Pettersson, M. N., Axelsson, J., Svenson, P., & Johansson, A. (2023). Towards a Risk Analysis Method for Systems of Systems: A Case Study on Wildfire Rescue Operations. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 530–545). Omaha, USA: University of Nebraska at Omaha.
Abstract: Crisis management (CM) is facing new challenges due to the increasing complexity of contemporary society. To mitigate a crisis, it is often necessary for a collection of independent systems, people, and organizations to cooperate. These collaborating entities constitute an interconnected socio-technical system of systems (SoS). An important question is how a CM SoS should be constructed to minimize the risk of failure and accurately handle a crisis. SoS pose new challenges in analysing risk during interactions. This paper investigates whether the risk analysis method STAMP (System-Theoretic Accident Model and Processes) is suitable for SoS, using a forest fire rescue operation case study. Results show characteristics of various risk sources and identify some SoS characteristics, such as dynamic structure and latent risks, that are not sufficiently handled in STAMP. The study further contributes to the body of knowledge by presenting potential directions for research on SoS risk assessment methods.
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Shada Alsalamah, Hessah Alsalamah, Jaziar Radianti, Sakher Alqahtani, Thamer Adnan Nouh, Mohamed Abomhara, et al. (2018). Information Requirements for Disaster Victim Identification and Emergency Medical Services:Hajj Crowd Disaster Case Study. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 861–873). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Disturbing crowd disaster incidents have been witnessed in every corner of the planet, which often lead to extensive difficulties, especially when they involve mass multi-nation casualties. When conducting Disaster Victim Identification (DVI) tasks, starting from finding the missing, curing the injured, and identifying the deceased, the challenge in such disasters is the lack of information to provide Emergency Medical Services (EMS) and conduct DVI in a timely manner. The literature presents fragmented solutions that can equip either post-mortem DVI or EMS with solutions to facilitate data collection and dissemination, but they do not consider a holistic solution that allows access to the victims' right information when needed. In this paper, we analyze information needs across multi-disciplines, as well as the requirements for technical support that can help manage the identification process. Recommendations should lay a sound foundation for future multi-disciplinary research in the areas of DVI, EMS, crowd disaster, health informatics, information security and software engineering in the health sphere.
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Zeleskidis, A., Chalarampidou, S., Dokas, I. M., & Torra, F. (2023). COBOT Safety Awareness: A RealTSL Demonstration in a Simulated System. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 874–891). Omaha, USA: University of Nebraska at Omaha.
Abstract: This work aims to propose the RealTSL methodology to empower collaborative robotic systems with self-safety awareness capability and address the methodology's limitation in determining time ranges for the unsafe system state transitions, which are inputs of the methodology. The COBOT system used in this paper to demonstrate RealTSL is an automated scissor lift robot to be used by first responders for “work at height,” simulated in Simulink™. The demonstration begins by 1) applying STPA to the system, 2) applying Early Warning Sign Analysis based on STAMP (EWaSAP), 3) creating an acyclic diagram that depicts system state transitions towards unsafe states, 4) incorporating the appropriate sensory equipment in the simulation, 5) simulating the system's operation for different scenarios using fault injection and finally 6) use information from the simulations to complete the RealTSL analysis and calculate the safety level of the system in real-time during its simulated operation.
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