Bangkit Capstone Project, This project will consist of 4 important parts, which are electronics, Machine Learning, Cloud Computing, and Mobile apps. The electronic part consists of a microcontroller and sensors that will be connected to the cloud server and apps via Wi-Fi. The sensors used include the DHT22 sensor to determine temperature and soil moisture sensor to monitor soil conditions. The sensor will connect to the ESP32 microcontroller and upload the data to the server. The app also has a feature to detect the health of the plants. Users can take a photo of some part of the plant that is affected by the diseases, then the app will predict the plant disease based on the Machine Learning model that has been made. Apps will also provide treatment recommendations for the diseases.
In this repository, there are several learning path activities, each activity can be seen from the name of the existing directory:
- Android
- Cloud Computing
- Machine Learning
- Electronics
- In the ML part the final result is to create a model TFlite Format and the results will be deployed to the Android part.
- In the electronics part, making IoT hardware which will be connected to the Android section assisted by the cloud computing part.
- In the cloud computing part, creating a cloud architecture that connects the IoT hardware that will be connected to the Android part and the application database.
- On the Android part, making an overall application combines all the features of ML images classification of leaf diseases and plant IoT monitoring features into one Android application.
