The latest articles on DEV Community by Jun-Zhe Lai (@jlai). https://dev.to/jlai https://media2.dev.to/dynamic/image/width=90,height=90,fit=cover,gravity=auto,format=auto/https:%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Fuser%2Fprofile_image%2F390148%2Fccbf9b87-3351-4719-823e-71c9bf59a5fd.jpeg https://dev.to/jlai en Jun-Zhe Lai Wed, 20 May 2020 06:51:21 +0000 https://dev.to/jlai/watchyourfac-es-1bjc https://dev.to/jlai/watchyourfac-es-1bjc <h2> My Final Project </h2> <p>Wasn't our final project but we developed an edge based face recognition system. You could upload a photo of a person of interest and train a face recognition model with it. This model was then distributed to our edge devices (a Rapsberry Pie with a webcam). </p> <p>Unlike most face recognition systems we leveraged fog computing, meaning that the face recognition happened on the edge device itself. This means that data was being transferred to the backend only in case a match was found, thus providing better privacy.</p> <p>We also added things like immutable logs and four-eyes principle to every action in order to facilitate accountability.</p> <h2> Demo Link </h2> <p><a href="https://watchyourfac.es/">https://watchyourfac.es/</a></p> <h2> Link to Code </h2> <p><a href="https://github.com/pwillmann/watch-your-face">https://github.com/pwillmann/watch-your-face</a> </p> <h2> How I built it (what's the stack? did I run into issues or discover something new along the way?) </h2> <p>Authentication: auth0<br> Backend: AWS IoT, DynamoDB, Lambda </p> <h2> Additional Thoughts / Feelings / Stories </h2> devgrad2020 octograd2020