Traffic lights aren’t an exception. The American traffic lights which have remained virtually unchanged for more than a century now are now being controlled by machine learning. The result is a more efficient more sustainable, safer and greener transport world. Preemption of traffic signals is one example. It can assist drivers in avoiding potentially life-threatening collision. And a system that integrates traffic lights and e-bike/scooter sensors will automatically time stops to coincide with commuters’ travel schedules.
IoT sensors and connectivity technologies enable more intelligent traffic control systems to maximize energy efficiency by optimizing signal timings based upon real-time conditions. The data from sensors and cameras can either be processed within the device or sent to a hub for traffic management, where it will be integrated into AI algorithms. The result is a more precise modeling and a predictive analysis that could help avoid congestion, improve schedules for public transit and reduce carbon emission.
These technologies are transforming urban transportation systems. Smart e-bike and scooter sensors, for instance, are able to detect and share the locations of personal vehicles that are shared for more convenient ride-sharing while micromobility payment systems enable parking on the street and road toll payment without the need to changes.
IoT smart traffic technology can also improve public transit efficiency, making it easier for commuters to track trams and buses in real-time with live tracking apps. Intelligent intersection technology can prioritize emergency vehicles in order to help them get to their destination quicker this innovation has already drastically reduced the number of crashes in certain cities.
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