IoT Hybrid Computing Model for Intelligent Transportation System (ITS)

IoT - a new proliferation in the technological advancement, changed the way object is perceived and used. It enables connecting smart objects to the internet and aims to develop new promising future to Intelligent Transportation System (ITS). ITS uses techniques such as wireless communication, computational technologies, GPS, and sensor technologies to provide smart and quick services to users and to be better informed and make safer, more coordinated, and 'smarter' use of transportation medium. As number of objects connected to ITS application increases, the amount of data generated also increases and they are send to cloud for data analysis and knowledge discovery. However, sending and retrieving of data across cloud is less useful due to delay latency and others. An alternative to cloud is fog (edge) model that overcomes the weakness of cloud by analyzing and discovering knowledge at the edge. However, the fog computing model has limited computational capability. For an IoT enabled Intelligent Transportation System with enormous number of objects connected, neither cloud nor fog computing model addresses the issues alone. This paper focuses on presenting an IoT hybrid model for Intelligent Transportation System (ITS). We also address the effectiveness of the model by discussing use case scenarios.