A Real-Time Notification System for Traffic Congestion on South African National Routes

Abstract

Transportation is an integral part of our daily life, and now with an ever increasing number of cars on the roads, traffic congestion is inevitable. Traffic congestion has a huge impact on service delivery and, in turn, on the economy of the country. Social network has revolutionized our lives, and commuters are now able to vent their frustrations and post live updates regarding these congestions. Social networks have enabled humans to become active live sensors participating in the network communication paradigm. This paper leverages Naïve Bayes classifier of Artificial Intelligence (AI) for data classification, .NET MAUI framework for application development, Social Network Scraping tool for collecting traffic congestion data from Twitter, and Sklearn library of Python to prepare, clean, and make meaning out of the Twitter data. The outcome of the notification system will assist commuters to plan their trips efficiently using alternative roads as suggested by the real-time traffic congestion notification system developed.