AI Food Scanner
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Project Overview
This project leverages advanced AI technology to help users effortlessly track their meals by simply snapping a photo. The AI analyzes the image to break down the meal into calories, nutrients, and other vital dietary information. This innovative approach empowers users to make healthier eating decisions without the hassle of manual logging.
Role and Responsibilities
I was responsible for designing the user interface (UI) and crafting a smooth user experience (UX) that makes meal tracking simple and engaging. My focus was on creating intuitive workflows that guide users through snapping their meal, viewing detailed nutritional breakdowns, and tracking progress over time. I collaborated with the AI development team to ensure seamless integration of visual elements with backend analytics.
Design Process
The design process began with researching user pain points in existing meal tracking apps. Based on findings, I developed user personas and mapped out key user journeys. Wireframes and prototypes emphasized ease of use and clarity of nutritional data presentation. The visual design adopted a clean, fresh aesthetic to reflect health and wellness themes. Interactive prototypes were tested with real users to gather feedback and refine usability.
Challenges and Solutions
One challenge was presenting complex nutritional data in a way that is accessible and non-intimidating. To solve this, I designed visual cues like color-coded nutrient bars and simplified summary cards. Another challenge was ensuring quick and effortless meal snapping without multiple steps, which was addressed by streamlining the capture and analysis flow.
Final Outcome
The final product is a user-friendly, visually appealing app that encourages healthy habits by making meal tracking quick and insightful. User testing showed high satisfaction with the ease of use and clarity of information. The project successfully integrated AI capabilities into an engaging UX, helping users make informed dietary choices.