A Literature Review on the Development and Creation of Digital Twins, Cyber-Physical Systems, and Product-Service Systems

Digital Twins offer vast potential, yet many companies, particularly small and medium-sized enterprises, hesitate to implement them. This hesitation stems partly from the challenges posed by the interdisciplinary nature of creating Digital Twins. To address these challenges, this paper explores systematic approaches for the development and creation of Digital Twins, drawing on relevant methods and approaches presented in the literature. Conducting a systematic literature review, we delve into the development of Digital Twins while also considering analogous concepts, such as Cyber-Physical Systems and Product-Service Systems. The compiled literature is categorised into three main sections: holistic approaches, architecture, and models. Each category encompasses various subcategories, all of which are detailed in this paper. Through this comprehensive review, we discuss the findings and identify research gaps, shedding light on the current state of knowledge in the field of Digital Twin development. This paper aims to provide valuable insights for practitioners and researchers alike, guiding them in navigating the complexities associated with the implementation of Digital Twins.

An Inexpensive Unmanned Aerial Vehicle-Based Tool for Mobile Network Output Analysis and Visualization

Usage of Unmanned Aerial Vehicles (UAVs) for different tasks is widespread, as UAVs are affordable, easy to manoeuvre and versatile enough to execute missions in a reliable manner. However, there are still fields where UAVs play a minimal role regardless of their possibilities. One of these application domains is mobile network testing and measurement. Currently, the procedures used to measure the main parameters of mobile networks in an area (such as power output or its distribution in a three-dimensional space) rely on a team of specialized people performing measurements with an array of tools. This procedure is significantly expensive, time consuming and the resulting outputs leave a higher degree of precision to be desired. An open-source UAV-based Cyber-Physical System is put forward that, by means of the Galileo satellite network, a Mobile Data Acquisition System and a Graphical User Interface, can quickly retrieve reliable data from mobile network signals in a three-dimensional space with high accuracy for its visualization and analysis. The UAV tested flew at 40.43 latitude and -3.65 longitude degrees as coordinates, with an altitude over sea level of around 600-800 m through more than 40 mobile network cells and signal power displayed between -75 and -113 decibels.

Scalable Fleet Monitoring and Visualization for Smart Machine Maintenance and Industrial IoT Applications

The wide adoption of smart machine maintenance in manufacturing is blocked by open challenges in the Industrial Internet of Things (IIoT) with regard to robustness, scalability and security. Solving these challenges is of uttermost importance to mission-critical industrial operations. Furthermore, effective application of predictive maintenance requires well-trained machine learning algorithms which on their turn require high volumes of reliable data. This paper addresses both challenges and presents the Smart Maintenance Living Lab, an open test and research platform that consists of a fleet of drivetrain systems for accelerated lifetime tests of rolling-element bearings, a scalable IoT middleware cloud platform for reliable data ingestion and persistence, and a dynamic dashboard application for fleet monitoring and visualization. Each individual component within the presented system is discussed and validated, demonstrating the feasibility of IIoT applications for smart machine maintenance. The resulting platform provides benchmark data for the improvement of machine learning algorithms, gives insights into the design, implementation and validation of a complete architecture for IIoT applications with specific requirements concerning robustness, scalability and security and therefore reduces the reticence in the industry to widely adopt these technologies.