Abstract

Several recent studies in Cyber-Physical Systems (CPS) focus on monitoring human movement and capturing data for further processing and analysis. However, there is a lack of studies that address the configurability and modularity of these systems, which is important for designing customized systems with customized devices. We propose a solution to solve this through a modular framework that automatically recognizes and configures new devices and provides real-time data wirelessly. The proposed framework creates a Digital Twin of the physical device and mirrors its attributes and sensory information into the cyber world so they can be used in real-time and post-routine analysis. As a proof of concept, a configurable CPS model for physical activities monitoring is designed and implemented. The designed gait monitoring and analysis system delivers spatiotemporal data from multiple multi-sensory devices to a central data handling and backup cloud server over conventional IEEE802.11 Wi-Fi. An experiment involving a young athlete examined whether or not the CPS components would recognize each other over foreign networks and communicate accurate information.

Highlights

  • Cyber-Physical Systems (CPS) became popular in recent years for the purpose of enhancing overall system performance as opposed to traditional integration of software systems and embedded computing systems or sensor networks

  • Several studies focus on health and wellbeing applications [3,4,5,6], and a percentage of these studies emphasizes on recording detailed foot kinetics and pressure points using embedded or wearable sensors

  • We introduce a CPS framework for measurement and analysis of physical activities that allows for configurability of system components

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Summary

Introduction

Cyber-Physical Systems (CPS) became popular in recent years for the purpose of enhancing overall system performance as opposed to traditional integration of software systems and embedded computing systems or sensor networks. Mukherjee et al comments on the high number of connected IoT devices, and how they can outnumber the devices connected to the internet very quickly [15] They propose a connectivity framework so that smart devices can be utilized in IoT data processing. Security Algorithm (TBSA) that enables energy-efficient data encryption based on an efficient key generation mechanism [16] Their algorithm can be used with low power Wi-Fi for smart home IoT systems to satisfy security requirements. Several surveys show different proposed frameworks in specific applications such as commercial [17], security [18], and cloud-based [19] IoT systems

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