THE ROLE OF PRECISION AGRICULTURE AND SMART TECHNOLOGIES: A COMPREHENSIVE RESEARCH STUDY ON DRONES, SENSORS, AND AI FOR ENHANCING CROP MANAGEMENT AND FOOD SECURITY

Abstract

Global agriculture is increasingly threatened by climate variability, soil degradation, and resource scarcity, creating the need for sustainable and efficient farming practices. Precision agriculture offers a pathway to address these challenges through the integration of smart technologies for site-specific management. This study investigated the combined role of drones, IoT-enabled sensors, and artificial intelligence in enhancing crop monitoring, resource use efficiency, and yield prediction within a semi-arid agroforestry landscape covering 250 hectares. Multispectral and hyperspectral UAVs were deployed to generate vegetation indices (NDVI, SAVI, NDWI), while IoT-based soil and climate sensors recorded continuous data on moisture, nutrients, and microclimatic conditions. These datasets were analyzed using advanced machine learning algorithms, including random forest regression and convolutional neural networks, supported by multivariate approaches such as principal component analysis. Results showed that UAV-derived indices accurately tracked crop growth and stress, IoT systems revealed nutrient and water variability strongly linked with canopy performance, and AI models achieved more than 80% variance explanation with stress classification accuracies above 90%. Precision-managed plots recorded a 19% higher yield while reducing water and fertilizer inputs by 21% and 17%, respectively, compared to conventional practices. These findings demonstrate the potential of integrated smart farming technologies to promote climate-smart agriculture, strengthen food security, and reduce environmental footprints, while highlighting the need for affordable solutions and multi-location validations for wider adoption.