Jendreck, M., Hellriegel, J., Allmann, J., Restel, H., Pfennigschmidt, S., Meissen, U., et al. (2023). ROBUST communication platform – A decentralized, distributed communi cation platform for the earthquake early warning system ROBUST. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 822–836). Omaha, USA: University of Nebraska at Omaha.
Abstract: Strong earthquakes of great intensity pose a severe threat to human life and property. Earthquake early warning systems are designed to give people in endangered areas valuable seconds to save their lives and property. The basis of an efficient warning system is a communication infrastructure that provides high-speed and reliable communication between the components of the warning system. This paper presents the distributed, decentralized communication platform for the ROBUST project. It discusses the key challenges and requirements such as resilience, real-time capability and target group-specific information distribution that are placed on such a communication platform. In addition, it presents the conception of the communication platform, which is based on a subscriber procedure between autonomous, decentralized peers (nodes), in order to be able to realize the requirements. Finally, it details the technical implementation, practical realization, and evaluation of the communication platform.
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Sterl, S., Almalla, N., & Gerhold, L. (2023). Conceptualizing a Pandemic Early Warning System Using Various Data: An Integrative Approach. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 284–294). Omaha, USA: University of Nebraska at Omaha.
Abstract: Covid-19 demonstrated the vulnerability of various systems and showed, however, that digital tools and data can serve not only to stop infections but also to detect viruses before or immediately after a zoonosis has occurred, thus preventing a potential pandemic. Although several pandemic early warning systems (P-EWS) and German pandemic-related projects (G-PRP) exist, they often use a limited data range or rely on third-party data. Here, we present a concept of an integrative pandemic early warning system (IS-PAN) applied to Germany using various data such as health data (e.g., clinical/syndromic) or internet data (e.g., social media/apps). Based on a systematic literature research of P-EWS and G-PRP on scientific and public health platforms, we derived indicators that help to detect virus threats with a system consisting of modules monitored in parallel. By integrating various pre collected digital data, this approach can help to identify a potential health threat efficiently and effectively.
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Benjamin Hong, Chanthujan Chandrakumar, Danuka Ravishan, & Raj Prasanna. (2023). A Peer-to-Peer Communication Method for Distributed Earthquake Early Warning Networks: Preliminary Findings. In V. L. Thomas J. Huggins (Ed.), Proceedings of the ISCRAM Asia Pacific Conference 2022 (pp. 111–116). Palmerston North, New Zealand: Massey Unversity.
Abstract: This work-in-progress paper presents preliminary findings of ongoing research into alternative peer-to-peer (P2P) communication methods for earthquake early warning (EEW) systems. It expands upon previous work (Prasanna et al., 2022) that explores a network architecture for a decentralised EEW system. This paper explores using Quick UDP Internet Connections (QUIC) over a hole-punched UDP tunnel as a potential alternative to a Software-Defined Wide Area Network (SD-WAN) for peer-to-peer networking in an experimental EEW network architecture. The performance of QUIC is tested and compared to TCP over ZeroTier, an SD-WAN chosen as a P2P communication method in the previous work, over a realistic network topology. The results show that QUIC can outperform TCP over ZeroTier. Future work is needed to produce a method suitable for actual use in an EEW system. This paper contributes to the EEW literature by introducing a new method of communication tailored for EEW.
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Chanthujan Chandrakumar, Raj Prasanna, Max Stephens, Marion Lara Tan, Caroline Holden, Amal Punchihewa, et al. (2023). Algorithms for Detecting P-Waves and Earthquake Magnitude Estimation: Initial Literature Review Findings. In V. L. Thomas J. Huggins (Ed.), Proceedings of the ISCRAM Asia Pacific Conference 2022 (pp. 138–155). Palmerston North, New Zealand: Massey Unversity.
Abstract: Earthquake Early Warning System (EEWS) plays a major role during an earthquake in alerting the public and authorities to take appropriate safety measures during an earthquake. Generally, EEWSs use three types of algorithms to generate alerts during an earthquake; namely: source-based, ground motion or wavefield-based and on-site-based approaches. However, source-based algorithms are commonly used in most of EEWSs worldwide. A source-based EEWS uses a particular time frame of the P-wave of an earthquake to estimate the source parameters such as magnitude and the location of that earthquake with the support of P-wave detection and earthquake magnitude and location estimation algorithms. As the initial step of a research project which aims to explore the best use of P-waves to generate earthquake alerts, this Work in Progress paper (WiPe) presents the initial partial findings from an ongoing literature review on exploring the algorithms used for P-wave detection and earthquake magnitude estimation.
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Samuel Auclair, Pierre Gehl, Mickael Delatre, Christophe Debray, & Philippe Méresse. (2022). In-depth Analysis of Practitioners' Perceptions about Seismic Early Warning Prior to Aftershocks: The Point of View of the USAR Community. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 740–754). Tarbes, France.
Abstract: Urban Search and Rescue (USAR) teams are particularly exposed to the risk of collapse of buildings due to aftershocks, making concept of earthquake early warning (EEW) particularly interesting. In addition to scientific advances in EEW, it is crucial to understand what are the real expectations and needs of USAR teams, and to what extent EEW solutions could meet them. In this study, we conduct a survey to collect insights from USAR rescuers: it highlights that aftershocks are a major concern for them. In this context, we find that the concept of EEW is very favorably received by the respondents, who consider different types of possible actions upon receipt of an early warning. This study provides a basis for the functional specifications of future solutions of EEW useful to all USAR teams, as well as for the definition of their modalities of engagement on the field.
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