AI-Powered House Price Estimation Using Machine Learning

P. Jacob Vijaya Kumar, Ch Manoj Reddy, S. B. Chand Basha, U. Siva, R. Naga Sai Mukesh

2025

Abstract

The exact estimation of house prices plays a vital role in property decision-making to benefit all real estate market parties including buyers and sellers as well as investors. This research investigates the applicability of data-driven methods in property value estimation, with the support of artificial intelligence and machine learning. Sophisticated predictive models analyze different factors including geographic location and size of property structure and economic condition and market trends within a broad range of variables. This method depends on regression models as well as decision trees among ensemble learning techniques and deep neural networks to achieve better price estimation results. Research shows that price forecast accuracy success depends on selecting the right features which encompass property characteristics together with neighborhood variables and financial variables. Predictions generated from analyzing real estate data using deep learning combined with ensemble learning outperform conventional statistical methods in accuracy levels. The research explores additional approaches to improve accuracy which combine the analysis of external economic facts and sentiment evaluation of property marketing content and geospatial data assessment. Research confirms that property market analysis benefits significantly from AI-powered automated valuation models which distribute essential information throughout industry professionals and financial institutions and public policy institutions. The study enhances knowledge about AI-based property valuation while suggesting developments for machine-based property valuation models. This work expands AI-driven real estate valuation knowledge through its proposals for machine-based property valuation method development.

Paper Citation

in Harvard Style

Kumar P., Reddy C., Basha S., Siva U. and Mukesh R. (2025). AI-Powered House Price Estimation Using Machine Learning. In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25; ISBN 978-989-758-777-1, SciTePress, pages 369-376. DOI: 10.5220/0013883100004919

in Bibtex Style

@conference{icrdicct`2525,
author={P. Kumar and Ch Reddy and S. Basha and U. Siva and R. Mukesh},
title={AI-Powered House Price Estimation Using Machine Learning},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25},
year={2025},
pages={369-376},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013883100004919},
isbn={978-989-758-777-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25
TI - AI-Powered House Price Estimation Using Machine Learning
SN - 978-989-758-777-1
AU - Kumar P.
AU - Reddy C.
AU - Basha S.
AU - Siva U.
AU - Mukesh R.
PY - 2025
SP - 369
EP - 376
DO - 10.5220/0013883100004919
PB - SciTePress