DormSafe

DormSafe uses intelligent machine learning to scan roommates faces on easy to use mobile applications when entering their dorms. Roommates can view entry logs for their dorm.

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Inspiration

With our venture into college fast approaching, we thought of some challenges that we might face upon arriving. One of the largest concerns that students face are regarding Dorms. Brainstorming more, we realized that Dorms are not as secure as most want to be.

What it does

Rather than relying on word of mouth or ID cards, DormSafe will utilize facial recognition keep track of students that are coming in and entering dorms. On top of having an understanding of the whereabouts of each student in the dorm, students will also be able to unlock the dorm simply by using our application or integrated cameras.

How we built it

We used flutter to develop an app for students in order to unlock their Dorm Rooms personally. The image that they supply through this mobile application will be sent to our firebase realtime database to then be compared to a database of all images that were used to calibrate the system. This comparison is a server-side comparison that will utilize DeepFace's ML model. If a match shows up, the firebase will notify the Arduino to unlock the door for the student. The information about the lock status of the door and wether or not the student is in the dorm will be sent to a web app made using flutter for dorm administrators to use.

Challenges we ran into

Integrating device with Firebase

Accomplishments that we're proud of

The integration between all of the devices was finally achieved, as well as the speed at which the model operates.

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