Skip to main content

Bluetooth-based traffic detection

Traffax has launched BluFax, based on the globally ubiquitous Bluetooth digital communications protocol, which operates by detecting the MAC addresses of Bluetooth signals from passing cars.
February 6, 2012 Read time: 2 mins
A BluFax freeway installation in Indiana
2262 Traffax has launched BluFax, based on the globally ubiquitous 1835 Bluetooth digital communications protocol, which operates by detecting the MAC addresses of Bluetooth signals from passing cars. By positioning two units at distances of between 1-3km, vehicle travel times are calculated from the relative detection times recorded by the two units. Traffax has licensed the patent-pending technology from the University of the Maryland, where the concept originated under the support of the Maryland State Highway Administration.

Traffax says Bluetooth address matching can be used for a number of applications including measurement of travel times on both freeway and arterial roadways, measurement of origin-destination patterns, and tracking of pedestrian flows. Since it directly measures travel times and space-mean speeds, Traffax claims BluFax is one of the few technologies that offers the ability to accurately measure arterial travel times. The company says that demonstrated detection rates exceeding five per cent of the total traffic stream, yield sample sizes adequate for reliable measurement of arterial flows.

There are two versions of the Traffax BluFax unit. An off-line version is offered that stores its measurements on removable storage media for subsequent processing. This device is typically used for traffic studies, performance measurement and validation of other data collection techniques. It is self-powered and requires no communications.

A real-time version is also offered that continuously transmits the MAC addresses and detection times of passing vehicles to a collection site for continuous processing. The real-time unit is used for such applications as display of travel times on variable message signs, and data inputs to 511 telephone systems.

Related Content

  • October 7, 2013
    Keeping over-height and overheating vehicles out of tunnels
    A review of pre-warning solutions for problematic commercial vehicles approaching tunnels
  • April 14, 2025
    Lidar lets planners see big picture in Chattanooga
    The city of Chattanooga, Tennessee, is attempting to make its streets safer by using the largest deployment of Lidar-based traffic detection in the US. Adam Hill reports…
  • May 18, 2018
    New ANPR solutions overcome variables
    The sheer range of variables makes it difficult to find a single algorithm to ensure a 100% standard of ANPR. David Crawford investigates new processing technology. Automatic number plate recognition (ANPR), using optical character recognition and image-processing to identify vehicles, plays key roles in traffic monitoring and law enforcement, access and parking control, electronic toll collection, vehicle security and crime deterrence. Overall, system performance is well rated, with high levels of
  • June 22, 2016
    Targeted roadside advertising project uses deep learning to analyse traffic volumes
    A targeted roadside advertising project for digital signage using big data and deep learning just launched in Tokyo, Japan, by US smart data storage company Cloudian will focus on vehicle recognition and the ability to present relevant display ads by vehicle make and model. Together with Dentsu, Smart Insight Corporation, and QCT (Quanta Cloud Technology) Japan, and with support from Intel Japan, the project will conduct, at its first stage, deep learning analysis – artificial intelligence (AI) for recog