PropVista: Intelligent Property Selection System

Property selection is a complex process involving financial, legal, and technical considerations. However, traditional approaches often overlook critical factors such as soil quality, environmental conditions, and lifestyle suitability. This paper presents PropVista, an intelligent property selection system that integrates Artificial Intelligence (AI), Machine Learning (ML), and IoT-based soil analysis to enhance decision-making. The system evaluates properties using parameters such as Safe Bearing Capacity (SBC), soil moisture, environmental risks, and user preferences. A weighted scoring model is applied to generate accurate and personalized recommendations. The system also incorporates features such as lifestyle suitability analysis and future development prediction to support long-term investment decisions. The implementation demonstrates improved accuracy, faster response time, and enhanced user experience. The proposed system reduces dependency on experts and provides a transparent, data-driven approach to property evaluation.

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Publication Details

Journal
International Journal of Technology & Emerging Research
Published
2026-05-30
DOI
https://doi.org/10.64823/ijter.2605021
Primary Topic
Soil and Land Suitability Analysis
Type
article
Field-Weighted Citation Impact
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article

PropVista: Intelligent Property Selection System

Shwetkranti Taware, Pragati Gaikwad, Jagruti Patil, Rohan Anil Bondre et al.
International Journal of Technology & Emerging Research
Soil and Land Suitability Analysis
article

PropVista: Intelligent Property Selection System

Shwetkranti Taware, Pragati Gaikwad, Jagruti Patil, Rohan Anil Bondre, Namrata Kedar
article en

Abstract

Property selection is a complex process involving financial, legal, and technical considerations. However, traditional approaches often overlook critical factors such as soil quality, environmental conditions, and lifestyle suitability. This paper presents PropVista, an intelligent property selection system that integrates Artificial Intelligence (AI), Machine Learning (ML), and IoT-based soil analysis to enhance decision-making. The system evaluates properties using parameters such as Safe Bearing Capacity (SBC), soil moisture, environmental risks, and user preferences. A weighted scoring model is applied to generate accurate and personalized recommendations. The system also incorporates features such as lifestyle suitability analysis and future development prediction to support long-term investment decisions. The implementation demonstrates improved accuracy, faster response time, and enhanced user experience. The proposed system reduces dependency on experts and provides a transparent, data-driven approach to property evaluation.

International Journal of Technology & Emerging ResearchVol. 2(5)
Savitribai Phule Pune University (IN)
Openalex Percentile: Top 3%
Soil and Land Suitability Analysis
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