VERDANT TERRA: An Acoustic and AI-Driven Framework for Real-Time Plant Stress Management in Precision Agriculture

Abstract: Precision agriculture demands innovative solutions for early and accurate plant stress detection to optimize growth and yield. Existing methods often lack real-time capabilities and proactive environmental control. This research presents VERDANT TERRA, an automated plant stress management system utilizing ultrasonic sensors and machine learning (ML). VERDANT TERRA captures stress-induced acoustic emissions from plants, imperceptible to human hearing. These signals are then analyzed by a custom-trained ML algorithm, enabling real-time stress identification and classification. The system integrates with environmental control mechanisms, automatically adjusting parameters like irrigation and lighting based on the detected stress levels. Experimental results demonstrate VERDANT TERRA's efficacy in identifying and responding to various stress factors, including dehydration and nutrient deficiencies, ultimately enhancing plant growth and productivity. VERDANT TERRA offers a cost-effective and scalable solution for precision agriculture, paving the way for sustainable and optimized crop management