An Ontology Based Earthquake Recommendation System

Jain, Sarika; Mehla, Sonia; Agarwal, Akshay

doi:10.1007/978-981-13-3140-4_30

Cited by 6 publications

(12 citation statements)

References 10 publications

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“…23 In particular, they have gained significant attention in the emerging domain of crisis management. 5,6 Jain et al 5 design a recommender system that can perform case-based reasoning and rule-based reasoning supported by ontologies. This system can recommend a list of actions that help to reduce damages caused by earthquakes.…”

Section: Recommender Systemsmentioning

confidence: 99%

“…The recommender systems presented in previous works [5][6][7] aim to assist decision-makers in the optimal distribution of public resources, such as ambulances and fire trucks. However, we argue that public resources are sometimes limited and may not be located to serve all affected areas during a crisis.…”

Section: Recommender Systemsmentioning

confidence: 99%

“…Similarly, a boat owner with a capacity of six passengers could help evacuate five people in the event of a flood. Unfortunately, existing research on crisis management (e.g., evacuation simulation) 1,[3][4][5][6][7][8] has primarily focused on the use of public resources, such as ambulances 8,9 and fire trucks. 5 However, in some cases, these resources may not be available due to high demand or the remote location of the affected area.…”

Section: Introductionmentioning

confidence: 99%

“…Unfortunately, existing research on crisis management (e.g., evacuation simulation) 1,[3][4][5][6][7][8] has primarily focused on the use of public resources, such as ambulances 8,9 and fire trucks. 5 However, in some cases, these resources may not be available due to high demand or the remote location of the affected area. Furthermore, the location of public resources may also be impacted by a crisis, exacerbating the shortage of resources.…”

Section: Introductionmentioning

confidence: 99%

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Ontology-based crisis simulation system for population sheltering management

Zhong,

Ngoc,

Negre

et al. 2023

SIMULATION

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Climate change has led to an increase in the frequency and intensity of natural disasters, necessitating the development of efficient crisis management strategies for population sheltering. However, existing research on this topic primarily focuses on the use of public resources such as ambulances and fire trucks, which may sometimes be insufficient due to high demand and impacted locations, worsening the shortage of resources. This research introduces an ontology-based crisis simulation system for population sheltering management that focuses on the integration and distribution of citizen–volunteer drivers/vehicles into the evacuation process. Recognizing the limitations of public resources in current crisis management models, our approach incorporates citizen resources to enhance overall evacuation capacity. We develop an ontology to standardize crisis management knowledge, frame vehicle distribution as a recommendation problem, and design a simulation module incorporating a constraint-based recommender system. The proposed scenario illustrates how the simulation system can recommend citizen resources during crisis situations by considering the constraints to be satisfied. With our system, we aim at helping stakeholders to be prepared for various disaster scenarios: optimizing resource allocation and reducing time to make decisions by decision-makers.

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Section: Recommender Systemsmentioning

confidence: 99%

Section: Recommender Systemsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Ontology-based crisis simulation system for population sheltering management

Zhong,

Ngoc,

Negre

et al. 2023

SIMULATION

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“…Formal ontology has been developed and integrated into a rule-based and casebased reasoning system that develops recommendations based on similar cases (disaster events) from the past. Ontology has been used to manage earthquake data in intelligent systems [40]. Liu et al [41] presented a knowledge model called the geologic hazard emergency response (GHER) used for modeling emergency knowledge, which is inevitable for providing a fast emergency response during geological hazards.…”

mentioning

confidence: 99%

Tsunami-Related Data: A Review of Available Repositories Used in Scientific Literature

Nacházel

Babič

Baiguera

et al. 2021

Water

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Various organizations and institutions store large volumes of tsunami-related data, whose availability and quality should benefit society, as it improves decision making before the tsunami occurrence, during the tsunami impact, and when coping with the aftermath. However, the existing digital ecosystem surrounding tsunami research prevents us from extracting the maximum benefit from our research investments. The main objective of this study is to explore the field of data repositories providing secondary data associated with tsunami research and analyze the current situation. We analyze the mutual interconnections of references in scientific studies published in the Web of Science database, governmental bodies, commercial organizations, and research agencies. A set of criteria was used to evaluate content and searchability. We identified 60 data repositories with records used in tsunami research. The heterogeneity of data formats, deactivated or nonfunctional web pages, the generality of data repositories, or poor dataset arrangement represent the most significant weak points. We outline the potential contribution of ontology engineering as an example of computer science methods that enable improvements in tsunami-related data management.

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