Data Management In Order To Extract Knowledge

Today, the effective role of information technology in intelligent transportation systems is not limited to the use of IT approaches to set up and implement these systems, but also to collect, manage and analyze information from it, so achieving the goals of ITS without studying the data obtained It is impossible. Data derived from the use of intelligent transport systems has three prominent features. First of all, huge amounts of data are generated due to the use of a variety of sensors, cameras, global positioning systems (GPS), spatial information management systems (GIS), and moreover, the problem of storage, analysis and applications of these data presents serious challenges. Second, data is produced and changed at an unprecedented pace. Encountering a variety of data streams and rapid response to other challenge variations is considered. The use of information and communication technology in intelligent transport infrastructure hardware hard ware and the ability to store data types transmitted from this equipment has led. Massive database of information on the activities of this equipment. Transmitted data from cameras contains useful information that, if analyzed, can be used for prediction, control and management. The analysis of these bulky data is not possible by manual methods; data mining provides the ability to extract knowledge from the mass of information by using automated solutions. This paper presents an effective model for extracting knowledge from plaque-camera data. Implementing this model is a valuable knowledge of the behavior of the drivers of the public passenger transport fleet.