Eco-Defender: Detection of Aphids Using YOLOV5 Model and Their Eradication Using a Precise Laser Equipped on an Autonomous rover

Traditional pest control methods, relying on chemical pesticides and manual inspections, are inefficient and environmentally damaging, leading to pesticide resistance, soil degradation, and harm to non-target organisms. This paper introduces a novel pest control system combining laser technology with machine learning, specifically YOLOv5, which achieves $85.4 \%$ precision in detecting aphids-significant pests affecting plant health. Integrated with logistic regression for decisionmaking and precise laser technology for pest neutralization, this system minimizes chemical use and environmental impact while enhancing control efficacy. The findings demonstrate that machine learningdriven detection, coupled with laser technology, offers a sustainable and precise alternative to conventional pest management, potentially revolutionizing agricultural practices.