Real MIT: a Property Analysis Tool for Real Estate Investment

An investment in real estate is one of the key paths to wealth, offering potential for long-term financial growth through property value increase and rental income. However, real estate investors face tough market research. They need to understand the various economic trends and data, which are complicated and time-consuming. Although many existing tools for property investments are invented to assist the investors, those tools don't do enough for decision-making in investment process due to the difficulty to use and to do effective analysis. Moreover, the market data in real estate are scattered across different data sources, making it hard to get an overall picture and to make smart choices. To solve these problems, the main objective of this project is to design and develop a web application named Real MIT, as a tool for property analysis for real estate investment. The application brings together all the essential information by consolidating critical market data and provides several useful functionalities such as dashboard for displaying key market trends, property data exploration, a side-by-side comparison of properties, and analysis on property’s detailed aspect scores. The evaluation results show that Real MIT is a robust and user-friendly tool that enhances the efficiency of evaluating property potential, thereby providing real estate investors with a superior analytical platform compared to traditional tools like Microsoft Excel.

Authors

Institutions

Publication Details

Published
2025-05-22
DOI
https://doi.org/10.1109/icbir65229.2025.11163371
Primary Topic
3D Modeling in Geospatial Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Real MIT: a Property Analysis Tool for Real Estate Investment

Songsri Tangsripairoj, Noppasit Laopoonphol, Nattapong Mumklang, Izada Lertanantachai
3D Modeling in Geospatial Applications
article

Real MIT: a Property Analysis Tool for Real Estate Investment

Songsri Tangsripairoj, Noppasit Laopoonphol, Nattapong Mumklang, Izada Lertanantachai
article en

Abstract

An investment in real estate is one of the key paths to wealth, offering potential for long-term financial growth through property value increase and rental income. However, real estate investors face tough market research. They need to understand the various economic trends and data, which are complicated and time-consuming. Although many existing tools for property investments are invented to assist the investors, those tools don't do enough for decision-making in investment process due to the difficulty to use and to do effective analysis. Moreover, the market data in real estate are scattered across different data sources, making it hard to get an overall picture and to make smart choices. To solve these problems, the main objective of this project is to design and develop a web application named Real MIT, as a tool for property analysis for real estate investment. The application brings together all the essential information by consolidating critical market data and provides several useful functionalities such as dashboard for displaying key market trends, property data exploration, a side-by-side comparison of properties, and analysis on property’s detailed aspect scores. The evaluation results show that Real MIT is a robust and user-friendly tool that enhances the efficiency of evaluating property potential, thereby providing real estate investors with a superior analytical platform compared to traditional tools like Microsoft Excel.

Mahidol University (TH)
Openalex Percentile: Top 73%
3D Modeling in Geospatial Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.