Plant Health Monitoring and Species Identification

Abstract

In modern agriculture and environmental conservation, having tools to monitor plant health is essential for making farming more productive and sustainable. Our Final Year Project (FYP) aims to develop an innovative web application that utilizes image processing, machine learning (ML), and artificial intelligence (AI) to analyze plant health and provide real-time feedback. This app is designed to assist a wide range of users, including farmers, gardeners, and plant enthusiasts, in making informed and smart decisions to improve plant care. One of the key features of the app is the ability to identify plant species quickly and accurately. Additionally, it includes a hydration assessment feature that checks whether a plant is hydrated or not. Another important aspect of the app is its disease detection functionality, which can detect various plant diseases and offer advice on how to manage them. Users can upload images of their plants, and the app will use machine learning algorithms to analyze these images and provide valuable feedback almost instantly. The artificial intelligence embedded in the system will not only detect diseases but will also evaluate if the plant has enough water, and give detailed advice on how to care for it based on the analysis. The user interface is designed to be easy for everyone, whether you are a beginner in plant care or an experienced gardener. As more people use the app and provide more data, the machine learning models will improve over time, making the app more accurate and efficient. Continuous learning ensures that the app stays relevant and adapts to new challenges in plant health monitoring. By combining traditional plant care knowledge with modern technological advances, this app helps users make smarter, more sustainable decisions that are beneficial for the future of agriculture and environmental conservation. This project aims to bridge the gap between traditional plant care methods and modern technology, making it easier for users to care for their plants in a more efficient and data-driven way.