We can reduce elephant poaching by deploying an AI trained acoustic sensor that distinguishes between heavy elephant hunting guns and small guns, allowing law enforcement units to accurately identify the level of threat and deploy response teams accordingly to high probability poaching events.
Week 1: Figure out materials needed, narrow down what to detect (specific guns, sounds, etc.)
Week 2: Researching how to implement the AI model into a sensor, finding datasets to use (elephant vocalizations, shotguns, rifles, etc.), and figuring out how to extract/isolate sound
Week 3: Code the AI and train it using the data we have, and figure out how to use the sensor
Week 4: Connect the AI model and the sensor so they can relay info to each other, and perform a few test runs on sounds to see if the AI model can correctly detect what type of sound it is.
Week 5: Add a threat indicator (1-10) to the model so it can detect how much of a threat the sound it receives is.
Week 6: Trial and error, keep testing to get AI to be as accurate as possible.
Week 7: Wrapping up, documentation, make progress on presentation, poster
Week 8: Presentation is priority + poster