Development and Performance Evaluation of a Selective Pyrethrum Harvester
This study aims to develop and evaluate a precision pyrethrum flower harvester optimized for small-scale farmers. To enhance harvesting efficiency, artificial intelligence (AI) will be integrated, employing MATLAB’s Image Processing and Deep Learning Toolboxes to train a neural network capable of recognizing and targeting mature flowers. This AI model will be deployed on a Raspberry Pi microcomputer, enabling real-time adaptive height adjustments based on vision sensor data.
Research Project
Submitted by: Andrew Mwamba, School of Engineering
View profileAndrew Mwamba
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