A crowdsensing platform for structural health monitoring of rural bridge infrastructure

Research output: Contribution to journalArticle

Abstract

Background
Ageing bridge infrastructure in rural areas poses significant safety challenges, yet traditional structural health monitoring systems remain prohibitively expensive for regions with limited budgets. The Horizon Europe FUTURAL project developed an innovative crowdsensing platform to address this gap, enabling affordable infrastructure monitoring through vehicle-based indirect measurements combined with low-cost Internet of Things sensors.

Methods
The Resilience to Shocks Smart Solution integrates multiple components: a mobile application (FUTURAPP) connecting USB-C accelerometers to smartphones for data acquisition; cloud-based processing infrastructure for secure data transmission and storage; autoencoder neural networks trained on frequency-domain acceleration data (2-15 Hz) for unsupervised anomaly detection; finite element models developed using ANSYS APDL for structural validation; and a web-based dashboard featuring Structural Health Index visualizations and citizen engagement tools. The platform was deployed and tested on two pilot bridges: a three-span concrete road bridge in Durangaldea, Spain, and the Diakofti Bridge in Kythira, Greece.

Results
The autoencoder algorithms successfully distinguished between healthy structural responses and anomalous conditions using reconstruction error as the damage-sensitive feature, with the 99th percentile threshold effectively discriminating normal from abnormal measurements. Finite element models showed good agreement with in-situ vibration frequency measurements. The web platform demonstrated high usability among non-technical users, with the intuitive Structural Health Index gauge enabling immediate comprehension of bridge conditions. Citizen issue tracking features facilitated community participation in infrastructure safety monitoring.

Conclusions
The crowdsensing methodology offers significant advantages over traditional approaches in terms of cost, scalability, and accessibility for resource-constrained regions. The platform represents a meaningful advancement toward digitalization of rural infrastructure management, with methodology and tools providing a foundation for replication across European transport networks.
Original languageEnglish
JournalOpen Research Europe
DOIs
Publication statusPublished - 16 Feb 2026

Keywords

  • IoT
  • Structural
  • Monitoring
  • Crowdsensing
  • AI

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