A5088564536- Business Process Modeling and Analysis
- Service-Oriented Architecture and Web Services
- Digital Innovation in Industries
- Corporate Governance and Management
- Collaboration in agile enterprises
- Semantic Web and Ontologies
- Augmented Reality Applications
- Digital Platforms and Economics
- Personal Information Management and User Behavior
- Business Strategy and Innovation
- Big Data and Business Intelligence
- Green IT and Sustainability
- Flexible and Reconfigurable Manufacturing Systems
- Information Technology Governance and Strategy
- Consumer Retail Behavior Studies
- Virtual Reality Applications and Impacts
- Mobile Health and mHealth Applications
- Recommender Systems and Techniques
- Context-Aware Activity Recognition Systems
- Data Quality and Management
- Industrial Vision Systems and Defect Detection
- Water Quality Monitoring Technologies
- Technology Adoption and User Behaviour
- Innovative Human-Technology Interaction
- Digital Transformation in Industry
AWS-Institute for Digitized Products and Processes
2016-2025
German Research Centre for Artificial Intelligence
2010-2021
Saarland University
2003-2015
Deutsches Forschungsnetz
2013
Purpose The transition to omnichannel retail is the recognized future of retail, which uses digital technologies (e.g. augmented reality shopping assistants) enhance customer experience. However, retailers struggle with implementation such in brick-and-mortar stores. Against this background, present study investigates impact a smartphone-based assistant application, personalized recommendations and explainable artificial intelligence features on experiences. Design/methodology/approach...
Complex Event Processing (CEP) is a novel and promising methodology that enables the real-time analysis of stream event data. The main purpose CEP detection complex patterns from atomic semantically low-level events such as sensor, log, or RFID Determination rule for matching these simple based on temporal, semantic, spatial correlations central task systems. In current design systems, experts provide patterns. Having reached maturity, Big Data Systems Internet Things (IoT) technology...
Abstract Purpose The business operations of today's enterprises are heavily influenced by numerous internal and external events. With the Event Driven Architecture particularly Complex Processing (CEP), technology required for identifying complex correlations in these large amounts event data right after its appearance has already emerged. resulting gain operational transparency builds foundation (near) real-time reactions. This motivated extensive research activities especially field...
Electricity load forecasting of private households usually aims at predicting the household's total by applying artificial intelligence methods to data measured grid connection point. This is a challenging task, as parameter interest influenced climate, seasonal and human factors. With rising number implemented digital metering systems, future household promises not only contain load, but also have an increased granularity, even covering single devices. analysis investigates extent which...
The propagation of digital infrastructure and intelligence within the electricity grids opens door to new methods residential load forecasting: away from usage aggregated standardized profiles an individual prediction at single-household level. Given highly nature data, performance state-of-the-art forecasting techniques, such as employment artificial neural networks (ANNs), is expected differ among certain household types. In this work, we study impact different types, characterized by...
ABSTRACT The fourth industrial revolution has driven the emergence of Digital Twins (DTs) and Industrial Internet Things (IIoT) in manufacturing. However, use different definition led to varied interpretations inconsistent understanding DTs. Thus, by exploring gap between theoretical frameworks practical implementations IIoT‐based DTs manufacturing, this paper aims shed light on DT phenomenon considering historical evolution fundamental concepts Therefore, a systematic literature review was...
Nowadays, companies are more than ever forced to dynamically adapt their business process executions currently existing situations in order keep up with increasing market demands global competition. Companies that able analyze the current state of processes, forecast its most optimal progress and proactively control them based on reliable predictions will be a decisive step ahead competitors. The paper at hand exploits potentials through predictive analytics big data aiming event-based...
Virtual Reality (VR) technology has found its way from entertainment and gaming applications into industrial environments. Only few approaches discuss the application of VR in inspection maintenance domain. Having reliable processes is however significant importance for economic success manufacturing companies. In order to optimize manual processes, we developed a concept visual remote inspections machines based on technology. The approach focusses usage real-world recordings that enable...
An ontology for the structured storage, retrieval, and analysis of data on lithium‐ion battery materials electrode‐to‐cell production is presented. It provides a logical structure that mapped onto digital architecture used to visualize, correlate, make predictions in production, research, development. Materials processes are specified using predetermined terminology; chain unit (steps) connects raw products (items) cell production. The enables attachment analytical methods (characterization...
Enterprises in today's globalized world are compelled to react on threats and opportunities a highly flexible manner. Hence, companies that able analyze the current state of their business processes, forecast most optimal progresses with this proactively control them will have decisive competitive advantage. Technological progress sensor technology has boosted real-time situation awareness, especially manufacturing operations. The paper at hands examines, based case study stemming from steel...
With recent advances in various hardware technologies, human motion capturing (MoCap) has gained importance the fields such as computer vision, animation, gesture recognition gaming, and most importantly bio-mechanical analysis. In this direction, is being captured using kinds of sensors. Correspondingly, many model-based data-based techniques have been developed order to decode sensor readings into information understandable by a person. Given that current technologies still lack...