'Dadelo' means wildfire in Nepali. In Nepal, there are lots of cases of uncontrolled wildfires.

Considerations and goals

1. Report Fire: For an app that is based on spotting fires around you, reporting fire using it is a must. Users should be able to report a fire near them easily.
2. Verify Fire: Simply reporting a fire can be a mere scam. Hence, people near that location should be able to verify the fire and give an extra layer of confirmation. On top of it, for more accuracy, we also use (AWS Image Recognition or Google Cloud ML kit) to verify the image for the presence of fire. Each image verified by ML receives a special verified ticker on the news feed. In this way, we get 2 layers of verification.
3. Real-time Notification: We must notify users about fires near their location for their safety. Real-time notification helps users to stay alert and emergency services to take necessary actions faster and hence it can be very efficient.
4. Track and Visualize Fire: Although getting real-time information about the fire is done mostly through crowdsourcing, the application should be able to use authenticated data provided by NASA to keep track of fire across the world for a certain amount of time and provide some relevant information.
5. Personalized and Voice Support: Finding and understanding the problem is one thing but we feel that making an impact with our product is absolutely necessary. So our app should be able to provide support to the people in need. Tips on what should be done during such situations can be very useful.
6. Emergency social networking: Our goal is to make this an important informative aspect of the app. Finding a safe spot, knowing the status of the people near affected areas and their location are the priorities of emergency social networking.

Features / Future Capabilities

• Crowdsourcing: Users can upload fire alert for others to view
• Verification of the submitted fire alert by at least 5 members with image recognition probability percentage more than 90 using (AWS Image Recognition or Google Cloud’s ML Kit) verification enables fire prevention mode
• Sending push notifications to affected users on the area based on the region about the necessary steps to take to prevent further damage after fire prevention mode has been activated.
• Prediction of the direction of fire from its recent movement and weather conditions. Providing safe paths and directions analyzing the region/vegetation and other conditions.
• Tracking past wildfires, the number of affected people and other information from NASA's data and prediction of future vulnerable places for wildfires and provide suggestions to people in order to prepare in case of a wildfire.
• Emergency safe area protocol: After fire prevention mode has been activated, users can mark themselves and an area safe by using a single button. Other users on the area will be sent a push notification about the safe area around them.
• Recent and ongoing fire tracking from webApp, sorted by earliest and nearest first

Project Diagrams

Fig: DFD Diagram

Fig: Gain Diagram

Project Impacts And Scalability

On completion, this app will have major impacts on spotting and controlling fires. It will also support people near the affected areas. For someone who wants to know about recent fire, this app’s newsfeed will provide information on them for 1 month.

The idea and tools are implemented thinking about the scalability of the project. Although its major focus is on wildfires, it can also be implemented in more general situations. The tools used are powerful and supports considerable change in size and features.

Tools And Resources Used

• Clojure
• VueJS
• React Native
• Figma
• Google Maps JavaScript API
• Amazon Web Services
• Google Cloud Platform

Conclusion

Throughout history, the wildfire has always been around. Although the causes of wildfire are complex, the effects are unbearable. Our app helps to spot the wildfires, notify relevant personnel and help people guide themselves to safety. On implementation, its scope and also its impact will be huge. Hence, our team “JHOL MOMO” presents you “Dadelo”.

Appendix

Fig: NASA wildfire data sample

Fig: API implementation

Fig: WebApp flow

Fig: Mobile App flow

GItLab repositories: https://gitlab.com/stop-that-fire