TRAFFIC SURVEILLANCE AND MANAGEMENT SYSTEM
Road safety has been a major concern since news about the road accidents validating the inefficiency of current surveillance systems. To overcome this, an Automated System is preferable which also takes immediate action upon violation of rules or anomaly activities. Proper traffic management can ensure that traffic flows smoothly and efficiently by reducing human loss or preventing unwanted situations. The Effective solution deals with training ML models and monitoring with AI developer kit. The purpose of AI-based traffic monitoring which will take live video as input and analyze it to acquire information about live traffic. The details of the vehicle’s certain activity in traffic are displayed in a mobile app. Detection of vehicles activity will be compared both in simulation and real-time. This will be Developed as a Product which serves to the Society and also a part of the Smart Traffic Management system in nearby future.
Front End
Android Studio is used to create the user interface for the application. It is a mobile application integrated with google firebase.
Back End
For detecting the vehicle and number plate the model is designed using yolo algorithm. The detection algorithm/code is developed in Python programming. Once the object is detected the object image will be sent to Firebase storage. The hardware used is jetson nano. The code is implemented in jetson nano.
Application Images
