Fog-Based Deep Learning Predicts Cold-Chain Temperatures Over LoRaWAN
Researchers describe a fog-computing setup that runs deep learning inference near the source of sensor data to forecast temperatures in perishable food cold chains. The work targets the latency and connectivity limits that make cloud-only inference impractical for LoRaWAN-linked monitoring of fresh produce. The paper reports on a real-world deployment and characterises its performance.