Intelligent IoT systems for traffic management: A practical application

The incorporation of Artificial Intelligence algorithms in Intelligent Transportation Systems gives rise to new opportunities for a more sustainable urban mobility. However, one the main challenges is decide when and where these techniques should be applied; several options appear, such as cloud computing, fog edge or even devices. In this paper, an Internet Things-based solution smart traffic management presented. Using lightweight Random Early Detection Vehicles Dynamic mechanism basis, we optimize using evolutionary algorithms. can applied signaled intersections proactively detect incipient congestion set best cycle phases lights. Then, authors demonstrate that once has been appropriately optimised offline, it later used unknown scenarios without burden applying constrained Things performance widely tested with SUMO simulation tool. Results show improved version, called iREDVD, notably reduces vehicles’ waiting time, average trip fuel consumption, emission particles gaseous pollutants compared other proposals.