APPLICATION OF DEEP LEARNING FOR ADVANCED TRAFFIC LIGHT CONTROLLER WITH ANIMAL DETECTION USING ESP32 CAMERA MODULE

Abstract

We can see many animals like cows, Buffaloes, dogs, cats, etc on road. The safety and security of animals as well as drivers is at stake due to them. This leads to accidents on a large scale. The existing traffic system does not provide the measures for security of humans as well as animals. It is necessary to make advancements in existing traffic light system to avoid these accidents. For this purpose, we have used the ESP32 camera module, this module is trained with images of various animals to detect the animal in the four-way traffic system. The ESP32 camera module is connected to four-way traffic system. The four-way traffic system is operated with the help of Arduino Uno. The traffic system is both timer based and sensor based, the timer based is open loop controller similarly the sensor based is closed loop controller. The timer-based approach can be applied when the traffic density is quite low and the sensor-based approach is used for controlling the increasing density of traffic.