The U.S. Department of Transportation (USDOT) is actively researching intelligent transportation systems (ITS) aimed at reducing traffic incidents, improving safety, and gathering real-time travel time (TT) information. An important aspect of the process is specifying the characteristics of traffic schemes, which include vehicle classification, origin/destination (O/D), TT, and vehicle occupancy, in addition to other factors. The project proposes the development of an Internet of Things (IoT) systems that integrates a complex system using Bluetooth (BT) sniffing and vehicle classification for monitoring route choices per vehicle class. The system consists of a BT identification 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 the magnetometer nodes, the changes in magnetic field are measured to identify vehicle length and speed. Algorithms were developed to associate detected BT addresses to the corresponding vehicles with exceptional accuracy. Research demonstrated that active monitoring of route choice and TT per vehicle class can be achieved using magnetometer nodes and BT stations.