Plant AI: An Application System for Detecting Plant Disease - Joash Otto (Uganda Christian University, 2024)
This project introduces an innovative Artificial Intelligence (AI) system specifically designed to address the pressing problem of plant diseases which significantly impact agricultural productivity. The urgency for early detection technologies to mitigate crop losses is more crucial than ever. In response, our AI model employs advanced deep learning algorithms, trained on an extensive dataset of leaf images covering a diverse range of diseases, highlighting the approach to tackling the identified problem. The capability of our system to precisely recognize disease symptoms in plants has undergone rigorous testing, yielding a high success rate in disease identification, which constitutes our key findings.Anand, R., Mishra, R.K. and Khan, R. (2022) The implementation phase involved developing a user-friendly application, making the technology accessible to farmers and enabling early disease detection to improve crop management and production. This operational approach emphasizes the practical application and field usability of our system. The successful outcomes of the project not only underscore the AI system's effectiveness in identifying plant diseases but also underscore its significant potential to revolutionize agricultural practices by democratizing access to advanced diagnostic tools. Furthermore, this report delves into the comprehensive development process of the AI system, from the initial data collection and model training phases to the nuances of application development and field testing. Through this detailed narrative, we aim to highlight the substantial benefits and the expansive future potential of integrating AI technologies in agriculture. In this context, the abstract serves as a concise reflection of the entire project, meticulously answering the critical questions of what problem is being addressed, how it is approached, what the findings are, and why these findings matter. This not only fulfills the purpose of providing a snapshot of the project's essence but also functions as a guiding framework for the report, ensuring coherence and focus throughout the document.