A design for an electronic capsule capable of recording data from an IR thermal camera and transmitting it wirelessly to another transceiver.

This project introduces the first all-in-one scar protector patch that combines microneedling, hydrocolloid healing, vitamin C delivery, and UV protection into a single, easy-to-use solution. Designed for individuals affected by long-term scarring from surgery, injury, or acne, the patch supports skin regeneration, reduces discoloration, and shields healing skin from sun damage. By integrating clinically supported therapies into a seamless patch format, our scar protector improves both aesthetic and medical outcomes, restoring skin health and boosting confidence.

For EN.601.290 (User Interfaces & Mobile Applications), our group developed a mobile app that allows users to log their clothing into a virtual closet, customize and save outfits, and view their closet at a glance on their phones. We hope this project will foster creativity and experimentation, encourage users to buy less and wear more of what they have, and have fun with fashion without the need for any special purchases beyond what they already own.

This project focuses on real-time gesture-based motion control of the Crazyflie 2.1 nano quadcopter using a machine learning model deployed on the GAP8 AI deck. The system uses camera-based hand gesture recognition, where x-y coordinates of tracked hand movements are extracted using MediaPipe and processed as input to a lightweight neural network.
The gesture recognition model is trained offline using time-series data of hand positions captured during predefined motions—such as upward swipes for ascending, downward gestures for descending, or lateral movements for turning. This data is used to train a neural network capable of classifying dynamic gestures in real-time. Once trained, the model is quantized and deployed to the ultra-low-power GAP8 processor.
The project demonstrates the feasibility of vision-based embedded ML on resource-constrained platforms. It highlights the integration of real-time gesture classification, camera-based input processing, and embedded deployment using the GAPflow toolchain, showcasing skills in time-series vision data handling, model optimization, and real-time system design for edge AI applications in robotics.