LoRa-Assisted Edge Analytics Framework for Long-Range Environmental Monitoring Using ESP32 Clusters
Abstract
The energy-efficient, scalable, and low-latency nature of long-range environmental monitoring needs resource-constrained operation of scalable and competent communication architectures. In this paper, the authors suggest a LoRa-assisted edge analytics platform with clustered ESP32 network nodes to obtain and process real-time environmental data. The suggested architecture will combine local edge intelligence with longrange LoRa communication in order to minimize the backhaul traffic and enhance system responsiveness. Delay and energy consumption and throughput mathematical models are obtained and the performance is assessed experimentally using representative simulation graphs. Findings show that the latency, power efficiency and scale of networking are greatly enhanced over monitoring solutions based on clouds.