Inspiration

The manufacturing industry has produce automobiles, furniture, computers, and many more. It is now time to revolutionize and create something that will help the environment. Wildfires are burning millions of acres in California, Oregon, and other parts of the western US alone. Globally those acres are even more. Forest and wildlife are being destroyed by these fires. We believe that our mother nature is too important to do nothing about it. That is why we developed the Drone FI-PRE for the fire departments and their team.

What it does

The Drone Fi-Pre is designed to help prevent wildfires in a specific area utilizing infrared cameras and electronic weathering sensors. With triangulation between the deployed drones, we are able to identify the location of the wildfire origins and predict the path of travel. Drone Fi-Pre serves as one of the first defenses towards wildfires by aiding and coordinating the user to take action to prevent disasters.As well with the use of AI it is able to predict the evolution of the fire.

How we built it

The Drone Fi-Pre is modeled after the DJI MAVIC PRO since it meets our design requirements for an HD Camera and a FLIR Duo Pro R - Infrared Camera. This product also includes a base and the docking station that consists of: • Ambient Weather WS-2902C Smart Weather Station • Solar Panels for self-sufficiency • Lithium Battery for emergencies • AR-Tag for precision landing.

After deployment, it scans the region while heading to the next docking location to maximize range and efficiency when there has been no detection of wildfire. However, when conditions are met it will follow a different sequence. The data will be sent back to the drone’s original deployed station. The station will then relay the information to the other drones to find the exact coordinates of the potential fire hazards and then activate the ambient weather station to get real-time data. Once all necessary information is gathered, an AI will process the information and transfer it to the user. The user should receive real-time visuals, AI analysis, and ambient parameters as indicated in the user interface section.

Challenges we ran into

We ran into a few challenges. One challenge was designing the entire system and learning new verbiage we were not familiar with. We had a problem delineating the scope of our system and defining what ideas were feasible to implement given current advances in technology. Since time was limited, we were constrained on how extensive our proposal had to be.

Accomplishments that we're proud of

It was everyone's first time participating in a Hackathon and we are quite proud of the progress we have made.

What we learned

We learned to see the bigger picture. It was essential to think about specific technology with our end goal in mind. Despite being in different time zones, we learned how to better coordinate as a team virtually and maximize our time and efficiency due to time restraints.

What's next for T14_Drone Fi-Pre

We would like to implement more features and produce a prototype that considers our challenges such as damages/obstacles by wildlife, potential wildlife disturbances, limited range, high winds, accessibility/cost, and other unforeseen conditions.

Roles

Project Manager - Samantha Parreno Designer - Ulysses Ortegon Research and Development - Diego Chachayma Business/Marketing - Gabriela Portillo

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