Project details:

Technologies: Flutter, Node.js, React, MongoDB, Flask, Google Cloud AI

Project Goal: Our client envisioned a fitness app that helps users calculate calories and track their nutritional intake. The idea was to allow users to take photos of their meals, ask questions about their diet, and receive detailed nutritional information and suggestions. We chose Flutter for the technology stack to ensure cross-platform compatibility, with Flask and MongoDB for the backend. The development was divided into iterations, each consisting of weekly sprints. We focused heavily on improving AI responses (prompt engineering) and enhancing the UX & UI. The total development time, including all iterations and updates, was 4 months.

Stage 1 - Improving Idea Planning and Finding Good References

Since the concept aimed to offer an innovative way to track calories using AI, we conducted extensive research on successful fitness and nutrition apps like MyFitnessPal and Lose It! to create an intuitive design. We also sought out references for scanning and image recognition features to create a seamless user experience, making users feel that the app effortlessly understands their dietary needs by analyzing photos of their meals.

Stage 2 - Technical Demo, Implementing AI Functionalities

The next stage was to prove the technical feasibility of the idea. After conducting research, we arrived at the following solution:

1. Take a Photo: Users capture images of their meals using the app.

2. Analyze It: Utilize Google Cloud AI to recognize food items in the image and estimate portion sizes.

3. Calculate Calories: Cross-reference the identified food items with a nutritional database to calculate total calorie intake.

4. Provide Feedback: Display the nutritional information and offer suggestions based on the user's dietary goals.

This approach effectively integrated AI image recognition and nutritional data to provide accurate calorie calculations.

Stage 3 - Developing the Mobile App Using Flutter

We began developing the mobile app using Flutter:

• Design: Created an intuitive UI that allows users to easily navigate through the app, capture meal photos, and view their nutritional information.

• Functionality: Implemented features such as user authentication, profile setup, and goal tracking.

• Challenges: Faced challenges with integrating real-time image processing and ensuring accurate food recognition, but we managed to resolve these issues with optimized algorithms.

Stage 4 - Mobile App Functionality Improvement and Preparing for Launch

In the final stage, we focused on refining the app's functionality and preparing for launch:

• AI Optimization: Improved the accuracy of food recognition and calorie calculations through machine learning.

• UX Enhancements: Enhanced the user interface based on feedback from beta testers to make the app more engaging and user-friendly.

• Testing: Conducted thorough testing to ensure the app performs well across different devices and meets all app store guidelines.