Traffic lights aren’t an exception. The American traffic lights, which have remained virtually unchanged for more than a century now are now being dependent on machine learning. The result is an efficient, safer and greener transportation world. Technology for preventing traffic signals, for example can assist drivers in avoiding an injury-causing collision with pedestrians. A system that incorporates traffic lights and e-bike/scooter sensors will automatically schedule stoppages to coincide with commuters’ timetables.
IoT sensor and connectivity technology allows smarter traffic control systems that maximize energy efficiency by improving signal timings according to real-time conditions. The data that cameras and sensors can be processed on the device or sent to a traffic management hub, where it is incorporated into AI-based algorithms. The result is more precise and precise modeling as well as a predictive analysis that will help prevent congestion, align schedules for public transport and reduce carbon emission.
These technologies are transforming urban transport systems. Smart e-bike/scooter sensors, for instance, can identify and relay the location of shared personal vehicles to make it easier to share rides, micromobility payment systems can facilitate parking on the street and road toll payment without the need to change.
IoT smart traffic technology can enhance the efficiency of public transit making it easier for commuters to track buses and trams in real-time using live tracking apps. Intelligent intersection technology can prioritize emergency vehicles to help them get to their destination faster This innovation has already drastically reduced the rate of crashes in a few cities.