In this paper, a novel Edge-IoT framework is proposed which interconnects the user's smartphones with the robotic system for human-robot interaction. The user sends speech commands using mobile application which is processed by the framework and sent to the robotic system. The robotic system executes the task and sends a completion message to the user through the framework. Preliminary experiments conducted by sending multiple requests to the framework to perform a robotic task showed that the framework is able to handle multiple requests, send commands to the robotic system to perform the robotic task and send completion messages to the user efficiently.

Covid Wizard or CoWiz is a Covid-19 visualization dashboard based on Multilayer Network (MLN) analysis underneath1. Online dashboards typically plot/visualize statistical information gleaned from raw data, such as daily cases, deaths, recoveries, tests, etc. However, for a better understanding, we need aggregate analysis (e.g., community, centrality) and its visualization which is the purpose of CoWiz. As an example, grouping counties across a country/region based on similarity of increase/decrease in cases, deaths, hospitalizations over intervals is not possible without aggregate analysis. This is where CoWiz utilizes community and other concepts over MLNs that are inferred from Covid and other relevant data sets for visualization.This demo presents a flexible, interactive dashboard which is capable of visualizing various aspects of Covid-19 data, including composition of Covid data with demographics (population density, education level, average earning, vehicle movements, and change in purchase patterns) at the granularity of county for USA. This paper elaborates on the types of analysis, underlying model, and how a flexible visualization dashboard has been developed using open source software and data sets. As new data becomes available, they can be incorporated into the visualization with no manual intervention.