Receivers, installed in key positions around the city, detect the transmitters when they are in within a range of 30m to 100m (depending on the conditions). Only when the “smart” bicycle passes by one of the strategically placed receivers is it spotted by the system. This anonymous tracking is opted-into by the bike owner at the time of the transmitter’s installation. The receiver sees that an enabled bicycle is within range of a receiver, but no personal data is collected on that bicycle or the owner. Strategically, the receivers are installed near city-owned CCTV cameras that are recording the city, and as such, via time-stamping, the police can be given a video capture of the camera recording that is within the timestamp of when the receiver “saw’ the now stolen bike. And this is all configurable and automated via the DATflow platform
When a bicycle equipped with a transmitter is reported and logged as stolen into the BIKEtrace DATflow platform by the relevant authorities, the platform automatically provides:
- Real-Time Tracking: The receivers start monitoring this “activated” transmitter actively, and when spotted the DATflow platform sends a message to to the relevant authorities. This could be a police car that is in the area of the latest stolen transmitter spotting.
- Historical Tracking: The DATflow platform, which can now ID the transmitter and owner, starts looking for that unique transmitter ID for where it was tracked in the receiver network in the past. The log files for the unique transmitter are kept for a period of time per the use case requirements. .
Phase 4- Ongoing Support: Shortly after initial deployment, newer and stronger transmitters with extended battery life came out but with a different communication protocol for the receivers. The DATflow platform was re-configured and continues to be upgraded as per regular assessments. The next upgrade will allow for identification of the bike to within 10 feet by mobile receivers.
The result of this platform was a stark reduction and deterrent in bike theft in subject cities and more effective data management.
