Harrasi, A. A., Grispos, G., & Gandhi, R. (2023). Using Cybersecurity Testbeds to Evaluate (In)Secure Structural Health Monitoring Systems. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 902–908). Omaha, USA: University of Nebraska at Omaha.
Abstract: An increasing amount of technology is being integrated into bridges and other structures, such as dams and buildings, to proactively look for signs of deterioration or damage. These technologies are collectively known as structural health monitoring systems. While the benefits of integrating this technology are attractive, this integration is also creating an environment that is conducive to security vulnerabilities. While previous research has focused on the broader cybersecurity challenges associated with structural health monitoring systems, limited guidance is available for identifying specific security vulnerabilities in these systems and their implications for responding to security incidents. Hence, this paper presents CYBRBridge, a cybersecurity testbed that provides a sacrificial environment to assist in identifying and exploring vulnerabilities associated with structural health monitoring systems. This paper reports ongoing research efforts to develop the CYBRBridge testbed and initial results identifying vulnerabilities within the wireless components of a commercial structural health monitoring system
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Chalioris, C. E., A. Papadopoulos, N., Sapidis, G., C. Naoum, M., & Golias, E. (2023). EMA-based Monitoring Method of Strengthened Beam-Column Joints. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 853–873). Omaha, USA: University of Nebraska at Omaha.
Abstract: Reinforced concrete (RC) beam-column joints (BCJ) are crucial structural components, primarily during seismic excitations, so their structural health monitoring (SHM) is essential. Additionally, BCJ of existing old RC frame structures usually exhibits brittle behavior due to insufficient transverse reinforcement. To alter the brittle behavior of BCJ, an innovative reinforcing technique has been employed, accompanied by a real-time SHM system. Carbon fiber-reinforced polymer (C-FRP) rope as near surface-mounted (NSM) reinforcement has been utilized as external reinforcement of the column and the joint panel. The use of piezoelectric lead zirconate titanate (PZT) transducers for real-time SHM of BCJ sub-assemblages was investigated. Statistical damage indices, such as RMSD and MAPD, were employed to quantify the damage. Furthermore, an innovative approach based on hierarchical clustering was introduced. The experiment results revealed that the damage level of the reference and the retrofitted specimens were successfully diagnosed with PZT transducers.
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Lorscheidt, J., Wehbe, B., Cesar, D., Becker, T., & Vögele, T. (2023). Increasing diver safety for heavy underwater works by Sonar-to-Video Image Translation. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 166–176). Omaha, USA: University of Nebraska at Omaha.
Abstract: Supervision of technical dives is particularly important in emergency and disaster response operations to ensure the safety of divers in unexplored locations with uncertain conditions. Diver monitoring relies primarily on voice communication and a video stream that gives the operator a first-person view of the diver. However, in many cases underwater visibility can drop to just a few centimeters, leaving the diver only able to feel his way with his hands and the operator depended only on voice communication, making it very difficult for both of them to identify upcoming hazards. In the DeeperSense research project, we are attempting to reduce the limitations caused by poor underwater visibility by using a sonar in combination with an AI-based algorithm designed to translate the sonar signal into a visual image that is independent of the turbidity of the water and gives an overview of the situation where the eye can no longer see anything. Laboratory results show that visual information can be recovered from sonar data.
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Zelenka, J., Kasanický, T. š, Gatial, E., Balogh, Z., Majlingová, A., Brodrechtova, Y., et al. (2023). Coordination of Drones Swarm for Wildfires Monitoring. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 144–151). Omaha, USA: University of Nebraska at Omaha.
Abstract: As a result of climate change and global weather patterns, large forest fires are becoming more frequent in different parts of the world. The focus of the presented work is on creation of a complex coordination and communication framework for a swarm of drones specially tailored for use in preventing and monitoring of forest fires. The presented algorithm has been testing and evaluating using a computer simulation. The testing and validation in relevant environment is scheduled during a pilot demonstration exercise with real personnel and equipment, which will take place in Slovakia on April 2023. The presented work is a part of the SILVANUS EU H2020 project, whose objective is the creation of a climate resilient forest management platform for forest fire prevention and suppression. SILVANUS draws on environmental, technical, and social science experts to support regional and national authorities responsible for forest fire management in their respective countries.
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Julian Zobel, Ralf Kundel, & Ralf Steinmetz. (2022). CAMON: Aerial-Ground Cooperation System for Disaster Network Detection. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 87–101). Tarbes, France.
Abstract: Information on large-scale disaster areas, like the location of affected civilians, is highly valuable for disaster relief efforts. This information can be collected by an Aerial Monitoring System, using UAVs to detect smart mobile devices carried by civilians. State-of-the-art systems typically rely on a purely passive detection approach. In this paper, we present a cooperative communication system between UAVs and ground-based devices to improve the detection performance of such an Aerial Monitoring System. We provide different approaches for the cooperative information collection and evaluate them in a simulated inner-city scenario. The results highlight the effectiveness of the cooperative system, being able to detect civilian devices in the disaster area faster and more comprehensively than a non-cooperative approach.
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