IoT system for real-time monitoring of small bridges

Abstract

An IoT system for real-time monitoring of a small bridge, consisting of several sensors, including at least one pressure or load sensor, a displacement sensor, a corrosion sensor, and a tilt sensor; an embedded controller that collects sensor data and compares it with predefined safety thresholds to detect anomalies; and a wireless module that sends alerts and telemetry data to a cloud platform when a structural defect is detected.

Description

Application area of ​​the invention

[0001] The invention relates to structural monitoring systems that use sensors, embedded controllers and energy-saving wireless long-range modules to continuously assess the integrity of small bridges and alert the authorities. Background of the invention

[0002] Small bridges are widespread, critical infrastructure whose continuous monitoring is often inadequate due to budget and access limitations. This leads to reliance on infrequent inspections, potentially overlooking early damage. The literature on structural monitoring describes sensor networks that measure strain, displacement, tilt, vibration, temperature, corrosion, and cracks to detect anomalies and track trends indicating progressive damage. Wireless IoT communication technologies such as LoRaWAN, NB-IoT, cellular, and MQTT / cloud architectures enable energy-efficient, long-range telemetry suitable for remote bridges.However, implementing a coherent, cost-effective system specifically tailored for small bridges requires the careful integration of energy-efficient sensors, edge analytics with thresholding methods, reliable long-range uplinks, and cloud dashboards with historical analysis and alerts. Existing case studies and vendor systems demonstrate the feasibility of long-distance inclination and strain measurement. Nevertheless, there remains a need for an integrated device specifically designed for small bridges that offers predefined safety thresholds, in-device anomaly detection, LoRa-based alerts upon defect detection, and cloud interfaces for authorities to analyze real-time and historical data. Summary of the invention

[0003] The invention relates to an IoT system consisting of a network of bridge-mounted sensors (pressure / load, displacement, corrosion, and inclination), an edge controller for real-time data acquisition and anomaly detection based on predefined safety thresholds, and a long-range LoRa or LoRaWAN module that sends alerts and telemetry data to a cloud platform upon detection of structural defects. The cloud platform stores, visualizes, and analyzes historical data for trend analysis and enables authorized users to configure thresholds, review events, and plan preventive maintenance.

[0004] In various implementations, the system utilizes energy-efficient sensors with signal conditioning, connected to an embedded controller. This controller performs local filtering and threshold logic, issues immediate alerts via LoRa when setpoints are exceeded, buffers data for temporary connection interruptions, and synchronizes it with cloud dashboards for continuous monitoring. The architecture is characterized by cost-efficiency and ease of implementation on small bridges, while simultaneously providing proactive maintenance information to reduce the risk of structural damage. Detailed description

[0005] The system comprises a sensor unit mounted at structurally relevant points on a small bridge. Pressure or load sensors at the bearings measure contact forces; displacement sensors monitor joint movement or span deflection; tilt sensors detect angular changes indicative of settlement or rotation; and corrosion sensors detect indicators of reinforcement corrosion or environmental corrosion. Temperature and humidity sensors can be integrated to consider structural responses within their context. Each sensor is connected to the local data acquisition unit, which incorporates appropriate bridge amplifiers and filters to ensure stable measurements.

[0006] An embedded controller aggregates sensor inputs, timestamps them, and applies digital filters and baseline normalization. The controller stores configuration tables with predefined safety thresholds for each sensor type (e.g., maximum inclination change per interval, displacement limits, corrosion potential trends), compares real-time values ​​and derived features against these thresholds, and flags anomalies. The controller maintains a ring buffer containing the current raw and processed data to capture the context when a threshold is exceeded.

[0007] When an anomaly is detected, the controller activates a LoRa or LoRaWAN radio module to send an alert containing sensor identifiers, a timestamp, the threshold exceeded, and a brief summary of the measured values ​​before and after the event. LoRa / LoRaWAN offers ranges in the kilometer range with low power consumption, making it particularly suitable for rural areas or bridges that are difficult to access. The controller can fall back on other connections (e.g., NB-IoT / LTE) if necessary and implements retransmission and acknowledgment logic to ensure delivery of the alert.

[0008] For continuous operation under fluctuating connectivity, the gateway stores data locally for several days and forwards it to the cloud upon reconnection to ensure continuity of analysis. Time synchronization via GNSS / NTP is supported to guarantee consistent timestamps across all sensor nodes. The housing is designed for outdoor use and features robust power management with a battery and optional solar input for unattended operation.

[0009] The cloud-based monitoring platform collects telemetry data from secure endpoints, stores time series, and provides dashboards that allow authorities to visualize live sensor readings, trends, and event histories. The platform enables the configuration of thresholds and alarm receivers and supports analyses such as drift detection for tilt / displacement, rate-of-change alarms for corrosion progression, and environmental correlation analyses. Role-based access control ensures that only authorized users can adjust thresholds or acknowledge alarms.

[0010] Edge analytics features such as moving averages, RMS vibration (if accelerometers are present), and rate limits reduce false alarms and send only relevant alerts to conserve bandwidth. The controller implements self-recovery and status reporting mechanisms, clearly distinguishing system failures (e.g., sensor failure, low battery) from structural anomalies.

[0011] The system supports wireless updates for adjusting thresholds and firmware, thus enabling the consideration of bridge-specific characteristics identified during commissioning. Commissioning includes the acquisition of baseline data under known loads to calibrate the thresholds and validate sensor positions. Thanks to its modular sensor design, the system can be adapted to the specific bridge type: for small concrete slab bridges, tilt and crack / displacement sensors may be the primary focus; for steel girder bridges, on the other hand, strain / load and corrosion monitoring may be paramount.

[0012] In normal operation, the system continuously collects sensor data at a defined interval, calculates characteristics, and compares them with threshold values. If a sudden change in inclination is detected during a load event, a warning with contextual data is immediately transmitted via LoRa, enabling remote analysis. Historical dashboards reveal trends such as increasing displacements at expansion joints or rising corrosion indices, thus providing a basis for planning preventive maintenance work.

[0013] Security measures include mutual authentication, encrypted transmission, device certificates, and signed firmware to protect data integrity and system operation. Data management policies regarding retention and access control meet the infrastructure operator's requirements. The overall concept results in a cost-effective, automated, and continuous monitoring solution suitable for widespread deployment on smaller bridges.

[0014] The system architecture is based on methods for structural monitoring described in the literature and industry, integrating common sensor types for bridges and using long-range IoT communication to reduce on-site visits and enable proactive maintenance.

Claims

[1] An IoT system for real-time monitoring of a small bridge, consisting of several sensors, including at least one pressure or load sensor, a displacement sensor, a corrosion sensor and a tilt sensor; an embedded controller that collects sensor data and compares it with predefined safety thresholds to detect anomalies; and a wireless module that sends alerts and telemetry data to a cloud platform when a structural defect is detected. [2] System according to claim 1, wherein the wireless module comprises a LoRa or LoRaWAN radio module configured for long-distance, low-power transmission to a remote network gateway that enables access to the cloud platform. [3] System according to claim 1, wherein the embedded controller applies edge analytics including filtering, feature extraction and rate of change detection and caches data to maintain transmission during temporary connection interruption. [4] System according to claim 1, wherein the cloud platform stores time series data, displays real-time and historical sensor readings, provides configurable alarm thresholds and notifications for authorized users, and supports the planning of preventive maintenance based on detected trends.