The book is about real-time infrastructure monitoring and safety using vibration and tilt sensors at urban scale integrated with IoT and has the core of machine learning algorithms for event detection and decision making. This work focused on comprehensive study, design, fabrication, testing, calibration, and deployment of industry-grade sensor nodes with extremely high resolution sensing to ensure trustable warnings against exceeding permissible site limits and call for intervention. The major demands in disaster monitoring consist of flexible deployment, system scalability, and fast retrieval of data to quickly locate hazardous areas (or eventual collapses).

Real-time Urban Scale Early Warning using Structural Health Monitoring IoT

Damiano Crescini
2022-01-01

Abstract

The book is about real-time infrastructure monitoring and safety using vibration and tilt sensors at urban scale integrated with IoT and has the core of machine learning algorithms for event detection and decision making. This work focused on comprehensive study, design, fabrication, testing, calibration, and deployment of industry-grade sensor nodes with extremely high resolution sensing to ensure trustable warnings against exceeding permissible site limits and call for intervention. The major demands in disaster monitoring consist of flexible deployment, system scalability, and fast retrieval of data to quickly locate hazardous areas (or eventual collapses).
2022
6204750771
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11379/562798
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