I developed an AI-powered tetanus risk detection device designed to analyze wound images and help identify whether an injury may require further medical attention. The idea originated from a simple problem: many people struggle to judge the seriousness of a wound or understand when there may be a risk of tetanus, especially when immediate medical guidance is not easily accessible. I wanted to explore whether technology could provide an early, accessible layer of support by combining image-based wound analysis with a simple user-facing system.
I worked on the project from the ground up, including researching tetanus and wound characteristics, developing and refining the detection approach, building the prototype, conducting testing, and improving the system based on feedback and real-world use. The project was tested by over 150 users and gradually evolved from an initial prototype into a more complete healthcare-focused solution. Alongside the technical development, I also wrote a research paper documenting the problem, methodology, development process, testing, results, limitations, and potential future improvements of the system.
The project has received recognition across several national and international innovation and research competitions. It received a Gold Award at the CREST Awards, a Silver Award at the International Greenwich Olympiad, and a Silver Award at INSEF. It was also selected as a Top 200 semi-finalist at NSRI GRC 2025 and reached the Top 200 in Vivo Ignite out of more than 39,000 applicants. These experiences allowed me to present the project to different judges, researchers, and innovation panels while continuously improving both the technical system and the way I communicated its real-world impact.
More than the awards, this project became an important introduction for me to building technology around an actual human problem. It taught me how to move beyond simply creating a working prototype and instead think about research, experimentation, usability, reliability, limitations, and impact. It remains one of my most meaningful projects because it brought together my interests in artificial intelligence, engineering, healthcare, and using technology to solve problems that can directly affect people's lives.