6G-Enabled Agricultural IoT: Serverless Edge-to-Cloud Middleware for Ultra-Low Latency Resource Management in Food Safety Networks

The impending transition to 6th Generation wireless networks promises ultra-reliable, low-latency communications capable of transforming agricultural food safety. However, the extreme data velocity generated by massive machine-type communications in 6G IoT environments introduces severe infrastructural bottlenecks for traditional centralized cloud architectures. This paper proposes a cloud-native, edge-orchestrated architectural framework utilizing Amazon Web Services to construct a real-time, serverless pipeline for 6G agricultural telemetry. By deploying asynchronous Python middleware integrated with dynamic resource management algorithms, the proposed system ingests high-frequency food safety data, prioritizing critical anomaly detection such as cold-chain temperature degradation or pathogenic pathogen detection. Preliminary architectural evaluations demonstrate that decoupling localized edge-filtering from centralized cloud persistence significantly reduces ingestion latency to sub-millisecond thresholds, providing computer scientists and agronomists with a deterministic, scalable technological foundation for leveraging 6G networks in critical food safety infrastructure.