O GIHC comemora mais uma importante publicação internacional, desta vez no evento FUSION (20th International Conference on Information Fusion).

A Conferência Internacional sobre Informação – FUSION é um fórum privilegiado para o intercâmbio das mais recentes pesquisas em fusão de informação e discussão de seus impactos em nossa sociedade. A conferência reúne pesquisadores e profissionais da indústria e da academia para informar os últimos avanços científicos e técnicos. Os autores são convidados a enviar artigos descrevendo avanços e aplicações na fusão de informações.

A 20ª Conferência Internacional sobre Fusão de Informação (FUSION 2017)  foi realizada em Xi’an, China, de 10 a 13 de julho de 2017.

Resumo do artigo: Situational Awareness (SAW) is a widespread concept in areas that require critical decision-making and refers to the level of consciousness that an individual or team has about a situation. A poor SAW can induce humans to failures in the decision-making process, leading to losses of lives and property damage. Data fusion processes present opportunities to enrich the knowledge about situations by integrating heterogeneous and synergistic data from different sources and transforming them into more meaningful subsidies for decision-making. However, a problem arises when information is subject to problems concerning its quality, especially when humans are the main sources of data (HUMINT). Motivated by the informational demand from the emergency management domain and by the limitations and challenges of the state of the art, this work proposes and describes a new information fusion model, called Quantify (Quality-aware Human-Driven Information Fusion Model), whose main contribution is the exhaustive use of the quality information management throughout the fusion process to parameterize and to guide the work of humans and systems. To validate the model, an emergency situation assessment system prototype was developed, called ESAS (Emergency Situation Assessment Systems). Then, experts from the Sao Paulo State Police (PMESP) tested the prototypes and the system was evaluated using SART (Situation Awareness Rating Technique), which showed higher rates of SAW using the Quantify model, compared to the model from the state-of-the-art, especially in questions relating to the components of resource supply and situational understanding.

AutoresLeonardo C. Botega  A. P. Valdir  Allan C. M. Oliveira  Jordan F. Saran  Leandro A. Villas  Regina B. de Araújo

Acesse o artigo: http://ieeexplore.ieee.org/document/8009851/

 

20th International Conference on Information Fusion (FUSION 2017)

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