Vision Based Traffic Control for Intelligence Ambulance Detection System
The increase in the number of vehicles brings the congestion problem to the road users especially the ambulance that stuck at the traffic junction and the simple traffic signal control system does not provide priority for the ambulance. To handle the problem faced, this paper presents the works in designing and developing a vision based traffic signal control system with priority for the ambulance and developed a traffic supervising system to synchronize the traffic condition to Firebase database and WhatsApp. The blob detection and colour detection method in the image processing technique is used to specify the size and colour of the ambulance required to be detected. Raspberry pi, webcams and LED traffic light module used to design a system model for prototyping the vision-based ambulance detection system and the system code is written in python language. Python IDE and Microsoft Visual Studio used to perform data analysis. In the system model, the sequence of traffic lights has been set to 3 seconds green light during normal conditions while 10 seconds green light during an emergency condition. Conclusively, the vision-based ambulance detection system was successfully designed and developed in which the system has provided an effective time response for the ambulance detected and works as a cloud-based monitoring system to synchronize the traffic condition to the database.