Traffic lights are no exception. The American traffic lights which have remained virtually unchanged for a century now are now influenced by machine learning. The result is an efficient, safer and greener transportation world. Preemption of traffic signals is one example. It can assist drivers in avoiding a potentially life-threatening collision. A system that incorporates traffic lights and an e-bike/scooter sensors can automatically time stoppages so that they align with commuters’ daily schedules.
IoT sensor and connectivity technologies allow smarter traffic control systems to maximize energy efficiency by optimizing signal timings in accordance with real-time conditions. The data collected by sensors and cameras can be processed on the device or transmitted to an automated traffic management hub which is then integrated into AI-based algorithms. The result is more precise modeling and a predictive analysis that could help avoid congestion, align schedules for public transport and reduce carbon emission.
These smart technologies can change the way we travel in urban areas. Smart sensors for e-bikes and scooters for instance, can detect and share the location of shared personal vehicles to make ride-sharing more efficient. Micromobility payment systems however permit on-street parking or road tolls without the requirement for accurate change.
IoT smart like this traffic technology can also increase the efficiency of public transport by allowing commuters to track trams and buses in real-time with live tracking apps. Intelligent intersection technology is able to prioritize emergency vehicles in order to help them get to their destination faster – an innovation that has already dramatically decreased crash rates in certain cities.