Revolutionizing Smallholder Agriculture with AI: Intelligent Sensor Networks for Real-Time Climate

Abstract

Purpose: Smallholder agriculture forms the backbone of global food security; however, it has been considered highly vulnerable to the impacts of climate variability. The present study explores the role of Artificial Intelligence in integrating intelligent sensor networks for real-time climate monitoring and improving resilience among smallholder farmers.

Materials and Methods: The present research will employ a mixed-methods approach, combining quantitative analysis of climate data with qualitative interviews of farmers regarding the efficiency of AI-driven strategies for climate adaptation.

Findings: The findings of this study have shown that intelligent sensor networks greatly enhance precision and timeliness of real-time climate data. These help the smallholder farmers in making very precise decisions regarding irrigation, pest control, and crop management that eventually lead to increased productivity and reduced vulnerability to climate risks. The quantitative results show that farmers adopting AI-driven interventions are likely to have a 50% better yield compared to those dependent on conventional methods. Farmers reported qualitative insights into the transformative potential of these technologies by way of improved confidence in decision-making processes and increased resilience against adverse climatic conditions.

Implications to Theory, Practice and Policy: Financial constraints, technical difficulties, and the need for capacity building in facilitating technology adoption comprise some important challenges that emanate from the study. All these barriers, once overcome, will see the integration of AI and sensor networks realize benefits not only at an individual farmer level but also at the global agricultural sustainability level. This research contributes to the increasing literature on climate-smart agriculture and gives actionable recommendations for policymakers, practitioners, and stakeholders. The potential of AI-driven intelligent sensor networks can be leveraged to empower smallholder farmers toward sustainable agricultural development that would meet the challenges of food security and economic stability in a changing climate.