LandSin: A differential ML and google API-enabled web server for real-time land insights and beyond

LandSin , a web application with a back-end database, is developed for global land value estimation by combining polynomial regression and differential privacy models. Leveraging local amenities and property details, LandSin offers key features, e.g., accurate land value and price predictions, affordability and habitability analysis, and terrain insights using Google Maps. In addition, it facilitates useful infographics, helping stakeholders identify economically deprived but habitable areas for balanced regional development. It also supports real estate agencies and community planners in finding habitable land by making data-driven decisions regarding land investments and regional planning, ensuring informed and strategic choices. • LandSin offers dynamic land value prediction using machine learning and differential privacy. • It integrates Google Maps for terrain insights and habitability analysis for real estate decisions. • LandSin helps real estate agencies assess investment opportunities by analyzing market trends. • Differential privacy ensures user data security while providing accurate land value estimates. • Governments can use LandSin for regional planning by identifying economically deprived areas.

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Publication Details

Journal
Software Impacts
Published
2024-11-01
DOI
https://doi.org/10.1016/j.simpa.2024.100718
Primary Topic
ICT in Developing Communities
Type
article
Field-Weighted Citation Impact
0.00
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article

LandSin: A differential ML and google API-enabled web server for real-time land insights and beyond

Imran Hasan, Mohammad Ali Moni, Md. Sadek Ali, AKM Azad et al.
Software Impacts
ICT in Developing Communities
article

LandSin: A differential ML and google API-enabled web server for real-time land insights and beyond

Imran Hasan, Mohammad Ali Moni, Md. Sadek Ali, AKM Azad, Píetro Lió, Salem A. Alyami, Alauddin Sabari
article en

Abstract

LandSin , a web application with a back-end database, is developed for global land value estimation by combining polynomial regression and differential privacy models. Leveraging local amenities and property details, LandSin offers key features, e.g., accurate land value and price predictions, affordability and habitability analysis, and terrain insights using Google Maps. In addition, it facilitates useful infographics, helping stakeholders identify economically deprived but habitable areas for balanced regional development. It also supports real estate agencies and community planners in finding habitable land by making data-driven decisions regarding land investments and regional planning, ensuring informed and strategic choices. • LandSin offers dynamic land value prediction using machine learning and differential privacy. • It integrates Google Maps for terrain insights and habitability analysis for real estate decisions. • LandSin helps real estate agencies assess investment opportunities by analyzing market trends. • Differential privacy ensures user data security while providing accurate land value estimates. • Governments can use LandSin for regional planning by identifying economically deprived areas.

Software ImpactsVol. 22
Charles Sturt University (AU), University of Washington (US), Imam Mohammad ibn Saud Islamic University (SA), University of Cambridge (GB), Islamic University (BD), Artificial Intelligence in Medicine (Canada) (CA), Jahangirnagar University (BD)
Climate action
Openalex Percentile: Top 68%
ICT in Developing Communities
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LandSin: A differential ML and google API-enabled web server for real-time land insights and beyond — Imran Hasan, Mohammad Ali Moni, et al. · Software Impacts (2024) | TGRS Research Map | TGRS