Due to the increasing number of vehicles accessing higher education campus nowadays, it is difficult to check the rule regulations, enforcement and security. Currently, the security checkpoint is still using the manual procedures to track vehicle driver’s entrance. At the same time, it is timeconsuming for an officer to check the car sticker/plate every day physically. Also, it is not workable for a hire full-time security officer just to check on the sticker/car plate. As a solution, an artificial intelligence system to identify the car plate has been building up. By implementing this intelligence system, it’s capable of enhancing the management, security and controlling of vehicles accessing by using license plate recognition. If a vehicle approaches the entry gate, the recognition system will initialize and execute license plate numbers to the database system. During the exits through the departure gate, the same method repeated. The archives of vehicle entries and departures im.....

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The role of poverty rate, medical diagnoses, napping and medication on sleep habits contribute to the academic performance of the children. The problem of sleeping student in class room is an underestimated problem in the Malaysia. The goal of our project was to produce a non-intrusive, portable and easy to use solution to detect whether or not a person was falling asleep while at classroom. The methods used in our system were sensors to detect whether or not the eye was open or closed and sensors to detect whether or not the head was dipped below a certain angle. This data was transmitted wirelessly where a microcontroller was used to determine whether or not to activate our alarm system. Our project was developed in C code and testing and verification were performed to validate the accuracy of the sensors and alarm decision system..

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The development of technologies for preventing drowsiness at the wheel is a major challenge in the  field of accident avoidance systems. Preventing drowsiness during driving requires a method for  accurately detecting a decline in driver alertness and a method for alerting and refreshing the  driver. As a detection method, the authors have developed a system that uses image processing  technology to analyse images of the road lane with a video camera integrated with steering wheel  angle data collection from a car simulation system. The main contribution of this study is a novel  algorithm  for drowsiness detection and tracking, which is based on the incorporation of  information from a road vision system and vehicle performance parameters. Refinement of the  algorithm is more precisely detected the level of drowsiness by the implementation of a support  vector machine classification for robust and accurate drowsiness warning system. The Support Vector  Machine (SY.....

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