Adaptive IoT Empowered Smart Road Traffic Congestion Control System Using Supervised Machine Learning Algorithm. (19th May 2020) - Ata, Ayesha; Khan, Muhammad Adnan; Abbas, Sagheer; Khan, Muhammad Saleem; Ahmad, Gulzar
Abstract: The concept of smart systems blessed with different technologies can enable many algorithms used in Machine Learning (ML) and the world of the Internet of Things (IoT). In a modern city many different sensors can be used for information collection. Algorithms that are cast-off in Machine Learning improves the capabilities and intelligence of a system when the amount of data collectedincreases. In this research, we propose a TCC-SVM system model to analyse traffic congestion in the environment of a smart city. The proposed model comprises an ML-enabled IoT-based road traffic congestion control system whereby the occurrence of congestion at a specific point is notified.