Development Of Real Estate Platform With Geolocation for Effective Rent-Cost Estimation

This study presents a geolocation-based real estate platform designed to provide a holistic view of housing affordability. Unlike traditional property platforms that focus solely on rental costs, the system integrates commuting expenses and proximity to essential amenities to estimate the true cost of living. Using Google Maps API for geolocation and distance calculations, the platform factors in rent, fuel consumption, fuel prices, and travel distances. The backend is built with Django ORM, while the frontend employs HTML, CSS, and JavaScript for usability. Evaluation results show that users achieved up to 20% annual cost savings, with high satisfaction ratings under the Technology Acceptance Model (TAM). The platform also scored strongly in Lighthouse analysis for efficiency, accessibility, best practices, and SEO. By bridging the gap between rental affordability and commuting costs, this work contributes a practical framework for transparent cost assessment in real estate, with potential extensions to utilities and other recurring expenses.