The Implementation of OBD-II Vehicle Diagnosis System Integrated with Cloud Computation Technology

This paper implemented a cloud computation based second generation on-board diagnostic (OBD-II) system. The proposed system is integrated with OBD-II, 3.5G wireless network, and cloud computing technologies. It can perform real-time vehicle status surveillance. The monitored features cover engine rpm, vehicle speed, coolant temperature, fault codes, and other vehicle dynamics information. The vehicle information will be transmitted to the cloud computing server via 3.5G wireless network for fault analysis. Once cloud computing server detects fault conditions, the proposed system could classify the fault conditions depended on vehicle type and its model year. Then the cloud computing server will report the fault code analysis results to the user and provide the description about repair procedure. The proposed system will greatly shorten the time to detect vehicle trouble condition. The system presented in this thesis has a very high value in the applications of vehicle maintenance and fleet management.