Model-Based Engineering of Collaborative Embedded Systems Extensions of the SPES Methodology
Material type:
ArticlePublication details: Springer Nature Springer [Imprint] 2021Description: 1 electronic resource (404 p.)Content type: - text
- computer
- online resource
- Economics, Finance, Business and Management
- Business and Management
- Business mathematics and systems
- Technology, Engineering, Agriculture, Industrial processes
- Transport technology and trades
- Automotive technology and trades
- Computing and Information Technology
- Computer programming / software engineering
- Software Engineering
- Computer science
- Artificial intelligence
- Expert systems / knowledge-based systems
- Automotive (motor mechanic) skills
- Automotive Engineering
- Automotive Software Engineering
- Automotive technology & trades
- Business applications
- Business mathematics & systems
- Co-Design of Systems
- Embedded Systems
- Expert systems
- IT in Business
- Model-Driven Software Development
- Open Access
- Requirements Engineering
- SPES Methodology
- Simulation
- Software Engineering
- Software Management
- Special Purpose and Application-Based Systems
- knowledge-based systems
Open Access Unrestricted online access star
This Open Access book presents the results of the "Collaborative Embedded Systems" (CrESt) project, aimed at adapting and complementing the methodology underlying modeling techniques developed to cope with the challenges of the dynamic structures of collaborative embedded systems (CESs) based on the SPES development methodology. In order to manage the high complexity of the individual systems and the dynamically formed interaction structures at runtime, advanced and powerful development methods are required that extend the current state of the art in the development of embedded systems and cyber-physical systems. The methodological contributions of the project support the effective and efficient development of CESs in dynamic and uncertain contexts, with special emphasis on the reliability and variability of individual systems and the creation of networks of such systems at runtime. The project was funded by the German Federal Ministry of Education and Research (BMBF), and the case studies are therefore selected from areas that are highly relevant for Germany's economy (automotive, industrial production, power generation, and robotics). It also supports the digitalization of complex and transformable industrial plants in the context of the German government's "Industry 4.0" initiative, and the project results provide a solid foundation for implementing the German government's high-tech strategy "Innovations for Germany" in the coming years.
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Creative Commons Licence http://creativecommons.org/licenses/by/4.0/ by cc
eng
Freely available e-book