Biotech Futures
Challenge

Task: To innovate and pitch a solution that addresses challenges in biotechnology.

Project

Our team investigated the existing technological aids provided to the visually impaired community. We noticed gaps in the number of devices available for outdoor navigation assistance and decided to focus on roadside environments. Our final device was a pair of glasses with camera vision and obstacle detection functionalities as a quick and trainable alternative.

Some Features:

• Multiple camera and dual speaker systems (visual input and audio output)

(3D modelling and printing done by another student M.S.)

• Object detection with YOLOv4

YOLOv4 is an open source object detection algorithm. It was implemented using the OpenCV library in Python with given weights. The obstacle and its distance from a camera can be identified. (The image was used for demo purposes - hence, measurements lack precision.)

• Simple mobile interface

The mobile application connected to the device and allowed users to change settings (e.g. output language) and recorded object-detection history. (Only designed, not deployed.)

In October, we attended the Biotech Symposium, where we pitched our solution. A report, a poster, and a presentation were also submitted to the Challenge.

Conclusion

Overall, I gained lots of practical experience in working with a team to develop a feasible prototype and convincing pitch. The project relied heavily on task coordination, setting deadlines, and frequent communication between team members to ensure that all of its aspects were cohesive. I also learned about object detection/classification and current research in tech-based aids.