51 research outputs found

    Open IOT-based telemedicine hub and infrastructure

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    In this paper, a unique healthcare solution is described that supports the even more effective operation of the hospital information systems. The main question is whether the emerging opportunities of the Internet of things devices can also be exploited in the industrial hospital information system landscape. This demonstrated research describes the most feasible way to integrate the Internet of things capability into hospital information production systems. The initial goal was the design and implementation of a single, unified telemedicine hub offering community-based solution for integrated medical systems. This solution allows the intercepted information to be collected and interpreted at community level. The designed and implemented system acts as a transmitter between the physician and patient. The software solution operates with sensor-based information collected from the individual. Emerging Internet of things devices and solutions open new horizons for today’s health care systems. The presented and detailed system provides the ability to real-time health-monitoring and in-depth health analyzing through open application programming interfaces. The telemedicine hub system makes it easier to integrate the Internet of things capability into the operating health care systems

    Doktori Iskolák egy információs rendszere

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    Ügyfélkapu azonosítás használata oktatási környezetben

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    Ügyfélkapu azonosítás használata oktatási környezetben

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    Cikkünkben a központosított oktatáshoz kapcsolódva egy új oktatási azonosító bevezetésének lehetőségét szeretnénk bemutatni. A megoldásunkhoz korábbi kutatásaink eredményei szolgáltatták az alapot. Célunk nem kizárólagosan elvetni a már meglévő törekvéseket, mint például az eduID szolgáltatás, hanem elsőként egy már működő infrastruktúra bevonásának lehetőségét megvizsgálni, másodsorban pedig egyfajta továbbfejlesztési irányt mutatni az említett eduID tekintetében. Az elkészített tanulmányunkban megfogalmazott hipotézisek alátámasztását egy felméréssel kívánjuk alátámasztani, mely nagymértékben igazolja is feltételezéseinket

    The human DNA can be the bridge between the Human and its data set in the Future

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    In our research, we are designing the abstract models of the global, centralized user authentication infrastructure. The user has only one trusted profile and a globally unique ID in the infrastructure. In this infrastructure model, we would like to support the cooperation among existing authentication providers. They can connect to the infrastructure if they comply with the common conditions. To identify a person in a trusted way, we have to relate the physical person to its digital data with a trusted method. Nowadays, this trusted method is the facial image of the person. Unfortunately, the biometric properties are very damageable, so a general biometric property based databank is also very damageable. In this paper, we would like to describe our possible solution based on the Human DNA for this problem

    eHealth and Smart Solutions framework for health monitoring in the course of the pandemic

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    Our main objective focuses on the different design principles for applications that can receive and store various data from smart devices, e.g., smart bands, smart watches, and smart homes, and could gain more information about its users to some extent to their health. We would like to collect this information, store it, then create understandable diagrams and show them to the user in a modern, responsive environment. We placed great emphasis on the underlying architecture, which holds the necessary features (scalability and extensibility). We have followed the design process’s standards, recommendations, and protocols. The result is an application framework that fulfills the duty of an XXI. century smart solutions application that could monitor people’s health and even help them live healthier lives by avoiding chronic disorders, e.g., obesity and/or diabetes. We focused on predicting and classifying COVID-19 disease according to the collected information and research
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