Preprint Article Version 1 This version is not peer-reviewed

Intelligent System for Analysis and Monitoring of Flood Embankments Based on Electrical Impedance Tomography, Machine Learning and Internet of Things

Version 1 : Received: 19 August 2018 / Approved: 20 August 2018 / Online: 20 August 2018 (06:29:09 CEST)

How to cite: Rymarczyk, T.; Kozłowski, E.; Kłosowski, G. Intelligent System for Analysis and Monitoring of Flood Embankments Based on Electrical Impedance Tomography, Machine Learning and Internet of Things. Preprints 2018, 2018080346 (doi: 10.20944/preprints201808.0346.v1). Rymarczyk, T.; Kozłowski, E.; Kłosowski, G. Intelligent System for Analysis and Monitoring of Flood Embankments Based on Electrical Impedance Tomography, Machine Learning and Internet of Things. Preprints 2018, 2018080346 (doi: 10.20944/preprints201808.0346.v1).

Abstract

The article presents a non-destructive test system based on electrical impedance tomography for monitoring flood embankments. The technology of cyber-physical systems and the Internet of Things with the use of electrical impedance tomography enables real-time monitoring of flood embankments. This solution provides a visual analysis of damage and leaks, which allows for quick and effective intervention and possible prevention of danger. A dedicated solution based on the IT structure, dedicated laboratory models and a dedicated measurement system with various types of sensors and machine learning algorithms for image reconstruction has been developed. The system includes specialized intelligent devices for tomographic measurements. The application contains the analysis of anomalies occurring in the structure of the object as a result of damage or danger and breaking the shaft during the flood. The presented solution enables ongoing monitoring of objects by collecting measurement results, forecasts and simulations. The main advantage of the proposed system is the spatial ability to analyse shafts, high accuracy of imaging and high speed of data processing. The use of tomographic techniques in conjunction with image reconstruction algorithms allow for non-invasive and very accurate spatial assessment of humidity and damages of flood embankments. The presented results show the effectiveness of the presented research.

Subject Areas

inverse problem; electrical impedance tomography; machine learning; flood embankment; internet of things

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