EasyBand: A Wearable for Safety-Aware Mobility During Pandemic Outbreak

Abstract

COVID-19 (Corona Virus Disease 2019) is a pandemic which has been spreading exponentially around the globe. Many countries adopted stay-athome or lockdown policies to control its spreading. However, prolonged stay-at-home may cause worse effects like economical crises, unemployment, food scarcity, and mental health problems of individuals. This article presents a smart consumer electronics solution to facilitate safe and gradual opening after stay-at-home restrictions are lifted. An Internet of Medical Things (IoMT) enabled wearable called EasyBand is introduced to limit the growth of new positive cases by auto contact tracing and by encouraging essential social distancing.

Novel MEC Based Approaches for Smart Hospitals to Combat COVID-19 Pandemic

“…Therefore in this paper, we are proposing a MEC based edge computing approach to satisfy the intrinsic technological requisites demanded by the novel contact-less and remote medical procedures for treating COVID-19 patients within a medical facility. This work extends the reach of MEC towards adaptability established by [8], assures the claims proposed by [9], [10] to mitigate COVID-19, and validates the utilization of edge computing in IoT systems as conceptualized in [11], [12] with MEC; while improving the feasibility of smart health solutions proposed in [2], [13], [14]. The Section II introduces three futuristic use cases that effectively establish contact-less operation, while the methodology to realize these initiatives with MEC is presented in Section III.…”

The Role of Digital Technologies that Could Be Applied for Prescreening in the Mining Industry During the COVID-19 Pandemic

“…The research conducted by Rahman et al (2020) revealed that real-time data collected with IoT-based health devices were used to predict the COVID-19 outbreak with a confidence level of more than 80%. Also, the study conducted by Tripathy et al (2020) Fig. 7 Digital face shield for the mining industry to manage and control the impacts of COVID-19, source: Das (2020) Fig.…”

Technical Perspectives of Contact-Tracing Applications on Wearables for COVID-19 Control

“…For example, when a tagged user A emits a wireless signal, the receiving users in proximity could first estimate the distance based on a number of available characteristics as presented in [14]. In case the distance is lower than a predefined threshold, e.g., the value is lower than 2 m, as the safety threshold adopted by many research papers [2], [15], [16], then the receiving user will store the anonymized ID from user tagged user and the corresponding timestamps. Therefore, a ledger of neighboring users could be created per node.…”

“…Undoubtedly, P p depends on several other parameters, which are described in Fig. 2: i) the joint probability of two users found in vicinity of each other to use the same contact tracing application, e.g., with independent users and individual probability P u per user, the joint probability becomes P u *P u , ii) the false alarm P f a and misdetection P md probability of estimating that two users are within infectious distance from each other, e.g., at less than 2 m for more than 15' [2], [15], [16]), iii) the probability P c that the connectivity to the cloud server works properly, e.g., device of user A has access to long-range wireless connectivity to the server storing information about the temporary IDs of COVID-19 positive persons during their period of being infectious, and iv) the illness probability P i (i.e., the actual probability that user B gets the disease if (s)he was within infectious distance from a COVID-19 positive user A for a duration exceeding a threshold).…”

“…The Easy Band [16] is a wearable-based proximity-detection solution relying on BLE RSS distance measurements to detect nearby located users. The data is processed on a centralized server accessible via infrastructure connectivity for the decision-making process on people's infectiousness state around.…”