Assessing Situation Awareness on Fusion-Driven Emergency Management Systems

• Autor(a) principal: Botega, Leonardo C. [UNESP]
• Data de Publicação: 2019
• Outros Autores: Pereira, Gustavo M. C. [UNESP], Junior, Valdir A. P. [UNESP], Oliveira, Allan C. M. de, IEEE
• Tipo de documento: Artigo de conferência
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://hdl.handle.net/11449/209446
• topic: Data and Information Fusion; Information Quality Management; Situation Awareness

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). This work describes the assessment of situation awareness provided by an emergency situation assessment system (ESAS), build based on the principles of a new information fusion model. Experts from the Sao Paulo State Police (PMESP) evaluated ESAS using SART methodology (Situation Awareness Rating Technique), which showed higher rates of SAW, compared to another system, based on the state-of-the-art high-level fusion model, especially in questions relating to the components of informational supply and situational understanding.