Securing Agricultural IoT Networks: Adapting SAFE-CAST Framework for LoRa-based Smart Farming Applications

Machine-to-machine (M2M) communication at IoT scale demands simultaneous security, privacy, and efficiency. We present SAFE-CAST, an integrated framework that combines federated clustering (Lloyd's K-means) with dual cluster-head selection, Quality-Diversity-based channel selection and division (QDOA), Merkle-tree-backed blockchain trust management, homomorphic encryption for privacy-preserving data exchange, and an Adaptive Multi-Agent RL scheme for Context-Aware Transmission (AMARLCAT). In NS-3.26 simulations, SAFE-CAST reduces energy consumption by 21.6%, increases throughput by 14.5%, strengthens security metrics by 15.3%, lowers end-to-end latency by 33.9%, and cuts packet loss by 12.9% versus state of the art. The architecture is modular, scalable, and designed for edge-assisted deployments where privacy and real-time performance are critical.