🚗🌍 Can a navigation system recommend the most fuel-efficient route instead of simply the shortest one?

This project was developed as part of my MPhil Remote Sensing & GIS thesis.

I designed and developed an intelligent Web GIS routing system that generates and compares four alternative routes between an origin and destination and recommends the most suitable route using a Multi-Criteria Decision-Making (MCDM) approach.

Instead of considering only distance, the system evaluates multiple factors such as:

• 🌱 Fuel-efficiency / environmental suitability • ⏱ Travel duration • 🚧 Road hurdles and route conditions • 📏 Travel distance

The alternatives are evaluated using a TOPSIS-based decision model, allowing the system to identify the route with the best overall balance rather than simply choosing the shortest path.

I also integrated an AI assistant that explains route recommendations in natural language, helping users understand why one route is preferable to the alternatives.

Key features:

• Interactive Web GIS navigation • Four-route generation and comparison • MCDM/TOPSIS route ranking • Fuel-efficient route recommendation • Route distance and travel-time analysis • Road-condition / hurdle consideration • AI-generated route explanations • Interactive route visualization • Decision-support interface for sustainable mobility

Built with Python, Django, GIS, Leaflet/OpenStreetMap, MCDM and AI integration.

This research explores how GIS + decision science + AI can support smarter and more sustainable urban mobility.