Department of Telematics and Electronics for Transports, Transports Faculty, University Politehnica of Bucharest, 060042 Bucharest, Romania.
Sensors (Basel). 2022 Nov 21;22(22):9025. doi: 10.3390/s22229025.
(1) Background: public transport demand dynamics represents important information for fleet managers and is also a key factor in making public transport attractive to reduce the environmental footprint of urban traffic. This research presents some experimental results on the assessment of low-energy communication technologies, such as Wi-Fi and Bluetooth, as support for people density and/or movement tracking sensing technologies. (2) Methods: the research is based on field measurements to determine the percentage of discoverable devices carried by people, in relation to the total number of physical persons in interest, different scenarios of mobile devices usage and evaluation of influences on radio signals' propagation, RSSI / RX read values, and efficiency of indoor localization, or in similar GPS-denied environments. Different situations are investigated, especially public transport-related ones, such as subway stations, indoors of commuting hubs, railway stations and trains. (3) Results: diagrams and experiments are presented, and models of signal behavior are also proposed. (4) Conclusions: recommendations on the efficiency of these non-conventional traveler and passenger flow tracking solutions and models are presented at the end of the paper.
(1) 背景:公共交通需求动态是车队管理人员的重要信息,也是提高公共交通吸引力以减少城市交通环境足迹的关键因素。本研究提出了一些关于低能耗通信技术(如 Wi-Fi 和蓝牙)评估的实验结果,这些技术可用于支持人员密度和/或运动跟踪感应技术。(2) 方法:该研究基于现场测量,以确定人们携带的可发现设备的百分比,与感兴趣的总人数有关,包括不同的移动设备使用场景以及对无线电信号传播、RSSI/RX 读取值的影响的评估,以及室内定位或类似 GPS 受限制环境中的效率。研究了不同的情况,特别是与公共交通相关的情况,如地铁站、通勤枢纽室内、火车站和火车上。(3) 结果:呈现了图表和实验,还提出了信号行为模型。(4) 结论:本文最后提出了对这些非传统的旅客和乘客流量跟踪解决方案和模型的效率的建议。