DISTRIBUTED AI AND ISAC FOR AUTONOMOUS AGRICULTURAL INFRASTRUCTURE: TOWARD COGNITIVE 6G FARMING ECOSYSTEMS

Abstract

The rapid evolution of sixth-generation (6G) wireless networks is transforming traditional smart agriculture into intelligent and autonomous farming ecosystems. Existing agricultural systems primarily rely on Internet of Things (IoT) devices for data collection and centralized cloud computing, resulting in increased communication latency, scalability challenges, and limited real-time decision-making capabilities. This paper proposes a Distributed Artificial Intelligence (AI)-enabled Integrated Sensing and Communication (ISAC) framework for autonomous agricultural infrastructure within cognitive 6G farming ecosystems. The proposed architecture combines distributed edge intelligence, ISAC-enabled environmental sensing, federated learning, unmanned aerial vehicles (UAVs), and digital twin technology to facilitate real-time crop monitoring, precision irrigation, disease detection, and autonomous farm management. By processing data collaboratively across edge devices while preserving privacy, the framework minimizes communication overhead and enhances scalability. Furthermore, AI-driven resource optimization enables sustainable utilization of water, fertilizers, and energy. The proposed framework demonstrates how AI-native 6G networks can support intelligent, resilient, and self-adaptive agricultural systems, paving the way for next-generation precision farming.