ABSTRACT
The combination of pervasive sensing and multimedia understanding with the advances in communications makes it possible to conceive platforms of services for providing telehealth solutions responding to the current needs of society. The recent outbreak has indeed posed several concerns on the management of patients at home, urging to devise complex pathways to address the Severe Acute Respiratory Syndrome (SARS) in combination with the usual diseases of an increasingly elder population. In this paper, we present TiAssisto, a project aiming to design, develop, and validate an innovative and intelligent platform of services, having as its main objective to assist both Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) multi-pathological patients and healthcare professionals. This is achieved by researching and validating new methods to improve their lives and reduce avoidable hospitalisations. TiAssisto features telehealth and telemedicine solutions to enable high-quality standards treatments based on Information and Communication Technologies (ICT), Artificial Intelligence (AI) and Machine Learning (ML). Three hundred patients are involved in our study: one half using our telehealth platform, while the other half participate as a control group for a correct validation. The developed AI models and the Decision Support System assist General Practitioners (GPs) and other healthcare professionals in order to help them in their diagnosis, by providing suggestions and pointing out possible presence or absence of signs that can be related to pathologies. Deep learning techniques are also used to detect the absence or presence of specific signs in lung ultrasound images. © 2022 IEEE.
ABSTRACT
Atenea is the Moodle virtual platform of the Universitat Politècnica de Catalunya (UPC) with about 31000 users and 5000 active subjects from 16 school centers. Atenea indicators give information on the teaching activity of the users and centers. This is specially relevant when teaching is online, as was the case in the Covid-19 period. The UPC already has a Atenea's Bussines Intelligent platform (BI), which has recently been launched. In this 1st phase the Institute of Science of Education (ICE) has actively participated in the design of the application. Currently it shows basic indicators over a period of time where one can filter or compare by centers or type of users. The paper presents this design and make a proposal for the extension of the BI, for the future, with respect to: 1) the inclusion of some key indicators for measuring the subjects' activity, 2) a proposal for cross-referencing data with academic performance. © 2022 SEFI 2022 - 50th Annual Conference of the European Society for Engineering Education, Proceedings. All rights reserved.