FloodSafeMyanmar: A Flood Safety Web Application
Inspiration
The increasing frequency and severity of floods in Myanmar, largely driven by climate change and unpredictable weather patterns, has heightened the need for reliable disaster response tools. Flooding impacts lives, displacing communities and damaging essential infrastructure. In Myanmar, where real-time information and quick evacuation can mean the difference between safety and catastrophe, there’s a pressing need for a dedicated, accessible platform to provide life-saving updates and resources. This inspired me to develop FloodSafeMyanmar, a web application designed to help people stay informed, prepare for emergencies, and find resources quickly during flood situations.
What it does
FloodSafeMyanmar provides users with real-time updates on flood alerts, weather forecasts, and evacuation routes. It features an interactive map that highlights flooded zones, safe shelters, and emergency resources, all optimized for quick, mobile-friendly access. Users can also opt to receive push notifications and SMS alerts about rising water levels and local emergency guidelines. The app also has a community reporting feature where residents can contribute real-time flood data, allowing users to stay informed based on both official data and crowdsourced reports.
How I built it
I developed FloodSafeMyanmar using a combination of React for the front end and Node.js with Express for the back end. MongoDB was used for storing user data, flood reports, and location-based resources. For the real-time flood and weather data, I integrated APIs like the OpenWeather API and Google Maps API for interactive mapping. The SMS alert system leverages Twilio’s API, ensuring timely notifications to users, even if they don’t have the app open. Additionally, I used Socket.io to provide real-time updates to users as new reports come in from both official sources and community reports.
Challenges I ran into
One of the biggest challenges was ensuring that the app could handle a high volume of real-time data from multiple sources without slowing down or crashing. Processing, mapping, and updating flood zones in real time is resource-intensive, especially given the potential unpredictability of user-contributed data. Another challenge was the connectivity issue common during floods, which made it necessary to design the app to work as smoothly as possible even in areas with low bandwidth. Ensuring data accuracy from both official sources and community reports was also crucial and challenging, as inaccuracies could lead to misinformation.
Accomplishments that I'm proud of
I’m proud of creating a platform that can genuinely help protect communities in Myanmar during floods. The interactive map feature was particularly challenging, but seeing it work in real time was incredibly rewarding. I’m also proud of integrating community reporting in a way that can bridge the gap between official data and on-the-ground realities, which helps make the app more inclusive and informative. Additionally, overcoming the technical challenges around ensuring quick loading times and smooth operation even with high data loads was a rewarding accomplishment.
What I learned
Developing FloodSafeMyanmar taught me about the intricacies of handling real-time, high-stakes data in an accessible, user-friendly format. I learned a lot about optimizing data flow to maintain app speed and reliability, which is crucial for emergency applications. Additionally, I gained insight into the importance of accessibility and inclusivity in design, especially for emergency tools that people from diverse backgrounds and digital literacy levels will use. This experience also deepened my understanding of API integration and the value of community reporting in enhancing data richness and reliability.
By Shreyash Srivastva
Built With
- backend
- deep-learning
- forecast.io
- frontend
- github
- json
- jupyter
- machine-learning
- node.js
- open
- python
- requests
- streamlit
- tensorflow
- twilio
- vscode
- weather
