Week 6 Report #

Presentation #

Project Overview #

This week, our primary focus was on polishing, packaging our prototypes, and crafting a final presentation to showcase our project. Our goal is to present SafeShelf in the best possible light, outlining the key features, use cases, and benefits to potential users.

Weekly Progress Report #

Our team accomplished the following:

• Bug Fixes and Enhancements: We addressed several critical bugs, including issues related to the connection between the backend and frontend, ensuring seamless integration and functionality. Additionally, we fixed bugs related to the external API, specifically in parsing JSON files and handling expiration dates.
• ML Integration: Initiated the connection of the machine learning part with the backend, making significant progress in integrating AI-driven features for personalized recipe suggestions and expiration date predictions.
• Functionality Testing: Conducted extensive testing to ensure all MVP functionalities are working correctly, excluding the ML part which is still under development. Users can now test the core features of the application.
• CI/CD Pipeline: Planned the implementation of a CI/CD pipeline to automate the deployment process, ensuring efficient and reliable updates to the application.

Challenges & Solutions #

Challenges:

1. Backend and Frontend Integration:

   • Issue: Encountered bugs while connecting the backend and frontend components.
   • Solution: Conducted thorough debugging sessions and collaborated closely to resolve integration issues, ensuring smooth communication between the two parts.

2. External API Handling:

   • Issue: Faced problems with parsing JSON files and handling expiration date data from external APIs.
   • Solution: Implemented robust parsing mechanisms and improved data handling processes to ensure accurate and reliable data retrieval.

3. ML Integration:

   • Issue: Complexity in integrating the ML part with the backend.
   • Solution: Began the integration process, laying the groundwork for seamless incorporation of AI features. This integration is ongoing and will be a focus in the coming weeks.

Conclusions & Next Steps #

Conclusions:

• Successfully fixed critical bugs, enhancing the stability and functionality of the application.
• Progressed significantly in integrating the ML part with the backend, though further work is needed to fully implement AI-driven features.
• Improved the handling of external API data, ensuring accurate and reliable information processing.

Next Steps:

1. Complete ML Integration:

   • Finalize the connection of the ML part with the backend, ensuring all AI-driven features are fully functional.

2. Implement CI/CD Pipeline:

   • Develop and deploy a CI/CD pipeline to automate the deployment process, facilitating efficient updates and maintenance.

3. End-to-End Testing:

   • Conduct comprehensive end-to-end testing to ensure all components of the application work seamlessly together.

4. Refinement and Optimization:

   • Continue refining and optimizing the application based on user feedback and testing results, focusing on performance enhancements and UI improvements.

Summary: This week, we fixed bugs during the backend and frontend connection, started integrating the ML part with the backend, and ensured that everything excluding the ML part works and can be tested. We also fixed bugs related to the external API, improving JSON file handling and parsing expiration dates. Our next steps include completing the ML integration, implementing a CI/CD pipeline, and conducting end-to-end testing to ensure a seamless and robust final product.

Presentation #