Smart Real-Estate System: A Data-Driven Approach to Property Management
Author(s):
S Mohammad Muzassar, A. KARTHIKRAM , A Madhan Kumar, G Lalith Prasad , P Manikumar Reddy
Keywords:
Smart Real Estate, Application, Machine Learning, EMI Prediction, Linear Regression, Random Forest, Text Process Algorithm, And Search Algorithm.
Abstract
The real estate industry plays a pivotal role in economic growth, facilitating property transactions worldwide. In this digital era, efficient real estate management systems are crucial for agents, buyers, and property owners. This paper presents the design and development of a Real Estate Management System (REMS) using PHP, aimed at providing a comprehensive platform for property listing, search, and communication. The REMS enhances user experience, improves efficiency, and facilitates seamless communication between stakeholders. This article speaks about Smart Real Estate Application which is a cutting-edge platform created to make it easier to purchase and sell properties using the most recent technological developments. It uses machine learning algorithms to precisely forecast a property's EMI price based on various aspects like total amount, duration, and Interest rate. Users can search through a sizable database of properties and select the one that most closely matches their requirements. To reach a larger audience and improve their chances of finding the ideal buyer or renter, users can also post their properties for sale or rent. Overall, this article provides insight into Smart Real Estate Application which provides a thorough response to the issues that both buyers and vendors of real estate must deal with. Its incorporation of machine learning algorithms guarantees that real estate prices are correctly predicted, enabling a more open and effective process for buying and selling.
Article Details
Unique Paper ID: 164160

Publication Volume & Issue: Volume 10, Issue 12

Page(s): 1105 - 1111
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