Extensions to Bluetooth/WiFi for Vehicular and Pedestrian Traffic Monitoring

先前的Engage赠款为MORR提供了探索推断车辆交通技术的机会 通过监测与个人设备（如智能手机、消费者和车辆）相关的信号， 附件.研究了市售的系统，如Libelium的Meshtron，以及 定制平台（内部）开发。通过这项初步研究，发现了不足和机会。 暴露于扩展数据收集和解释。具体而言，难以估计流量 遇到流量/速度以及外推实际流量的百分比。此外，本发明还提供了一种方法， 发现了车辆交通监测以外的机会。Engage Plus将允许MORR 进一步缩放所述设备发现系统以减轻与所述设备发现系统的可变范围相关联的不确定性。 扫描当前部署和设备。此外，MORR有机会扩展蓝牙的作用， 和WiFi数据收集通过推断流动交通以及相关的独特机会 交通延误导致了城市内不可预见的延误和拥堵。用低成本的原型 由MORR开发的，也是可行的，以解决数据收集从移动的探头和集成， 网络中的数据。后一种方法将固定探针与包含的移动的探针集成 将有助于增加一般可以众包的数据量， 速度和流量推断的参考或基线。Engage Plus将涉及两名研究生 并且允许将数据收集缩放到真实的环境或交通走廊。

A previous Engage grant afforded MORR the opportunity to explore technologies for inferring vehicular traffic through the monitoring of signals related to personal devices such as Smartphones, consumer and vehicular accessories. Commercially available systems such as Libelium's Meshlium were investigated as well as a custom platform (in-house) developed. Through this initial study, shortcomings and opportunities were exposed to extend data collection and interpretation. Specifically, difficulties in estimating traffic flow/velocities as well as extrapolating percentages of actual traffic were encountered. In addition, opportunities outside of vehicular traffic monitoring were identified. The Engage Plus will allow MORR to further scale the device discovery system to mitigate against uncertainties associated with the variable range of current deployments and devices scanned. In addition, MORR has the opportunity to extend the role Bluetooth and WiFi data collection has through inferring ambulatory traffic as well as unique opportunities associated with traffic delays caused unforeseen delays and congestion within the city. With the low cost prototype developed by MORR it is also feasible to address data collection from mobile probes and integration of that data within the network. This latter method of integrating stationary probes with the inclusion of mobile probes would serve to increase the amount of data that could be crowdsourced in general as well as providing references or baselines to velocity and flow inferencing. The Engage Plus will involve two research students and allow scaling of the data collection to a real environment or traffic corridor.