking functions on their mobile devices. In this paper, we propose an occupancy estimator based on BT signals, that uses the capture and recapture (CRC) technique. In ecology, CRC is an established method for estimating an animal population size. We examine the viability of using CRC in conjunction with BT devices to infer building occupancy density profiles. Our simulation results show that the CRC estimator calculates accurate occupancy profiles under certain circumstances (i.e., BT ratio > 0.3). With the results, we propose recommendations for experimental studies.
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