Related papers: Towards Industry 4.0: Gap Analysis between Current…
The Industrial Internet of Things (IIoT) paradigm has emerged as a transformative force, revolutionizing industrial processes by integrating advanced wireless technologies into traditional procedures to enhance their efficiency. The…
Adoption of state-of-art Generative Artificial Intelligence (GenAI) aims to revolutionize many industrial areas by reducing the amount of human intervention needed and effort for handling complex underlying processes. Automotive software…
The aim of this paper is to propose a rigorous and complete design framework for complex system based on system engineering (SE) principles. The SE standard EIA-632 is used to guide the approach. Within this framework, two aspects are…
This study explores the state-of-the-art, application, and maturity of socio-technical security models for industries and sectors dependent on CI and investigates the gap between academic research and industry practices concerning the…
Industry 4.0 and the Internet of Things are recent developments that have lead to the creation of new kinds of manufacturing data. Linking this new kind of sensor data to traditional business information is crucial for enterprises to take…
The ongoing process of smart grid digitalisation is increasing the volume of automated information exchange across distributed energy systems. This has driven the development of new information and data models when existing models fail to…
Engineering models created in Model-Based Systems Engineering (MBSE) environments contain detailed information about system structure and behavior. However, they typically lack symbolic planning semantics such as preconditions, effects, and…
An upcoming industrial IoT revolution, supposedly led by the introduction of embedded sensing and computing, seamless communication and massive data analytics within industrial processes [1], seems unquestionable today. Multiple…
The construction industry is presently going through a transformation led by adopting digital technologies that leverage Artificial Intelligence (AI). These industrial AI solutions assist in various phases of the construction process,…
Machine learning (ML) techniques are enjoying rapidly increasing adoption. However, designing and implementing the systems that support ML models in real-world deployments remains a significant obstacle, in large part due to the radically…
Over the last decade, researchers and engineers have developed a vast body of methodologies and technologies in requirements engineering for self-adaptive systems. Although existing studies have explored various aspects of this topic, few…
Against the backdrop of the European Union's commitment to achieve climate neutrality by 2050, efforts to improve energy efficiency are being intensified. The manufacturing industry is a key focal point of these endeavors due to its high…
The automotive industry is currently undergoing a major transformation with respect to the Electric/Electronic (E/E) and software architecture, driven by a significant increase in the complexity of the technological stack within a vehicle.…
Recent advances in large pretrained models have led to their widespread integration as core components in modern software systems. The trend is expected to continue in the foreseeable future. Unlike traditional software systems governed by…
We argue that interpretations of machine learning (ML) models or the model-building process can be seen as a form of sensitivity analysis (SA), a general methodology used to explain complex systems in many fields such as environmental…
Decision support system in Requirements engineering plays an important role in software development life cycle. The relationship between functional and non-functional requirements often plays a crucial role in resolving conflicts or…
This paper presents a framework that guides the requirements engineer in the implementation and execution of an effective requirements generation process. We achieve this goal by providing a well-defined requirements engineering model and a…
Context: As the diversity and complexity of regulations affecting Software-Intensive Products and Services (SIPS) is increasing, software engineers need to address the growing regulatory scrutiny. As with any other non-negotiable…
This paper delves into the contrasting roles of data within academic and industrial spheres, highlighting the divergence between Data-Centric AI and Model-Agnostic AI approaches. We argue that while Data-Centric AI focuses on the primacy of…
Autonomous driving systems (ADSs) promise improved transportation efficiency and safety, yet ensuring their reliability in complex real-world environments remains a critical challenge. Effective testing is essential to validate ADS…