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The online car service booking system has gained significant popularity in recent years due to its convenience and efficiency. This project aim is to develop a comprehensive system that enables users to book car services online and predicts the price of used cars based on available data. The system utilizes a dataset that contains information about various car service centers, including their locations and services offered. By leveraging this dataset, the system can recommend the nearest service provider based on the user's location, ensuring timely and convenient service booking. Furthermore, the system incorporates a machine learning model trained on a separate dataset of used car prices. This model takes into account factors such as car make, model, year, mileage, and condition to predict the approximate price of a used car. Users can input the relevant information about their car, and the system will provide an estimated price range based on the trained model. The implementation of the system involves developing a user-friendly web interface that allows users to input their location, select desired services, and view the estimated prices for their used cars.
Keywords:
Online Service Booking, Nearest Service Provider, Desired Service, Price Prediction, Trained model.
Cite Article:
"Smart Service and Price Prediction", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.8, Issue 5, page no.734 - 739, May-2023, Available :http://www.ijrti.org/papers/IJRTI2305115.pdf
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000205326
ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator