Visual Analysis Tool for a BLE Technology based Tracking Data

Several systems deal with human mobility. Most of them are for outdoor environments and use mobile phones to capture data. However, there is a growing interest of enterprises to consider indoor movement to take employees and client classes into account. Moreover, they usually want to assign semantics to the visited locations. We propose a visual exploration tool for analyzing the dynamics of individual movements in an indoor environment in this work. We present the use of suitable charts and animations to explore these complex data better. Finally, we argue that one could use our solution to monitor social distancing in indoor environments, which is a sensible thing during the current COVID-19 pandemic. Copyright © 2021 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved.

IoT-Based COVID-19 Health Monitoring System: Context, Early Warning and Self-Adaptation

The Internet of Things (IoT) has enabled novel solutions for monitoring patients' health through wearable sensors in conditions of both non-communicable and infectious diseases. In this paper, we report work in progress involving the development of an IoT-based COVID-19 health monitoring system that can effectively monitor the essential physiological functions of a patient through wireless sensors, thus supporting the early detection of severe cases and the continuous assessment of the patient status. The work provides several main contributions, as it includes: (i) a brief description of the current IoT-based system for remote monitoring of COVID-19 patients;(ii) a description of embedded characteristics of our device, including its contextual functions, early warning score mechanisms and self-adaptive features;and (iii) a description of our preliminary experiment results. Our proposed solution reduced drastically the amount of redundancy in data and still maintain monitoring accuracy. Given the COVID-19 scenarios, in which human resources are extended to the limit and the number of patients in severe conditions is often high, a system that can support IoT-based continuous monitoring are essential to identify changes in clinical status promptly and accurately and can potentially transform the way patients are monitored. © 2021 IEEE.

Yet another BLE technology based tracking system

There are numerous systems for analyzing human mobility for outdoor environments at the scale of large regions or entire cities. Most of them use mobile phones to capture data information. However, these systems are agnostic to a specific business field, do not consider indoor movement, do not take into account the participants' employee or client category, and usually do not assign semantics to the visited locations. In this work, we first developed a low-cost tracking system to detect, collect, process, and store users' movement and presence data in indoor environments. Such an approach takes into consideration the users' category and location semantic. We collected these data in two university buildings used by faculty, staff, and students. We suggest that our work could monitor social distancing in indoor environments due to its human presence detection capability, whenever required, such as for the COVID-19 pandemic. © 2021 Owner/Author.