The increase of wildfire scales in 2020 and the rapid growth of a fire outbreak has proven that fire management systems lack efficiency in noticing fires, coordinating as a national team to mitigate the risk 🚒 and ensuring enough units are deployed. 🧑🏼‍🚒 As a result, we attempted to create a management system for the former. 🔥

What it does

Using real time data of the fire severity, FERM can suggest how many units and resources then automate its deployment once confirmed to immediately mitigate the fire. FERM also has a map view of the fire location and location of the respective units (trucks, helicopters, ambulance, etc) moving.

How we built it

We used 💿SQL 💿to store user authentication information and fire description (location, scale, region, latitude, longitude) which should automatically updates the 🗺three.js map🗺 then the web application using 🧩HTML/ CSS🧩 that succinctly displays the info for users and personnel.

Challenges we ran into

Gluing everything together! Since we were using three independent systems, it was difficult making them all work synchronously. Especially with a few hiccups in integrating the CockroachDB to the interactive three.js map - we were happy to have finished it either way.

Accomplishments that we're proud of

Applying our respective skillsets to our individual tasks and pouring it into a collective effort for this project. It was pretty cool to see how everything panned out since one worked on the CockroachDB, one in creating the 3D map using webGL and three.js, one on the frontend stuff, and lastly one on the design stuff - it's quite nice to have a finished product.

What we learned

➡️ Although an integration failed, there's always plan B! We ended up using SQL in place of Cockroach since it somehow won't let us create tables and insert mock data. ➡️ Communicating - we are all in different timezones so just trusting each other in finishing our tasks was a major plus

What's next for FERM

🎯 Figuring out how to use CockroachDB for better performance (especially with handling large datasets) in place of SQL 🎯 Integrating Twilio API for automatic messaging on real time updates

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