| dc.description.abstract | The constant advances in mobile and ubiquitous computing enable new developments and new features in different areas, among thesethe health area stands out. From these new possibilities comes the concept of Ubiquitous Care, where these new resources are applied in order to provide better conditions for doctors and medical staff in the treatment of patients. Using the concept of ubiquitous care as a reference, the present work presents a new approach for monitoring patients through the use of Situation Awareness, supported by the use of Fuzzy Logic, Artificial Neural Networks and Time Series, also with patient data collected through mobile devices and wearable devices. The SAC - Situation-Aware Care model aims to apply the three phases of situation awareness - perception, comprehension and projection - using the data collected as inputs to the inferences. Aiming to provide a solution that assists physicians and medical teams in diagnostics - and prognoses - more assertive, through the monitoring and availability of records and more accurate information regarding the patient's health status.For the evaluation of the model, prototypes were developed for the SAC Services and the SAC4Mobile application. The SAC model had its evaluation in relation to its service performance and also through an extended use case, assessing the usability. Performance evaluations presented good indicators of response times and computational resources, where the highest time for the return of all the requests, 100 simultaneous requests, was 5.5 seconds and the consumption of computational resources did not exceed 18%. As well as the assessment of usability had positive results highlighting the relevance of the SAC model proposal. | en |
