EXPERIMENTAL CHARACTERIZATION OF MEASUREMENT CONSISTENCY AND TEMPORAL VARIATION IN AN ESP32 BASED IOT SYSTEM FOR BRIDGE MONITORING

Structural health monitoring (SHM) relies on the systematic acquisition and temporal analysis of data that reflect structural behavior. Internet of Things (IoT) architectures offer considerable potential for developing distributed, connected, and low-cost monitoring systems [1–6]. Before these systems can support anomaly detection or structural condition assessment, however, the quality, consistency, and temporal variability of the acquired data must be evaluated [7–11]. This study reports the experimental deployment of an ESP32-based IoT prototype for multiparameter monitoring of a bridge. The prototype integrates DHT22 and DS18B20 sensors for temperature measurement and an MPU-6050 module comprising a triaxial accelerometer and gyroscope for inertial measurements. Three measurement campaigns were conducted at different locations on the bridge. Temperature measurements from the DHT22 and DS18B20 sensors exhibited closely correlated temporal trends, with correlation coefficients of 0.97, 0.90, and 0.83 for the three campaigns, respectively. Nevertheless, differences in measured temperature levels and fluctuation ranges suggest sensitivity to local environmental conditions and sensor placement. The indicators derived from the MPU-6050 measurements also differed in magnitude and variability across the experimental configurations. These findings provide a preliminary characterization of the temporal patterns captured by the prototype and identify similarities and differences among measurement locations. Further validation is required to establish measurement accuracy and determine the suitability of the system for structural condition assessment.