ArticleSensors (Basel, Switzerland)2024
Low-Cost, Low-Power Edge Computing System for Structural Health Monitoring in an IoT Framework.
Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed.
- Design, Development, and Laboratory Validation of a Low-Cost Multi-Sensor System for Bridge Structural Health Monitoring with Scour-Related Environmental Sensing.Sensors (Basel, Switzerland) · 2026Article
- Evaluation of an IoT Strain-Sensing System with LoRa Telemetry and Asset Metadata.Sensors (Basel, Switzerland) · 2026Article
- A Secure Multi-Layer Edge-Based Sensor Architecture for Building-Level Disaster Monitoring and Decision Support.Sensors (Basel, Switzerland) · 2026Article
- Spike-Driven Neuromorphic Sensing for Energy-Proportional Indoor Air Quality Monitoring in Multi-Zone IoT-Enabled Smart Building Environments.Sensors (Basel, Switzerland) · 2026Article
- Advancing Structural Health Monitoring: Accurate PCB Design for IoT-Based Real-Time Damage Detection with Digital Twin Integration.Sensors (Basel, Switzerland) · 2026Article
- Bridge Damage Identification Using Time-Varying Filtering-Based Empirical Mode Decomposition and Pre-Trained Convolutional Neural Networks.Sensors (Basel, Switzerland) · 2025Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A complete low-power, low-cost and wireless solution for bridge structural health monitoring is presented. This work includes monitoring nodes with modular hardware design and low power consumption based on a control and resource management board called CoreBoard, and a specific board for sensorization called SensorBoard is presented. The firmware is presented as a design of FreeRTOS parallelised tasks that carry out the management of the hardware resources and implement the Random Decrement Technique to minimize the amount of data to be transmitted over the NB-IoT network in a secure way. The presented solution is validated through the characterization of its energy consumption, which guarantees an autonomy higher than 10 years with a daily 8 min monitoring periodicity, and two deployments in a pilot laboratory structure and the Eduardo Torroja bridge in Posadas (Córdoba, Spain). The results are compared with two different calibrated commercial systems, obtaining an error lower than 1.72% in modal analysis frequencies. The architecture and the results obtained place the presented design as a new solution in the state of the art and, thanks to its autonomy, low cost and the graphical device management interface presented, allow its deployment and integration in the current IoT paradigm.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.