Traffic lights are no exception. Virtually unchanged for more than 100 years, the current American traffic signals have entered the era of machine learning. The result is an efficient, safer, and more sustainable transportation system. Technology for preventing traffic signals, for example will help drivers avoid the possibility of a fatal collision with pedestrians. A system that combines traffic light sensors and e-bike/scooter sensors will automatically time stops so that they align with commuters’ travel schedules.
IoT sensor and connectivity technologies help intelligent traffic control systems that maximize energy efficiency by optimizing signal timings based on actual conditions. The data gathered from sensors and cameras can either be processed in the device itself, or sent to a hub for traffic management where it is integrated into AI algorithms. The result is a more precise model and predictive analysis data rooms providers for international companies that can help to avoid congestion, align schedules for public transportation and reduce carbon emission.
These advanced technologies could transform urban transport systems. Smart e-bike/scooter sensors for example, can detect and relay the locations of personal vehicles that are shared for more convenient ride-sharing, while micromobility payment systems permit on-street parking and road toll payments without the need for correct change.
IoT smart traffic technology could also increase the efficiency of public transport and make it easier for commuters to track trams and buses in real-time by using live tracking apps. Intelligent intersection technology can help prioritize emergency vehicles to ensure they reach their destination faster This is a breakthrough that has already reduced the number of crashes in some cities.