Optimized Resource Orchestration for CS-Enabled SHM in LoRa Networks

Abstract

The growing demand for sustainable monitoring solutions has positioned Wireless Sensor Networks (WSNs) and Low-Power Wide Area Networks (LPWANs) as critical enablers for Structural Health Monitoring (SHM). In this work, we propose a centralized optimization framework for LoRa-based IoT networks that jointly tunes the spreading factor, coding rate, and compression factor to balance energy efficiency and data reconstruction quality. A centralized controller dynamically adjusts communication parameters based on environmental conditions and application constraints. We evaluate system performance through extensive simulations under noisy channels. Results demonstrate the effectiveness of centralized orchestration in adapting to channel variability while minimizing the computational burden.