Inspiration

Each year, there are about a million car collisions with deers, which can be deadly for the wildlife and even the passengers. Not just that, annually more than 2 million animal attacks are reported in the United States alone. To solve that, we came up with WildAware.

What it does

WildAware is a platform-independent application that recognizes animals from images captured by an IoT-based setup and also allows its users to log animal sightings around forest regions. The users can check for animal sightings near them and take precautions accordingly.

How we built it

Front-end: Flutter, Dart
Back-end: Python-Flask
Animal Identification: AWS Rekognition
Hardware: NodeMCU, External Webcam

Challenges we ran into

Running the flutter app locally was a challenge which we overcame with a lot of configurations. Another challenge was calling the APIs with Flutter because of the asynchronous nature of APIs.

Accomplishments that we're proud of

Configuring AWS rekognition to identify wild animals along with displaying them in a cross platform mobile application is an accomplishment we are proud of.

What we learned

We learnt flutter and AWS Rekognition over the weekend.

What's next for WildAware

Having a map with all the sightings and filter them based on the animal. Notifications when the user travels to a location with a recent wild animal sighting.

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