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🚗🌍 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.
The network for creativity
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