PROPERTY VALUTAION SYSTEM

ABSTRACT:
The valuation of real estate properties is a critical process in the fields of property management, banking,
taxation, investment, and urban planning. Traditional property valuation methods are often manual, time
consuming, subjective, and highly dependent on the experience of valuers, resulting in inconsistent and delayed
price estimation. Recent research in automated valuation models shows that integrating computerized data
processing, spatial information, and machine learning significantly improves valuation speed, transparency, and
prediction consistency. This project presents the design and development of a Property Valuation System, an
intelligent software application developed to estimate the market value of residential and commercial properties
based on various influencing parameters. The system collects and analyses key property attributes such as
location, land area, building size, age of construction, number of rooms, nearby facilities, legal approvals,
market demand, and historical sales records. By applying predefined valuation formulas and comparative
market analysis techniques, the proposed system generates an approximate and reliable valuation report for the
selected property. Modern valuation studies indicate that location intelligence, comparable sales analysis, and
automated regression-based methods are among the most effective contributors to realistic property pricing.

KEYWORDS:
Real Estate Valuation, Property Estimation, Automated Valuation Model, Market Price Prediction, Property
Database Management, Comparative Market Analysis, Geographic Information System (GIS), Machine
Learning, Decision Support System, Valuation Report Generation.