An Android-based Image Processing Approach for Indoor Plant's Disease Detection
Year: 2024
Type: dissertation
Abstract: This project introduces a disease-free solution for people who love indoor plants. We created an Android app that uses fancy image processing to detect diseases in indoor plants early on. The app not only helps diagnose plant issues through pictures but also gives smart solutions to fix them. We aim to improve the health of indoor plants by combining technology and gardening, providing a user-friendly platform for plant lovers to take better care of their green friends. Our main focus is on developing a plant disease detection app using image classification. We use a friendly web tool to quickly and accurately create machine learning models. The app targets four common diseases in indoor plants. The process involves uploading various plant images, training the model, and then integrating it into Android Studio for easy use.
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W6930637403
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