Sri Lanka is one of the top Tea manufacturers in the world and it holds the rank No 1 in the black tea exporter category throughout the past 2 decades. The tea industry contributes more than 5% to the national GDP. The tea manufacturing process is an interlinked process and the final output of the tea production depends entirely on the quality of green leaves received from Green Tea dealers to the tea factory.
Unfortunately, a significant amount (10% – 40%) of total leaves get damaged during the plucking, collection, packing and transportation process. To mitigate the issue of receiving poor leaves to the factory, we have decided to identify tea leaves using AI with an image processing method during the initiation phase of this challenge. Under the Machine Learning life cycle following phases have been completed successfully and we will do further improvements during the 2nd phase of the project.
Remaining steps will be started from the model which we have already built during the 1st phase and embed the model to a mobile application , so that users could operate the ML based classification model without any inconvenience.
The major goals of phase 2 of the project are:
- Develop mobile applications for the classification of Tea qualities, based on main tea regions.
- Using edge computing and cloud development for mobile applications.
1. Develop a portable device solution.
2. Integrate the mobile device solution with the trained models.
3. Apply the solution to the real environment and fine tuning the application.
4. Understanding of MLOps Life cycle.
5. Understanding of the server and client side of the application.