An increase in the human population requires an increase in the quality of agricultural production. Generally, the most important thing in agriculture that affects the quantity and quality of crops is plant diseases. A farmer knows that his plant is attacked by the disease through direct vision. However, this process is sometimes inaccurate. With the development of machine learning technology, plant disease detection can be done automatically using deep learning.
Through this project, we desired to develop an application that can help the farmers that are unaware of rice plants’ quality and disease just by scanning the crops. The application will detect their quality (health) status. If a disease is detected, the application will give information about the disease (this includes 3 diseases: Brown Spot, Hispa, and Leaf Blast) and show how to cure the diseased crops. In addition, the earlier prediction result can be stored in a database to be analyzed later on.
The most important thing in agriculture that affects the quantity and quality of crops is plant diseases. The rice plants face a serious problem that causes the reduction of yields due to the diseases. Based on this problem, we propose the idea of developing the Rice Disease Detection application to detect diseases that often attack rice crops including Brown Spot, Hispa, and Leaf Blast). By developing this application, we believe that the farmers won’t have trouble with the disease, and rice crop quality will increase much better.
Build an android-based application to make it easier for users, mostly farmers, to detect rice crop disease and improve the quality of rice crops.
- Provide easy access for users to detect rice crop disease symptoms
- Provide education about the rice crop disease and how to cure it
- Help to improve the quality of rice crops
From the problems we have described, we agreed to implement our solution into an Android application called Rice Disease Detection. Rice Disease Detection can be used to detect the disease on Rice Crop using Image Recognition. The results of Image Recognition and Rice Crops data will be analyzed by a Machine Learning model from Cloud to predict whether the crop has a disease or not. Not only that, Rice Disease Detection will improve the crops' quality by its functionality such as how to cure guidance, the right treatment to have the best crops conditions, articles to improve their knowledge, and the progress recapitulation. Therefore, we conclude that these are our features:
- Login/Register
- Guidance
- Rice Disease Detection
- Curing Guidance
- Articles
- Progress Tracking.
Google Colab/Python, Library (TensorFlow, Keras, Scikit-learn), pretrained model (DenseNet121)
Android Studio/Kotlin, Firebase, Figma UI
Google Cloud Platform (Google Compute Engine, Virtual Machine, Bucket)
The creation of a Rice Disease Detection Application that can help farmers to improve the quality of their rice crops.