IOT system for Bluetooth based Origin-Destination studies

Abstract

Designing and modelling a transportation system is a complicated, yet crucial task that demands comprehensive study of public needs. An important aspect of the process is specifying the characteristics of traffic schemes, which include vehicle classification, origin/destination (O/D), travel time (TT), and vehicle occupancy, in addition to other factors. A more thorough understanding of these factors will lead to improved transportation planning. This thesis proposes the development of an Internet of Things (IoT) system that integrates two systems, namely Bluetooth (BT) identification and vehicle classification, for monitoring route choices per vehicle class. The extant system consists of one BT identification/vehicle classification unit deployed at an Oklahoma port of entry, along with a number of BT identification stations deployed at various locations across Oklahoma’s roadways. As vehicles travel over magnetometer nodes, sensors measure changes in magnetic field (i.e., vehicle magnetic signature) for defining each vehicle’s time of arrival and time of departure. Stated times will be used to estimate magnetic length of a passing vehicle for the purpose of classifying the vehicle. During this process, the BT ID of detected BT mobile devices in the vehicle is captured using BT identification stations. Algorithms were developed to associate detected BT addresses to the corresponding vehicles with exceptional accuracy. BT addresses are planned to be sent alongside the vehicle group to a server where they will be matched by multiple stations as the vehicle travels on observed roadways. Hence, active monitoring of route choice and TT per vehicle class is achieved using only inexpensive BT stations.