This paper monitors and detects the neighbor's activities in smart vehicle using computer vision technology and innovation of Internet of Things (IoT). These activities include vehicles monitoring, movement, and location status of vehicle. The proposed solution recognized vehicles neighbors and collects data from whole sensors of vehicle, vehicle engine, road info, mobile of the derivers, and analyze such data to make some decisions. The decision includes vehicles monitoring, automated accident, road safety, air pollution, and congestion reduction in road. Therefore, the paper suggests a data analysis method to model many devices and engines, based on ontology formulation and IoT technology. This in addition, modeling and managing over such places information from anywhere at any time. Accordingly, the current paper investigate and focus on ideation and assessing the potential of computer vision using vehicles and roads signs detections, to control traffic congestion in smart roads. Consequently, an intelligent traffic approach (vehicles and road signs recognitions) will be presented in real smart vehicles or drivers assistant system. Several scenarios to identify potential components of ITVS to recognize neighbor's vehicles based on ontology architecture and road signs issues will be analyzed and recognized. The paper sketches out and develops an ontology-based to represent vehicle, drivers, roads, traffic and weather, so five ontologies will be drawn and presented. Vehicle detection ontology-based with Haar features and computer vision library will be implemented and tested. Although, traffic detection is used to help and warn drivers for specific actions. Therefore, driving safety is increased and it will be comfort. The recognition task of the vehicles and the detection task of signs within the road will be developed and tested.