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Wireless Sensor Networks Composed of Standard Microcomputers and Smartphones for Applications in Structural Health

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This study introduces a WiFi-based wireless sensor network framework for structural health monitoring (SHM) using affordable single-board computers. The system offers robust data acquisition and analysis, proving effective for SHM tasks.

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Area of Science:

  • Engineering
  • Computer Science
  • Materials Science

Background:

  • Wireless sensor networks (WSNs) are increasingly vital for structural health monitoring (SHM) due to their deployment flexibility and cost-effectiveness.
  • Existing WSN solutions may lack the integration capabilities or affordability required for widespread SHM applications.

Purpose of the Study:

  • To develop and validate a software framework for WiFi-based WSNs using low-cost single-board computers for SHM.
  • To enable robust data acquisition, processing, communication, and timing within the WSN framework.
  • To integrate smartphones as data acquisition nodes, leveraging their internal sensors for enhanced monitoring capabilities.

Main Methods:

  • Development of a software framework with specific system-level components for data acquisition, processing, communication, and timing.
  • Validation of the framework on Raspberry Pi computers, with detailed performance analysis.
  • Implementation of a complementary smartphone application for data acquisition, visualization, and analysis.
  • Prototypical integration of smartphones as data acquisition nodes utilizing their internal sensors.

Main Results:

  • The framework demonstrated robust performance in measurement quality, including sampling accuracy and time synchronization.
  • The system's suitability was validated through several monitoring campaigns, comparing target quantities with reference measurements.
  • The presented system achieved measurement performance suitable for typical SHM tasks like modal identification.

Conclusions:

  • The developed WiFi-based WSN framework provides a cost-effective and robust solution for structural health monitoring.
  • The integration of low-cost single-board computers and smartphones enhances the feasibility and accessibility of SHM.
  • The system represents a viable alternative to traditional, often more expensive, structural monitoring solutions.