Developing a risk-informed decision-support system for earthquake early warning at a critical seaport

Cremen, Gemma; Bozzoni, Francesca; Pistorio, S; Galasso, Carmine

doi:10.1016/j.ress.2021.108035

Cited by 23 publications

(6 citation statements)

References 33 publications

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“…Tools were developed to process the streamed data to effectively implement an Earthquake Early Warning (EEW) and Rapid Response to Earthquake (RRE) system at the port of Gioia Tauro. By leveraging the implemented algorithms concerning the multi-component nature of the port system [37], a risk-informed Decision Support System (DSS) was delivered for mitigating earthquake impacts [38]. Costs of implementing and maintain the EEW system within the test bed was extracted from the research project's financial accounts and grouped into a range of phases and work scopes.…”

Section: Methodsmentioning

confidence: 99%

Economic appraisal standards for planning earthquake early warning infrastructure acquisition

Wanigarathna,

Jones,

Mulder

et al. 2023

IOP Conf. Ser.: Earth Environ. Sci.

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Earthquake early warning systems can reduce potential economic losses caused by earthquakes. However, they are expensive to implement and maintain, as examples from around the word show. These examples also show the challenges in accurately estimating their costs during the acquisition phase and the consequences of poor cost estimating practices. Indeed, current approaches to early cost estimates lack consistency and a well thought out structure as there are currently no established standards to support cost planning for EEW systems. This paper argues that standards for estimating capital and maintenance costs are important during the infrastructure acquisition phase to ensure the financial viability and effective cost management of earthquake early warning systems. By comparing cost estimates of selected existing EEW systems against generic economic appraisal standards and using cost data from a research project which developed and tested a new EEW system, this paper provides insights into the factors that need to be considered when estimating the capital and maintenance costs of new EEW systems. As such, it provides the foundation for the development of economic appraisal standards for EEW systems. Standards for estimating costs could help decision makers develop well thought through estimates for capital and maintenance costs for major investments such as earthquake early warning systems and, assist subsequent cost controlling activities throughout the project life cycle.

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Section: Methodsmentioning

confidence: 99%

Economic appraisal standards for planning earthquake early warning infrastructure acquisition

Wanigarathna,

Jones,

Mulder

et al. 2023

IOP Conf. Ser.: Earth Environ. Sci.

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“…The underlying infrastructure of the EEWS includes a variety of hardware and software components, including seismometers, communication networks, computing systems, and databases [168]. The seismometers are typically deployed in a dense network to ensure high spatial resolution and coverage, and they are connected to a communication network that transmits the sensor data to the processing center [169]. The processing center comprises a set of computing systems that perform real-time data analysis, using a variety of algorithms and models to estimate the earthquake parameters [170].…”

Section: Iot-cloud-based Eewsmentioning

confidence: 99%

Early Detection of Earthquakes Using IoT and Cloud Infrastructure: A Survey

Abdalzaher,

Krichen,

Yiltas-Kaplan

et al. 2023

Sustainability

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Earthquake early warning systems (EEWS) are crucial for saving lives in earthquake-prone areas. In this study, we explore the potential of IoT and cloud infrastructure in realizing a sustainable EEWS that is capable of providing early warning to people and coordinating disaster response efforts. To achieve this goal, we provide an overview of the fundamental concepts of seismic waves and associated signal processing. We then present a detailed discussion of the IoT-enabled EEWS, including the use of IoT networks to track the actions taken by various EEWS organizations and the cloud infrastructure to gather data, analyze it, and send alarms when necessary. Furthermore, we present a taxonomy of emerging EEWS approaches using IoT and cloud facilities, which includes the integration of advanced technologies such as machine learning (ML) algorithms, distributed computing, and edge computing. We also elaborate on a generic EEWS architecture that is sustainable and efficient and highlight the importance of considering sustainability in the design of such systems. Additionally, we discuss the role of drones in disaster management and their potential to enhance the effectiveness of EEWS. Furthermore, we provide a summary of the primary verification and validation methods required for the systems under consideration. In addition to the contributions mentioned above, this study also highlights the implications of using IoT and cloud infrastructure in early earthquake detection and disaster management. Our research design involved a comprehensive survey of the existing literature on early earthquake warning systems and the use of IoT and cloud infrastructure. We also conducted a thorough analysis of the taxonomy of emerging EEWS approaches using IoT and cloud facilities and the verification and validation methods required for such systems. Our findings suggest that the use of IoT and cloud infrastructure in early earthquake detection can significantly improve the speed and effectiveness of disaster response efforts, thereby saving lives and reducing the economic impact of earthquakes. Finally, we identify research gaps in this domain and suggest future directions toward achieving a sustainable EEWS. Overall, this study provides valuable insights into the use of IoT and cloud infrastructure in earthquake disaster early detection and emphasizes the importance of sustainability in designing such systems.

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“…The technical components of EEW have been widely reviewed and debated by authors such as Allen and Melgar (2019) and Cremen and Galasso (2020). Nevertheless, there is an urgent need to integrate new technology, real-time seismology methods, and engineering modelling/decision-making (see, for example, Cremen and Galasso, 2021;Cremen et al, 2022) and practices concerning the dissemination of warnings (see, for example, Alcántara-Ayala and Oliver-Smith, 2019;Herovic, Sellnow, and Sellnow, 2019;Velazquez et al, 2020). Different authors have examined people's behaviours towards and perceptions of EEW (see, for example, Nakayachi et al, 2019;Santos-Reyes, 2019), but some critical fragmentation is still associated with organisational needs, policies, and practices (Velazquez et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Integrating earthquake early warnings into business continuity and organisational resilience: lessons learned from Mexico City

Pescaroli

Velazquez²,

Alcántara-Ayala

et al. 2022

Disasters

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Earthquake early warning (EEW) is becoming a popular tool for mitigating earthquake-induced losses. However, the current literature separates the EEW's technical components and their operational and behavioural implications.This paper investigates how EEW can be integrated into business continuity practices, organisational resilience, and disaster risk reduction. We use a mixed-method approach to analyse EEW perceptions in the case study of Mexico City (Mexico), a city characterised by high seismic hazard, and social and physical exposure/vulnerability. Our dataset includes evidence from 15 semistructured interviews with representatives of the public and private sectors (e.g., governments, enterprises) and 78 valid questionnaires compiled by local organisations, including civil protection, education institutions, and enterprises.Our results reveal inconsistencies between technical EEW methodologies and their integration in three core domains of organisational practices: accountability, governance, and jurisdiction; standardisation of plans and procedures; training and education. Finally, we highlight open challenges for future research.

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Developing a risk-informed decision-support system for earthquake early warning at a critical seaport

Cited by 23 publications

References 33 publications

Economic appraisal standards for planning earthquake early warning infrastructure acquisition

Economic appraisal standards for planning earthquake early warning infrastructure acquisition

Early Detection of Earthquakes Using IoT and Cloud Infrastructure: A Survey

Integrating earthquake early warnings into business continuity and organisational resilience: lessons learned from Mexico City

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