Avances en el diseño de sistemas ciber-físicos y modelos digitales gemelos para la sociedad 4.0

Abstract

n the digital era, Cyber-Physical Systems (CPS) and Digital Twin (DT) models have become central elements of technological innovation, significantly impacting sectors such as industry, agriculture, medicine, architecture, and robotics. By integrating physical systems with communication and computing technologies, CPS and Digital Twins enable the realtime extraction, processing, and synthesis of vast data, improving process optimization, problem-solving, and overall efficiency. CPSs bridge the physical and digital worlds. These systems collect and process data, enabling real-time adaptations to environmental changes. Digital Twins extend the functionality of CPSs by creating real-time digital replicas of physical systems. This allows for enhanced monitoring, simulation, optimization, and control, anticipating future issues. Together, CPSs and their evolution into Digital Twins offer transformative potential in areas such as autonomous vehicles, smart building management, and robotics in healthcare. This Doctoral Thesis poses the following research question: Can integrating Cyber-Physical Systems technologies, supported by Digital Twin models, address specific challenges of Society 4.0, such as optimizing resource usage and improving safety, comfort, and efficiency in smart environments and vehicles? The hypothesis suggests that the combination of CPS with Digital Twins could provide solutions to many current societal concerns, such as optimizing the use of resources like energy and water in smart buildings, the use of robots in human environments, and enhancing safety in autonomous vehicle driving. The research was conducted through several phases, including the formal definition of the problem, sensorization of each scenario, integration of various communication protocols, creation of a virtual world integrated into a flexible and scalable architecture, and the final use of data acquired from the physical world for visualization and post-processing. These efforts culminate in real-world case studies involving autonomous vehicles, social robots in smart care homes, and sustainable building management, validating the proposed solutions. As part of the RoboLab research group at the University of Extremadura, this work builds upon significant prior contributions, such as the CORTEX cognitive architecture for decision-making, the SmartPoliTech project for sustainable campus management, and a custom navigation stack for an autonomous vehicle with 5G connectivity. This Thesis is a compilation of previously published high-impact articles, laying the foundation for advancing CPS and Digital Twin technologies and their application in smart environments. The included works cover risk prediction during autonomous vehicle navigation, energy optimization in smart buildings, water consumption management in smart campuses, and assistive robotics in caregiving centers. These contributions pave the way for developing robust and efficient systems in various contexts within Society 4.0.