AI-Driven Approach for Sustainable Bicycle Tourism Development in Sri Lanka
EcoCycle Explorer is an innovative Android mobile application with web application designed to revolutionize sustainable bicycle tourism in Sri Lanka. Leveraging artificial intelligence, the app ensures enhanced user safety, optimized routes, and immersive experiences while promoting eco-friendly tourism.
24-25J-217
- Dr. Samantha Rajapaksha
- Mr. Nelum Chathuranga Amarasena
- Bandara K.M.V.T. (Team Leader)
- Bandara R.M.D.L.
- Chandrasena H.M.K.G.J.K
- Kumara M.G.S.D
To develop an AI-driven mobile application to:
- Enhance sustainable bicycle tourism in Sri Lanka.
- Provide real-time hazard detection and route optimization using ML models.
- Develop a Location base Voice Navigation System with multilingual support
- Deliver an immersive cycling experience integrating eco-friendly and culturally rich elements.
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AI-Driven Route Optimization
- Personalized routes based on user preferences, weather conditions, and road hazards.
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Hazard Detection (ML-Based)
- Real-time detection of dangerous road bends, sandy surfaces, and other hazards using mobile phone sensors.
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Location-based Voice Navigation
- Multilingual voice assistance for safe and hands-free navigation.
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3D Audio Immersion
- Adaptive audio environment based on user behavior, such as heartbeat sounds for speed warnings or forest sounds during scenic rides.
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Safety Notifications
- Alerts cyclists about dangers ahead and hazards detected by other users on the same route.
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Health Monitoring
- Tracks vital signs and provides emergency notifications in case of abnormal readings.
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Cultural Integration
- Highlights eco-friendly routes and culturally significant landmarks.
The architecture integrates:
- AI-based route optimization engines.
- Machine learning models for hazard detection using real-time sensor data.
- APIs for real-time weather and navigation data.
- Adaptive audio technology for immersive cycling experiences.
- Python: AI and backend development.
- JavaScript: Frontend and mobile app development.
- React Native: For building cross-platform mobile applications.
- Node.js: Backend framework.
- TensorFlow: For training and deploying ML models.
- OpenCV: For real-time hazard analysis.
- Google Maps API: For route planning and navigation.
- OpenWeatherMap: For real-time weather updates.
- Kaggle Datasets: For training AI models.
- MongoDB: For user data and app metadata storage.
- Arduino Uno: Microcontroller used to build the IoT device.
- Sensors: Heart rate sensor
- Communication Module: Bluetooth module (e.g., HC-05) for transmitting data to the mobile app.
- AI algorithms dynamically calculate the most efficient and safe routes.
- Factors like road conditions, real-time weather, and user preferences are considered.
- Real-time mobile phone sensor data (accelerometer, gyroscope, and GPS) is fed into a custom-trained ML model.
- The model identifies potential hazards such as dangerous road bends, sandy roads, or steep slopes.
- Cyclists are alerted via voice notifications and 3D adaptive audio to ensure proactive safety measures.
- An algorithm analyzes sensor data from nearby cyclists to detect and relay alerts about road dangers.
- Alerts are shared with cyclists further behind to prevent accidents.
- Design a system that offers real-time voice guidance for cyclists.
- Ensure the system accurately identifies and announces landmarks.
- Integrate GPS and mapping technologies for precise navigation.
- Design a system that monitor cyclists' health metrics and alerts.
- Build an IoT device to monitor cyclists' health metrics.
- Utilize machine learning algorithms to detect deviations from user baseline health data.
- Create options for both solo rides and group navigation.
- Develop a feature to synchronize rides within a team, allowing shared experiences.
- Ensure the system can handle real-time updates for multiple users on different routes.
- Implement multi-language options for both navigation and landmark descriptions.
- Localize the application for different languages spoken by tourists.
- Ensure translations are culturally appropriate and accurate.
- Routes are designed to include eco-friendly paths and culturally significant landmarks, fostering sustainable tourism.
EcoCycle Explorer combines cutting-edge AI and ML technologies with real-time sensor data to ensure safe, immersive, and sustainable bicycle tourism. Its innovative route optimization, hazard detection system and adaptive audio features set a new standard for eco-friendly travel experiences.