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Article history: Received: 31 August, 2020 Accepted: 04 December, 2020 Online: 21 December, 2020 In an intelligent transportation system (ITS), time is a big challenge since processing a huge amount of data in a short time is very difficult, especially when the processed data is heterogeneous, consisting of a mixture of emergency data, normal data, and noise. In an ITS, an ambulance is one of the priority vehicles, and the data sent by the ambulance to the infrastructure and other vehicles must be treated first because if the ambulance does not receive a status of road from the infrastructure in time, it could take the wrong road or takes a road where there is a traffic jam has a high chance of arriving late, which could put the patient's life in danger. Prioritizing treatment of this type of data has become paramount and vital in such cases. This paper proposes modifying the big data process to include handling the intelligent transport system's urgent data type. We will add a classification step that allows us to classify the data according to the priority degree. We use the SVM algorithm of machine learning because it has given good results concerning data classification.

Handling Priority Data in Smart Transportation System by using Support Vector Machine Algorithm