BLOCK ESTATE

The real estate sector grapples with the persistent issues of inconsistent property appraisals, a lack of transparency in valuation methodologies, and a reliance on outdated pricing frameworks. This project introduces an innovative solution: a distributed ledger-based real estate valuation system. This system leverages self-executing digital agreements and spatial data analytics to deliver dynamic, transparent, and data-driven property assessments. By incorporating OpenStreetMap APIs, the system automates the acquisition of real-time data pertaining to proximate community resources, such as educational institutions, healthcare facilities, recreational spaces, and public transit networks. A weighted valuation algorithm processes this information to derive a contextual relevance score, quantifying the spatial influence and impact of these factors on property values. The computed scores, along with pertinent property details, are securely stored and managed on the Ethereum network via smart contracts, ensuring data integrity, immutability, and enhanced stakeholder trust. Furthermore, the system automates the entire valuation workflow through a Python-based backend, which serves as an intermediary between distributed ledger interactions and spatial data acquisition. Designed for scalability, transparency, and operational efficiency, this project aims to modernize conventional property valuation practices by addressing inherent inefficiencies and empowering stakeholders with access to reliable, up-to-the-minute valuation data. By redefining the paradigm of property value assessment, this system offers a transformative approach to real estate pricing, harmonizing cutting-edge distributed ledger technology with advanced spatial data analysis.

Authors

Publication Details

Journal
International Journal For Multidisciplinary Research
Published
2025-05-17
DOI
https://doi.org/10.36948/ijfmr.2025.v07i03.45055
Primary Topic
Housing Market and Economics
Type
article
Field-Weighted Citation Impact
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article

BLOCK ESTATE

Sarah Shaikh, BADADHE SHIVAJI, VENKATESH IYER, ARUN GHANDAT
International Journal For Multidisciplinary Research
Housing Market and Economics
article

BLOCK ESTATE

Sarah Shaikh, BADADHE SHIVAJI, VENKATESH IYER, ARUN GHANDAT
article en

Abstract

The real estate sector grapples with the persistent issues of inconsistent property appraisals, a lack of transparency in valuation methodologies, and a reliance on outdated pricing frameworks. This project introduces an innovative solution: a distributed ledger-based real estate valuation system. This system leverages self-executing digital agreements and spatial data analytics to deliver dynamic, transparent, and data-driven property assessments. By incorporating OpenStreetMap APIs, the system automates the acquisition of real-time data pertaining to proximate community resources, such as educational institutions, healthcare facilities, recreational spaces, and public transit networks. A weighted valuation algorithm processes this information to derive a contextual relevance score, quantifying the spatial influence and impact of these factors on property values. The computed scores, along with pertinent property details, are securely stored and managed on the Ethereum network via smart contracts, ensuring data integrity, immutability, and enhanced stakeholder trust. Furthermore, the system automates the entire valuation workflow through a Python-based backend, which serves as an intermediary between distributed ledger interactions and spatial data acquisition. Designed for scalability, transparency, and operational efficiency, this project aims to modernize conventional property valuation practices by addressing inherent inefficiencies and empowering stakeholders with access to reliable, up-to-the-minute valuation data. By redefining the paradigm of property value assessment, this system offers a transformative approach to real estate pricing, harmonizing cutting-edge distributed ledger technology with advanced spatial data analysis.

International Journal For Multidisciplinary ResearchVol. 7(3)
Openalex Percentile: Top 85%
Housing Market and Economics
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