Integrating AI with Traditional Agriculture Practices

Abstract

Agriculture, which is a cornerstone pillar of economic development and sustainability, is being revolutionized to respond to increasingly emerging challenges like climate change, crop diseases, resource degradation, and population pressure. Farming practices that were long based on traditional practices embedded in indigenous knowledge are now increasingly being complemented with technological innovations to stabilize food security and environmental resilience. One such innovation is Artificial Intelligence (AI), which is an essential facilitator of modernizing agriculture. This essay discusses the convergence of AI with conventional agricultural methods, with emphasis on the use of hyperspectral imaging technologies on different platforms—airplanes, satellites, close-range systems, and drones. These technologies, in conjunction with AI-enabled data analytics, provide greater precision and effectiveness in tracking the health of crops, soil, and environmental stressors. The paper analyses how every hyperspectral platform gives something special to agricultural productivity and how AI enables the interpretation of data and decision-making. Through connecting conventional knowledge to sophisticated AI applications, this study gives a glimpse into the future direction of sustainable, intelligent, and adaptive farming systems that can respond to existing and emerging needs of agriculture.