Every cloud has a silver lining, and IEEE members from the Portugal section show us a motivating aspect of this new reality
COVID-19 has brought a series of negative aspects in our lives to a level that we are separating our behavior and habits in two categories. Pre-COVID-19 and past-COVID-19.
But as the old saying mention’s, every cloud has a silver lining, and IEEE members from the Portugal section show us a motivating aspect of this new reality. We have the technology, and new ideas are born turning to actual solutions.
Five projects were born during the hardest period of the pandemic in Portugal, providing help to those in need, but also providing technological solutions for a better and safer living during this new era.
COVID-19 What’s Open? Is a project about an interactive map of open businesses during the Emergency State in Portugal, focused on the hospitality sector, with delivery and takeaway offers. The team consists of Igor Matias and Paulo Silva, from the IEEE University of Beira Interior Student Branch.
Igor Matias shared an update about the current progress of the project. The project is concluded since the month of May, about 0,5 hours after the idea was born. Right now it is suspended, because there is no need to such platform as the things here in Portugal are quite normal. However, the platform is still available at https://covid19.starje.pt with old and not updated data, just to let people still access it.
eCoViG is an app, cloud-based eHealth platform for collection, management and visualization of physiological and clinical data for acquiring COVID-19 symptomatic measures (oximetry, temperature, heart rate, respiration). The team consists of João Sanches and Hugo Silva from the IEEE EMBS Portugal Chapter and Instituto Superior Técnico, University of Lisbon, Portugal).
João Sanches and Hugo Silva explain to us how the mobile app works. Patients undergoing e-CoVig monitoring are assigned with an unique QR code that can be used across the different components of the system (i.e. mobile and web apps). The mobile app is installed either by the patient, informal carer, or healthcare professional, and serves as the primary data collection interface. Qualitative assessment of the symptoms is performed periodically using an in-app measurement diary; self-report questionnaires enable the recording of other relevant clinical data to support the characterization of the pathology. Quantitative assessment of physiological parameters can be performed momentarily or near-continuously with the specialized wearable (when applicable). The mobile app also issues reminders and enables the patients to access historical data. All the collected data is stored locally and synchronized with the BrainAnswer cloud backend whenever an Internet connection is available. The BrainAnswer platform provides a web-app with a user-friendly eHealth dashboard through which healthcare professionals can review the status population that they are following, receive alerts for patients in which abnormal parameters are detected (e.g. hypoxia), and review the collected qualitative and quantitative data. The platform also integrated algorithms for feature extraction and risk assessment of the monitored subjects following the guidelines set forth by the Trace COVID-19 task force. For patients with enhanced risk or already diagnosed, a specialized low-cost wearable device, with wireless connectivity, and equipped with specific sensors for the COVID-19, is used assigned to the patient, enabling the recording of temperature, heart rate, and SpO2.
Contactless Temperature Detection.The project is about a device for screening people for fever before they enter public facilities prototyped with Arduino, including a medical grade infra-red sensor for low-cost temperature measurement. Pedro Brandão, from the IEEE University of Porto Student Branch, runs the project.
Zelar@CB is a system for monitoring the activity of elderly people living in isolated rural areas (who are particularly isolated due to the COVID-19 pandemic) with an wearable IoT device combined with AI to send alerts in case of falls or energy consumption unusual patterns to family members and caregivers. The team consists of Rogério Dionísio, Cassandra Jesus and Fábio Formiga from the Polytechnic Institute of Castelo Branco.
Rogério Dionísio describes how the project works and how easy it is for an old person to use it. Generally speaking, the project uses Internet of things (IoT) devices, a LoRa Network, and Artificial Intelligence algorithms to monitor indicators related to the daily activities of isolated elderly people. The objective of the project is, from one side, alert family member or caregiver for any change of habits in daily energy consumption (we use an IoT energy meter combined with AI algorithms). For example, when a TV set is left tuned on or off for a long and unusual time, the system is capable to detect it and send an SMS message or a notification to a previously authorised mobile phone; On the other side, the system monitors the elder’s falls inside and outside the house, using a wearables device (similar to a smart watch or embedded in cloths) and a LoRa Network. When a fall is detected, the system triggers an alert to a mobile phone. The proposed system is user friendly and works autonomously, that is, the elder do not need to push any button from the wearable device or need to know any technical detail form the system.
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