| Group |
2021-21 |
Status |
completed |
| Title |
Sentinel |
| Supervisor |
Kash Khorasani |
| Description |
Description:
Wildfires are a real-life problem that is affecting countries all over the world. This year
has seen horrible wildfires that caused a great amount of devastation. Currently, wildfire
suppression is conducted via wildfire fighting teams only after a fire has been reported
and scouted. Our goal to create an all-terrain autonomous vehicle (ATAV) to traverse
wooded areas and then suppress fires. We will be designing a to scale vehicle, to travel to
predetermined locations, detect early wildfires, and suppress them. While communicating
data in real time to a base station.
Deliverable
Our project will integrate new control approaches based on deep reinforcement learning
(and other machine learning approaches) with a controller, and other visual sensors, to
simulate our proposed system and deliver an ATAV for fire detection, monitoring and
suppression. |
| Requirement |
Microcontrollers
Python
Computer Vision
Neural Networks |
| Tools |
Test Equipment:
Multimeter
Various hand tools
Software:
Wildfire Simulation Software
Multiphysics Engineering Simulation Software
Matlab |
| Number of Students |
6 |
| Students |
Ryan Hans, David Sorin, Dilara Omeroglu, James Francia, Tarek El Dick, Mohamed ElSagh |
| Comments: |
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| Links: |
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