Smart Farming in Arid Lands: AI and Digital Innovation in Sangola's Pomegranate Economy

Abstract The global community stands at a critical crossroads where technological advancement and environmental preservation must converge to ensure human well-being. This paper explores the multidisciplinary approach required to navigate global futures, focusing on the harmonization of economic science, Artificial Intelligence (AI), and digital innovation with sustainability metrics. Focusing specifically on the drought-prone Sangola Taluka of Solapur District, Maharashtra, this study examines how traditional agrarian economies can transition into sustainable models using precision farming. With over 73.96% of the workforce in Solapur engaged in agriculture, yet suffering from an average rainfall of less than 545-750 mm, integrating AI-driven resource frameworks is crucial. The paper provides factual insights into the pomegranate economy of Sangola and highlights how digital interventions can optimize water use, mitigate economic risks, and align local systems with Environmental Sustainability. Critical interventions such as IoT sensors, Convolutional Neural Networks (CNNs) for pathological tracking, and decentralized drone application systems are detailed to model an optimal input-to-output agricultural grid.