We saw that amber alerts and wanted suspects have been constantly increasing from the past year. We saw a need for innovation and a way reduce these numbers and find those missing and wanted suspects and to take them back to where they belong. Instead of having a manhunt, we use our community as a way to stay informed and help make the world a safer and better place for everyone.

What it does

PinPoint is an application that enables users all around the world to take pictures missing or wanted suspects. The application that you are using is connected to a server for your region that contains missing and wanted people’s image’s in your area. When an Amber alert or wanted person case occurs, pictures of the missing person are scraped off of top news sites and are used to train a model for comparing uploaded images with. What this ensures is that when a case like this occurs images are trained as fast as possible. When you upload an image of a suspect that you think is missing or wanted our machine learning back-end scans the image with the actual picture of the suspect and identifies if the person in both pictures match. If the image is matched the location will be Pinpointed and will sent to the main server where immediate help will be coming. What this allows for is safer and faster means of finding those who are possible suspects. Our login system verifies the user who has Pinpointed someone and the email that it is registered with is safely secure in a database and a certification will be provided to that email address if the suspect is found safely as graditution for your assistance. Once you register the app will keep you logged in so images can be uploaded as quickly as possible and the missing or wanted person is pinpointed.

How I built it

Our login system uses fire base user authentication in order to keep emails and passwords secure. What this allows for is not having our own database but being backed up by a well known and very trusted company, Google. When you click on the Missing section or the wanted section, you are given an option to upload the image and once you do that you will click the scan image button and the face recognition will check to see if the actual image of the missing person matches the picture that was just uploaded. The back end of the app is what is doing all the hard work. As our Back end, we have our own private Flask web-server that takes the JSON from the face recognition and sends it to the android application and if the face is matched you will get a screen which tells you that the person has matched.

Challenges I ran into

Configuring post and get requests and getting it to work with the android application. And implementing the python face_recognition library into the web-server.

Accomplishments that I'm proud of

Getting post and get requests to work and setting up our flask web server to work with python face_detection library.

What I learned

We learned how to setup a flask web server and how to connect it to an api. We learned to use the face_detection library and how to implement it to our application. We also learned how to use firebase for our user-authentication.

What's next for PinPoint

We want to create add license tracking with machine learning and text detection. We also want to heavily improve our location system and improve our face recognition by implementing larger databases for model training.

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