Focus fit AI: study space ,tuned to you

Inspiration

Students have different study preferences, yet most study advice assumes that the same environment works for everyone. We wanted to create a simple tool that helps students build a study space that fits their individual needs.

What it does

FocusFit AI is a personalized study-space assistant. It asks students about their study task, preferred sound environment, lighting preferences, focus duration, and estimated room noise. Based on their answers, it generates a practical study plan with recommendations for sound, lighting, desk organization, and study sessions.

How we built it

We built a responsive web prototype using HTML, CSS, and JavaScript. The interface collects user preferences, and a transparent rule-based recommendation system generates personalized suggestions. The prototype also explains why each recommendation was selected and allows users to copy their study plan.

What makes it different

Instead of giving everyone the same study advice, FocusFit AI adapts its recommendations to the student's answers. It also explains the reasoning behind its suggestions, making the experience more transparent and easier to personalize.

Challenges we faced

One challenge was turning different study preferences into clear and actionable recommendations. We addressed this by organizing the inputs into categories and creating rules that connect each choice to relevant suggestions.

What we learned

We learned how to turn a real student problem into an interactive web prototype, design a user-friendly interface, and build a recommendation system that responds to user input.

What's next

Future improvements could include optional sound-level measurement, student feedback to improve recommendations, and testing the prototype with students to evaluate its usefulness.