In present world, the problem of traffic congestion has become a major concern. It's not just restricted to megacities or metropolitans but even for small cities. Hence we require a smart or intelligent traffic control system. Our present traffic control system is not adaptive but is based on time and independent of the traffic density. This static nature makes it inefficient, chaotic and noisy. To tackle this issue of managing traffic roads a real time traffic information collection and monitoring system is proposed. The proposed model controls the clearance time of each lane in a sequential manner and is function of real time traffic density. The approach is rather hybrid - a blend of sensors networks and camera technology. United results of image processing and IOT ensures more accuracy and efficiency rather than native approach. Besides traffic congestion minimization, prioritization for emergency vehicle is also achieved through RFID. Other technology like stolen vehicle tracking/detection is also deployed. Simple GUI for use add an advantage to the system making it easy for control room to handle. The model could be used for analysis purpose and hence predict traffic jams and traffic status at different times. Hence proposed model is cost-effective and time efficient smart traffic control system.