Drive Net

Abstract

Selling vehicles is not left behind in the digital era as technology is shaping the ways consumers want it. The website of the ‘DriveNet’ project aims to solve the problems of car sellers and buyers, which makes it remarkable. ‘DriveNet’ project is the trading site that enables the sellers to list their vehicles for sales and enable the buyers to have a view of the vehicles which they require and then contact the respective seller for the deal. DriveNet, using the Machine Learning approach, estimates the fair price of vehicles to provide the seller with superior values as well as the buyer to make informed decisons. It also aimed at creating a community of users with passion for cars or motorcycles as it is the case with many young people. The goals remain at 80% accuracy of the price prediction, the increase of the amount of users, 75% satisfaction rate, and a non-biased feedback system. No other investing application is as specialized in vehicles as DriveNet, which feature an easy-to-navigate GUI, ML vehicle price forecast, and a built-in community. The goal of the project is to facilitate selling cars, enhance the experience of the users, and enable people connected with cars to share their passion. The approach consists of requirement gathering phase, design phase, selection of technology stack, development phase, integration with community, machine learning and final phase of intense user testing phase. The overall design of the system is client/server with an object-oriented design paradigm.