ArticleSensors (Basel, Switzerland)2026
Advancing Structural Health Monitoring: Accurate PCB Design for IoT-Based Real-Time Damage Detection with Digital Twin Integration.
Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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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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Authors and funding
4 authors.
Funding
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Abstract
This paper introduces a cost-effective customised Printed Circuit Board (PCB) designed to establish an accurate Internet of Things (IoT) platform integrated with established Digital Twin (DT) models for advanced structural monitoring. The study focuses on developing a low-cost, precise PCB to synchronise real-time data between physical structures and their DT counterparts. The methodology includes a robust communication architecture utilising MQTT protocols, facilitating reliable data transmission and efficient integration with MATLAB for processing. Validation tests demonstrate high accuracy in data capture, with less than 1% deviation from conventional systems across multiple structural damage scenarios. This research highlights the potential of cost-effective PCB solutions for enhancing SHM and developing more resilient, proactive infrastructure management strategies.
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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.