An efficient and intelligent model to control driving offenses by using cloud computing concepts based on road transportation situation in Malaysia

Information Technology (IT) has had undeniable effects on various industries in the recent years whereby road transportation industry and control services over vehicles and drivers are not apart from these effects. One of the most potential and new IT technologies that has not been considered and focused significantly in road transportation industry is cloud computing. This paper proposes an efficient and intelligence model for control driving offenses by using three main technologies in IT industry: Image Processing, Artificial Intelligence, and Cloud Computing. In the proposed model, Vertical-Edge Detection Algorithm (VEDA) was used for car license plate detection process in highways to provide an efficient image processing process with low quality images that were taken from installed cameras. Furthermore, two intelligence cloud-based Software-as-a-Service applications were used for car license plate detection, matching violations detected numbers with entrance detected numbers, and identification of possible exit routes for further processes. In addition, the suggested model contains a cloud server for storing databases and violation records which make them always accessible according to cloud computing concepts. The theoretical analysis of the proposed model was done according to three main parameters: efficiency, intelligence, and compatibility, and showed that Cloud-based Driving Offenses Control (CDOC) algorithm might be effective for providing an efficient method to control driving offenses and decreasing the rate of violations at highways.