Automatic car service recommendation system using machine learning techniques

M. Kumar, Abdullah Khan Mohammed, Siri Reddy Gundlapally, Tarun Ramavath, Yadav Sujith
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Abstract

The automobile industry has been growing at a high rate in the past few decades, contributing about 7.5% to India's total Gross Domestic Product (GDP). As the number of vehicle owners are increasing the demand and need for automobile service is also high, but people are busy with their routines, hence failing to perform proper maintenance on their vehicles. This paper uses machine learning algorithms and object detection to come up with the idea to develop a web application that suggests users some offers and timing for their car maintenance by analyzing a car using computer vision without the owner's involvement. This project aims at both the owner's convenience and the growth of the service provider's business. Generally, we do not realize that multiple tasks can be done at a time, which results in incomplete tasks. This paper presents a machine learning-based automated car maintenance system with effective time utilization, by using the Internet of Things (IoT) device that could be installed at the parking's main gate in 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 then sent to the device, which uses pre-trained models to detect any damages or dirtiness in the vehicle.
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采用机器学习技术的自动汽车服务推荐系统
在过去的几十年里,汽车行业一直在高速增长,对印度国内生产总值(GDP)的贡献率约为7.5%。随着车主数量的增加,对汽车服务的需求和需求也很高,但人们的日常工作很忙,因此没有对他们的车辆进行适当的维护。本文使用机器学习算法和对象检测来开发一个web应用程序,该应用程序在没有车主参与的情况下,通过计算机视觉分析汽车,为用户提供一些建议和维修时间。这个项目的目的是为了业主的方便和服务提供商的业务增长。通常,我们没有意识到可以同时完成多个任务,这就导致了任务不完整。本文通过使用物联网(IoT)设备,提出了一种基于机器学习的有效利用时间的自动汽车维修系统,该系统可以安装在人们倾向于花费很多时间的地方的停车场正门,如办公室或商场。该装置由一个摄像头组成,负责从实时视频中检测汽车图像。然后将这些图像发送到设备,该设备使用预先训练的模型来检测车辆中的任何损坏或污垢。
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