Soft computing algorithms for infrastructure monitoring: preliminary results of PROION project

Konstantinos Nikolakopoulos; Vassiliki Mpelogianni; Peter Groumpos; Aggeliki Kyriou; Athanassios Ganas; Vassiliki Charalampopoulou; Theodoros Athanasopoulos

doi:10.1117/12.2680702

21 September 2023 Soft computing algorithms for infrastructure monitoring: preliminary results of PROION project

Konstantinos Nikolakopoulos, Vassiliki Mpelogianni, Peter Groumpos, Aggeliki Kyriou, Athanassios Ganas, Vassiliki Charalampopoulou, Theodoros Athanasopoulos

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Proceedings Volume 12786, Ninth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2023); 127861S (2023) https://doi.org/10.1117/12.2680702
Event: Ninth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2023), 2023, Ayia Napa, Cyprus

Abstract

Structural health monitoring of civil infrastructures is a complex engineering problem that requires the use of advanced soft computing algorithms. The rapid advances in soft computing have been a step forward in the direction of infrastructure monitoring. The field of computer science has given promising results in monitoring systems when applied along with engineering technologies. In this framework, Artificial Intelligence (AI) Deep and Machine Learning applications, Neural Networks, Fuzzy Logic, Fuzzy Cognitive Maps (FCM), Genetics Algorithms and Hybrid systems are growing exponentially in the field of structural health monitoring, including structural recognition, change detection, crack detection, damage identification, damage quantification and damage prediction. Specifically, some of the above-mentioned more sophisticated infrastructure soft computing monitoring algorithms are utilized to generate strategies and processing pipelines towards structural building damage mapping and assessment. In this paper remote sensing data, acquired by Global Navigation Satellite System (GNSS), Synthetic Aperture Radar (SAR), Light Detection and Ranging (LiDAR) and Unmanned Aerial Vehicles (UAV) sensors will be processed and a state-of-the-art unified platform imbedding Neural Networks, Fuzzy Cognitive Maps and Hybrid systems in the field of Structural Health Monitoring of civil structures is proposed.

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Konstantinos Nikolakopoulos, Vassiliki Mpelogianni, Peter Groumpos, Aggeliki Kyriou, Athanassios Ganas, Vassiliki Charalampopoulou, and Theodoros Athanasopoulos "Soft computing algorithms for infrastructure monitoring: preliminary results of PROION project", Proc. SPIE 12786, Ninth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2023), 127861S (21 September 2023); https://doi.org/10.1117/12.2680702

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KEYWORDS

Artificial intelligence

Evolutionary algorithms

Fuzzy logic

Education and training

Artificial neural networks

Machine learning

Structural health monitoring

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