Author(s): Mouammine Zakaria, H. Khoulimi, A. Ammoumou, B. Nsiri
This paper proposes an innovative model to enable intelligent transportation which rationalizes logistics/transportation cost and increases subsequently the value independently to whether or not there is an intelligent infrastructure. The proposed model is an operational framework for automatic monitoring of road traffic state and transportation conditions through a near-real time detection of related events. Facebook and twitter social networks are used as a source of social data. To deal with comments/tweets written in Moroccan Dialect a set of tools related to big data architecture are utilized respectively, Machine Learning Algorithms and Apache spark framework. We applied our model to monitor the traffic on the city of casablanca which is the larger city in morocco, the obtained results reveal that our method is able to enable intelligent transportation, more precisely it can detect automatically road traffic events, without any prior information, this has allowed the real time traffic operation monitoring, To the best of our knowledge, this is the first work addressing traffic event detection from tweets written in Moroccan dialect language using machine learning and Apache Spark big data platform.