CycleCare – AI-Powered Menstrual Health Platform
Inspiration
I wanted to build a project that solves a real-world problem rather than just demonstrating technical concepts. Menstrual health is often overlooked, and many existing applications focus only on period tracking. I wanted to create a platform that combines cycle tracking, health insights, nutrition, symptom monitoring, and AI assistance into a single application.
What it does
CycleCare is an AI-powered menstrual health platform that helps users manage their menstrual health through:
- Period and cycle tracking
- Next period and fertile window prediction
- Symptom and mood logging
- Nutrition tracking
- Personal health journal
- AI-powered health assistant
- Personalized health reports
- Secure user authentication and dashboard
The goal is to provide users with meaningful insights instead of simply storing cycle dates.
How I built it
I developed CycleCare using Java Spring Boot as the backend and Thymeleaf for the frontend. The application uses Spring Security for authentication, Spring Data JPA with Hibernate for database operations, and MySQL for data storage.
For AI-powered assistance and report generation, I integrated the Gemini API. The frontend was built using HTML, CSS, Bootstrap, and JavaScript to provide a clean and responsive user experience.
Challenges I faced
One of the biggest challenges was designing a database that could efficiently manage cycle records, symptoms, nutrition logs, journals, and user information.
Integrating AI while maintaining fast response times also required careful handling of API requests and user interactions. Another challenge was creating a user-friendly interface that remained simple despite offering multiple features.
Deploying the application securely and configuring the production environment was another valuable learning experience.
What I learned
This project helped me strengthen my knowledge of Spring Boot, Spring Security, REST APIs, Hibernate, MySQL, frontend development, and AI integration.
Beyond the technical skills, I learned how to design software around real user needs and how different technologies can work together to build a complete full-stack application.
Future Improvements
In the future, I plan to add machine learning-based cycle prediction, wearable device integration, medication reminders, multilingual support, downloadable health reports, and a mobile application to make CycleCare even more useful.
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