Use of Linked Data in the design of information infrastructure for collaborative emergency management system

Cordeiro, Kelli de Faria; Marino, Tiago Badre; Campos, María Luiza Machado; Borges, Marcos R. S.

doi:10.1109/cscwd.2011.5960204

Cited by 8 publications

(3 citation statements)

References 4 publications

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“…The Sky Guard solution is differentiating itself from CO-SEMIWA by not adopting semantic web technology in the project. On the other hand, in Cordeiro et al (2011) the proposed system is using the Linked Data´s approach in the design of information infrastructure for Collaborative Emergency Management System extensively adopting the semantic Web technology and creating teams to act in a disastrous scenario, but this solution doesn´t have been focused for mobile applications and crowdsensing technology, or using OSNs to amplify the scope of users scalability.…”

Section: Related Workmentioning

confidence: 99%

Coordinating emergency response by competent teams

Hasse¹,

Gauthier²,

Rolt³

et al. 2018

IJCSIS

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ICTs and social networks can contribute to the emergence of creating competent teams for emergency response. For example, during disasters such as Pakistan flood of 2010, Japan tsunami of 2011 and Thailand flood of 2011, On-Line Social Networks (OSNs) have served as a main technology for numerous people seeking to share information about their personal status, to request resources, or to report the status of their community. They can be used at least for three main functions: detecting emergencies, disseminating information, and managing emergencies. On the other hand, the combination of Internet and mobile technology generated smart devices with associated sensor technologies that are becoming crucial parts in delivering supports during disaster and emergency situation. However, such use of mobile devices usually requires a reliable support system from crowdsensing technologies and back-end intelligent systems. In this way, the mobile crowdsensing must be designed with focus on mechanisms to identify and localize survivors and first responders in an incident zone, as well as mechanisms for competence characterization provided by social networks to facilitate coordination for individuals as well as crowds. These main technologies, the crowdsensing and social networks combined with semantic web and ontologies can provide a complete emergency response system that is the purpose of the CO-SEMIWA platform. This platform permits an interaction among participants to create dynamically competent teams where all participants perform tasks and solve problems in a specific emergency context and situation.

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Section: Related Workmentioning

confidence: 99%

Coordinating emergency response by competent teams

Hasse¹,

Gauthier²,

Rolt³

et al. 2018

IJCSIS

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“…Identifying the geolocation of tweets is a problem that can leverage Linked Data and the Semantic Web [16]. The challenges of geolocation under this perspective are quite different.…”

Section: Introductionmentioning

confidence: 99%

A Knowledge Graph-Based Method for the Geolocation of Tweets

Lovera

Cardinale

Buscaldi

et al. 2023

Workshop Proceedings of the 19th International Conference on Intelligent Environments (IE2023)

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Twitter geolocation is useful for various purposes, including tracking COVID-19 perceptions, analyzing political trends, and managing natural disasters. However, accurately predicting geolocations based on tweet content remains a challenge. In the past, machine learning approaches have tried to solve this problem by training prediction models on previously seen data, but these models often struggle to generalize to unseen places. To overcome these limitations, in this work we present a framework based on Natural Language Processing (NLP), Knowledge Graphs (KG), and Semantic Web to find geographical entities on tweets’ content. KG facilitate the extraction of structured knowledge of texts in order to study their semantic analysis based on NLP techniques to search associated geographical coordinates to the entities of that KG; if there is explicit mention of places in the tweet, the Semantic Web is used to find geographical information associated with the entities present in the tweets’ content. To evaluate the precision of the prediction algorithm, we compare our predicted latitude and longitude coordinates with AlbertaT6 floods dataset. Our results show an F1 score up to 0.851 within a 10 kilometer radius.

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“…Nos últimos tempos, tem-se percebido com frequência que não existe uma cidade, estado ou país que possa resistir a ameaça de uma catástrofe natural, mesmo sendo ameaçados em diferentes níveis. Com isso, cada vez mais os governos e pesquisadores tem buscado mecanismos para minimizar as perdas e os danos oriundos destes tipos de eventos, conforme pode ser visto nos trabalhos de Wattegama (2007), Lage et al (2011), Cordeiro et al (2011) e De Faria Cordeiro et al (2014). Diante deste cenário, é possível perceber ainda que a preparação para catástrofes não é mais uma escolha, mas sim um caminho obrigatório, independentemente de onde se vive.…”

Section: Introductionunclassified

Relpio: uma aplicação Mobilepara auxiliar no cadastro de vítimas de catástrofes naturais

Pereira¹,

Padilha

Procópio

2016

R. Eletr. TECCEN

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A preparação para catástrofes não é mais uma escolha, mas sim um caminho obrigatório, independentemente de onde se vive. Sendo assim, desenvolver e buscar apoio em recursos tecnológicos é de extrema importância para ajudar a minimizar os impactos causados por estes eventos. Este artigo apresenta um aplicativo móvel, ainda em fase inicial, que tem como objetivo apoiar o cadastro de vítimas de catástrofes naturais e ainda, apresentar os principais meios para que a população possa ajudar estas famílias. Um cenário real de catástrofe natural ocorrido nas cidades de Paraíba do Sul e Três Rios, ambas localizadas no interior do estado do Rio de Janeiro apoiou o desenvolvimento desta solução. A aplicação desenvolvida é chamada de Relpio.

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Use of Linked Data in the design of information infrastructure for collaborative emergency management system

Cited by 8 publications

References 4 publications

Coordinating emergency response by competent teams

Coordinating emergency response by competent teams

A Knowledge Graph-Based Method for the Geolocation of Tweets

Relpio: uma aplicação Mobilepara auxiliar no cadastro de vítimas de catástrofes naturais

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