Published Paper Details:

Agriculture is a critical sector for sustaining human life, and the demand for increased crop yield, quality, and resource efficiency has never been higher. To address these challenges, this research presents a novel approach to crop growth monitoring through the integration of system adaptivity and edge Artificial Intelligence (AI) technologies. The proposed system leverages a combination of advanced sensors, edge computing, and AI algorithms to provide real-time monitoring and analysis of crop growth. Traditional approaches to crop monitoring rely heavily on centralized data processing, which can lead to latency issues, data security concerns, and increased operational costs. In contrast, our approach utilizes edge AI to process data directly at the source, reducing latency and ensuring data privacy.The system's adaptability is achieved through a smart system management mechanism that dynamically adjusts cryptographic functions based on security needs and resource constraints. This approach ensures that the system can safeguard sensitive sensor data without compromising performance or energy efficiency.