Car Dirtiness and Damage Detection For Automatic Service Recommendation Using Machine Learning Techniques

Abstract

Automobile Industry is growing by a huge percentage in a few decades contributing about 7.5% to India’s total GDP. As the number of vehicle owners is increasing the demand and need for automobile service is also high but people are busy with their routines hence failing in proper maintenance of their vehicles. In this paper by using machine learning algorithms, and object detection we have come up with the idea to develop a web application that can suggest to users some offers and timing for their car maintenance by analyzing a car using computer vision without the owner’s involvement. The primary Aim of this project is to maintain a vehicle without disturbing the owner’s day-to-day routine. This project is built using the latest technologies and the most trending domains in the industry. We have used the YOLOV5 (You Only Look Once) object detection model and VGG16 architecture to analyze the car images and Flask framework to create a responsive interface for the web application. We generally don’t realize that multiple tasks can be done at a time resulting in many tasks being incomplete one of which is vehicle maintenance. This project aims at both owner’s convenience and the growth of the service provider’s business. In this paper, we present the Machine Learning based automated car maintenance system with effective time utilization which is an IOT device that could be installed at the parking’s main gate of places where people tend to spend many hours like offices or malls. This Device consists of a camera that is responsible for detecting a car image from the live video. These images are sent for the further process where the device detects if there are any damages or dirtiness in the car using pre-trained models.