What question did this study set out to answer?

The aim is to develop an AI-powered framework for accurate property valuations in multiple currencies.

May 8, 2026Open Access

AqarMeter: AI-Powered Multi-Currency Valution

Key Points

The aim is to develop an AI-powered framework for accurate property valuations in multiple currencies.
Utilized the XGBoost machine learning algorithm for price estimation.
Integrated a FastAPI backend with a Flutter mobile application.
Evaluated model performance using Mean Absolute Percentage Error (MAPE).
Achieved a MAPE of 8.5%, indicating high accuracy in price estimates.
Provided objective price estimates in both SYP and USD.
Served as a reliable alternative to existing informal brokerage methods.

Abstract

AqarMeter: AI-Powered Property Valuation Framework Developed as a senior project at Arab International University, AqarMeter utilizes the XGBoost machine learning algorithm to deliver objective price estimates in both SYP and USD. Created by Zien Akram Alizraee under the guidance of Dr. Tareq Barhoum, the system integrates a FastAPI backend with a Flutter mobile application to address the absence of transparent valuation tools in Syria. The project achieved a MAPE of 8.5%, providing a robust alternative to informal brokerage methods. For more information on the institution, visit: https://www.aiu.edu.sy.

AqarMeter: AI-Powered Multi-Currency Valution

Key Points

Abstract

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