This study presents a low-cost edge-IoT-based structural health monitoring (SHM) architecture for crack monitoring in operational underground tunnels. The system integrates crack-displacement sensing, temperature measurement, ESP32-based edge processing, LoRa/MQTT communication, AES/ECDSA-based data protection, and cloud-based data management. The architecture was validated through a 30-day field campaign at two representative cracks in the Hai Van Tunnel, with measurements acquired at 60 s sampling intervals. The results show that edge-based wavelet–Kalman processing improved measurement stability and reduced high-frequency noise, while the implemented security mechanism introduced only minor latency relative to the monitoring cycle. The two monitored cracks exhibited small micrometer-scale fluctuations associated with temperature variation and showed no cumulative widening trend during the observation period. This study demonstrates the feasibility of campaign-based tunnel crack monitoring using a trustworthy edge-sensing architecture, while longer deployments with more sensing nodes are needed to fully evaluate scalability and operational durability.

Structural health monitoring (SHM) systems based on Internet of Things (IoT) technologies have become an effective approach for continuous monitoring of bridge infrastructures. However, many wireless monitoring systems relying on LoRaWAN or contention-based communication suffer from packet collisions, unpredictable latency, and limited scalability when multiple sensing nodes operate simultaneously. To address these limitations, this study proposes a soft real-time LoRa-based IoT architecture for bridge SHM using a time division multiple access (TDMA) communication framework implemented on an embedded real-time platform. The proposed system integrates distributed vibration sensing nodes, a TDMA-enabled LoRa communication layer, an ESP32-based gateway, and a web-based monitoring database for remote visualization and analysis. The architecture leverages FreeRTOS (v10.4.3) for system-level task scheduling, enabling concurrent execution of sensing, communication, and networking processes across the dual-core ESP32-WROOM-32D platform. Experimental results obtained using a laboratory-scale cable-stayed bridge model demonstrate stable multi-node communication with a packet delivery ratio exceeding 95% and predictable TDMA-scheduled transmission cycles with TDMA slots of 100–200 ms under the evaluated operating conditions. The experiments validate end-to-end operation using a representative three-node deployment, while broader scalability is evaluated analytically through the TDMA capacity model and identified as future work for larger physical deployments.