Traffic lights aren’t an exception. Virtually unchanged for more than 100 years, modern American traffic lights have entered the era of machine learning. The result is a more efficient, safer, and more green transportation system. Preemption of traffic signals, for example can aid drivers in avoiding a potentially life-threatening collision. A system that integrates traffic lights and an e-bike/scooter sensors can automatically time stoppages to align with commuters’ schedules of travel.
IoT sensor and connectivity technology helps to build more intelligent traffic control systems that maximize energy efficiency through optimizing signal timings in real time. The data collected by cameras and sensors can be pre-processed on the device or transmitted to a traffic management hub which is then integrated into AI-based algorithms. The result is a more precise and precise modeling as well as a predictive analysis that can help to avoid congestion, create schedules that align with public transportation, and decrease carbon emissions.
These advanced technologies can revolutionize urban transport systems. Smart sensors for e-bikes and scooters for instance, can identify and communicate the location of shared personal vehicles to make ride-sharing more convenient. Micromobility payment systems, on the other hand permit parking on the street or road tolls with no need for a change in the right amount.
IoT smart traffic technology could also improve public transit efficiency 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 get to their destination faster this is a major breakthrough that has already reduced crash rate in some cities.
