Precision Agriculture and AI-Driven Resource Optimization for Sustainable Land and Resource Management
Mrutyunjay Padhiary, Azmirul Hoque, G. Krishna Prasad, Kundan Kumar, Bhabashankar Sahu
Abstract
Amidst the escalating global challenges of climate change, limited resources, and population growth, the adoption of sustainable land and resource management has become imperative to ensure food security and environmental conservation. Precision agriculture enhances process efficiency, reduces environmental impact, and improves agricultural productivity through the integration of artificial intelligence technologies, including machine learning, deep learning, and computer vision. Key findings indicate a reduction of 10–20% in input costs and an increase of 15–25% in crop yields through efficient resource utilisation. Furthermore, precision irrigation systems can achieve water savings of up to 50%, while targeted pesticide treatments reduce chemical usage by 30–40%. This chapter examines the economic and environmental benefits, highlighting a 20% reduction in CO2 emissions. Recent advancements underscore the potential of AI to foster sustainable agriculture, promoting environmental conservation and economic viability.