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The wearables' market is rapidly evolving, with applications ranging from healthcare and activity monitoring to emerging domains such as drones and haptic helmets. Wearable-based contact tracing is gaining increased attention in the COVID-19 era for more efficient disease prevention. Therefore, it is of timely relevance to identify the leading existing wireless contact-tracing solutions and their suitability for wearables. Existing trade-offs of contact-tracing applications require a thorough analysis of technical capabilities, such as accuracy, energy consumption, availability, sources of errors when dealing with wireless channels, privacy challenges, and deterrents towards a large-scale adoption on the wearables market. Based on extensive literature research, we conclude that decentralized architectures generally offer a better place in a trade-off in terms of accuracy and user eagerness to adopt them, taking into account privacy considerations, compared to centralized approaches. Our paper provides a brief technical overview of the existing solutions deployed for contact tracing, defines main principles that affect the overall efficacy of digital contact tracing, and presents a discussion on the potential effect of wearables in tackling the spread of a highly contagious virus. acceptedVersion Peer reviewed

The world population currently counts more of 617 million people over 65 years old. COVID-19 has exposed this population group to new restrictions, leading to new difficulties in care and assistance by family members. New technologies can reduce the degree of isolation of these people, helping them in the execution of healthy activities such as performing periodic sports routines. NAO robots find in this a possible application; being able to alternate voice commands and execution of movements, they can guide elderly people in performing gymnastic exercises. Additional encouragement could come through demonstrations of the exercises and verbal interactions using the voice of loved ones (for example, grandchildren). These are transmitted in real time to the NAO which streams the video of older people exercising, bringing the two parties involved closer together. This proposal, realized with the robot NAO V6, allows to have a help at home ready to motivate, teach the exercises and train the elderly living alone at home.

The recent COVID-19 emergency has pointed out the importance of effective and efficient tools to support users in their day-by-day activities, ranging from health-related ones to studying, remote working and recreation. Indeed, wearables and modern network technologies, such as network slicing and SDWAN, play a key role in this scenario, but existing applications should be rethought to be really useful in critical situations like the current pandemic. In this paper, we reflect about this topic, trying to design an innovative architectural framework where Wearable Expert Systems, IoT and network infrastructures are integrated to obtain the best level of performance.

In this innovative practice full paper we present the implementation of the distant laboratory for the Internet of Things teaching and training. The recent outbreak of the SARS-COV-2 virus and related COVID-19 pandemic throughout the world has caused governments across the world to shut down schools and universities, to slow down the spread of the coronavirus that is causing the disease. As a result, some universities and schools have switched from physical classrooms to virtual or online classrooms. This approach is working well for theoretical subjects and courses, but it is not straight forward in the case of laboratory subjects and courses that require access to hardware resources. The IOT-OPEN.EU remote laboratory infrastructure presented in this paper is a timely solution. In this paper, we present current advances in distant learning, distant laboratory models, and the IOT-OPEN.EU remote laboratory implemented as part of the IOT-OPEN.EU ERASMUS+ project, along with short analysis on current advances in distant learning, where students are interacting with physical hardware remote way.