From Sensors to Insights: The Fusion of AI, Edge Computing, and Precision Agriculture

Abstract

Integrating artificial intelligence (AI), with edge computing, and precision agriculture is revolutionizing farming making it more resilient and sustainable. This article focuses on combine positive impact that the merger of these transformative technologies, can have in providing solutions for key challenges such as plant disease detection, resource optimization, and real-time decision-making. AI algorithms enables rapid and precise analysis of massive agricultural data allowing early disease detection and preventive measures to ensure plant health. Concurrently, edge computing gives the power of reduced latency with on spot data processing and solutions provision to the farmers, even in areas with limited coverage. The fusion of these technologies aligns with key UN sustainable development goals (SDGs), by optimizing the use of water, fertilizers, and pesticides, reducing environmental impacts, and mitigating climate change effects. However, the widespread adoption of AI and edge computing in agriculture is constrained by challenges such as hardware limitations, data collection, quality issues, and the need for technical expertise in particular cases. This review explores how these technologies are currently being used in agriculture, their pros, cons, and potential areas for further research and development. Encouraging interdisciplinary collaboration and continuous innovation will be crucial to overcome these challenges, ensuring that AI and edge computing play a central role in securing global food security and promoting climate-resilient farming.