Angel's Eye

Vision security solutions aimed at the automated early detection of gun violence and police/civilian notification

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Inspiration

In the US in 2015, 372 mass shootings, killing 475 people and wounding 1,870. 64 school shootings. In total, approximately 13,286 people were killed in the US by firearms and 26,819 people were injured, excluding suicide. Now more than ever, gun violence is on the rise. Political solutions take time, but the need for a solution is urgent. After the most recent tragedies, standing on the side lines is no longer an option.

What it does

Enter Angel’s Eye Inc. We offer a suite of security solutions that leverage vision and communication technology aimed at the automated early detection of gun violence and law enforcement notification. Seconds save lives. Count the ticks of a clock, the number of thoughts, and the number of lives separating the point in time when a gun is unconcealed to the point when someone is able to notify the police. Now imagine a world where that count is zero; where the police is instantaneously notified as soon as the presence of a gun is detected in public, and where the time taken to apprehend the assailant is reduced since his/her identity is immediately known. Picture the robbing of a convenience store. The shop owner terrified for his life attempting to find an opportunity to set off the silent alarms. With Angel’s Eye, the police would be on their way as soon as the gun is revealed to the shop owner. The gun being raised IS the call to 911. Here’s the walkthrough: The gun is raised at the shop owner. The cameras in the store, whether it would be a mobile camera running an android app or a webcam running a python desktop app, sends the image to the AWS server where Google’s Vision API will determine whether a firearm is present. That returns true and triggers a Twilio API call where a text message will be sent to 911 with the time, location, and images of the situation. Meanwhile, all bystanders in the vicinity of the store will be pushed a notification to warn them about the nearby incident. In addition, everyone who has the desktop app will be able to view a map and see, in real time, areas where incidents are occurring and should be avoided.

How we built it

The back-end was built with AWS, and firebase. The mobile app was built on Android and Google maps API. The desktop app was written in Python and utilized OpenCV. Google's Vision API was used for object detection and Twilio was used to send automated text messages.

Challenges we ran into

Communication between the desktop app and the server as well as long lines for food

Accomplishments that we're proud of

We feel that this hack is a proof of concept for something that may actually be of practical use to society.

What we learned

We learned to use the Google Vision API

What's next for Angel's Eye

Should this be scaled, paired with the versatility of the solution, Angel’s Eye could facilitate the nation in fostering a long-lasting sense of security, or play a small part in the potential saving of lives.

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