This study proposes to develop an intelligent monitoring system for the urban traffic and environmental management. In the proposed system, embedded system- based sensing devices are installed in vehicles to monitor the roads that each car takes, and the environmental parameters around the roads, including temperature, humidity, illumination, suspended particulates, and carbon monoxide. In this study, the sensed data will be directly transmitted to a decision support platform for traffic-related analysis to improve the use of roads, road safety and reduce traffic congestion. With the proposed vehicle sensing devices that deliver the sensing data to the decision support platform, drivers can make smart traffic decisions through the response from the proposed system. So drivers can avoid traffic bottlenecks and further reduce energy consumption and costs of cars. Moreover, the proposed system is capable of detecting damping coefficients, car speed, tire pressure, and oil consumption, and it can also provide information about potholes or road repaving as a preventive measure, so drivers can drive their cars in a more comfortable way. The proposed system is not only a safety and environmental monitoring system but the implementation of the concept of urban traffic and environmental management. Combining the adaptability analysis with IoT and information and communication technologies, this study is able to generate accurate information regarding major roads in urban area of Taiwan and provide better solutions to the improvement of road safety and conditions and the reduction of traffic congestion, and eventually helps the development of the cities in Taiwan.