Automated Plant Disease Identification with Artificial Intelligence for Mobile and Edge Devices
Conducted research and developed AI models for real-time plant disease identification on mobile and edge devices, earning distinction in a master's project.
For my master’s research at Teesside University, I developed an AI-based solution for automated plant disease identification tailored for mobile and edge devices.
The project required a systematic literature review, hypothesis development, and model validation using TensorFlow Lite and MobileNets. I processed and cleaned data, trained models, and documented my findings in a thesis that received distinction.
The project led to the development of a functional artefact, codebase on GitHub, and a viva presentation, contributing to advancements in precision agriculture and plant disease management.