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.

https://doi.org/10.59200/ICONIC.2022.009