Cyber-physical energy systems (CPES) describe a specialization of the cyber-physical system concept, in which energy systems are transformed into intelligent energy networks. These systems provide the basis for the realization of smart microgrids and smart grids. In the last decade, numerous research projects have intensively explored the fundamentals and modeling of CPES and validated them in pilot projects. In the meantime, more and more CPES solutions have been appearing on the market and the battle for the most suitable standards has begun. This paper gives an overview of the currently available standards for CPES sensor technologies and assesses the suitability for implementation. In two case studies in the application area of operational energy management in German companies, a sensor retrofitting is described—once with proprietary technology and once using the standards Long Range (LoRa) Wide Area Network and OPC Unified Architecture (OPC UA). As a result, the shortcomings of the standards for their use in CPES are shown and discussed. OPC UA, which was originally developed for the manufacturing industry, turns out to be to be a suitable standard for a wide range of CPES implementations.

Integrated Engineering consists of 3 modules:

The automotive industry is undergoing a profound transformation driven by technological innovations, such as electrification, autonomous driving systems, digitalization, and the shift toward mobility services. This transformation is further intensified by new competition from the IT sector, industrial policy objectives, particularly from China, and the increasing automation and connectivity of manufacturing processes. In addition, environmental regulations, evolving consumer preferences, and advancements in artificial intelligence (AI) play a crucial role in shaping the industry’s future. This study aims to identify and analyze the key technological drivers contributing to the transformation of the automotive sector. Using a systematic literature review based on the approach outlined by vom Brocke et al., a structured and reproducible analysis of the relevant literature is conducted. The findings indicate that technological drivers, such as connectivity, autonomous driving, electrification, and digitalization are crucial to this transformation. Furthermore, supporting technologies such as AI, cloud computing, and big data analytics are critical enablers of this transformation. A deep understanding of these drivers is essential for industry stakeholders, policymakers, and researchers to anticipate future developments, address emerging challenges and develop effective strategies for sustainable and competitive mobility solutions. This study contributes to the ongoing discourse on transformation and its implications for the future of the automotive industry.

This paper focuses on quantifying the economic and financial viability of NB-IoT and LoRaWAN technologies, two low-power wide-area network (LPWAN) technologies with unique characteristics that make them suitable for IoT applications. The purpose of this study is to propose a “pragmatic” artifact for performing life cycle cost analysis and demonstrate its application to these technologies. The methodology uses pragmatic computational tools to facilitate the analysis and considers all relevant economic and financial factors, such as operating costs, equipment costs, and revenue potential. The main finding of this study is that Narrow Band-Internet of Things (NB-IoT) and Long Range Wide Area Network (LoRaWAN) technologies have different cost structures and revenue potentials, which may affect their economic and financial viability for different IoT applications. Ultimately, the study concludes that a comprehensive life cycle cost analysis is critical to making informed decisions about technology adoption, and that the proposed methodology can be applied to other IoT technologies to gain insight into their economic and financial viability.