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Cyber-physical Systems, IoT and Autonomous Systems ​

The size of the Danish Embedded & Cyber-Physical Systems industry is difficult to measure as CPS constitute an inherent part of a wide variety of high-tech products and services. In 2017 Danish companies in the ICT industry produced a turnover of 33 B€, an export of 11.5 B€ and an all-time record of close to 100,000 employed in Denmark. Many of the classical industrial companies are increasingly creating added value by making their products smart and interconnected using CPS/IoT technologies or even fully digital.

The objectives are:

  1. to increase the capacity and methods and system
    support for CPS and IoT as well as the engineering skills, and
  2. to show impact on real world applications working together with start-ups, industry and public institutions.

The design and development of Cyber-Physical Systems and Internet of Things complement and integrate methodologies from the other thematic areas. In particular, the design of highly robust and secure systems depends on methods from Software Engineering and Verification and Cyber Security and Blockchain. Artificial Intelligence is an important method for processing sensor data and planning actuation actions.

The design of successful human components also links to the area of Human Computer Interaction, CSCW and InfoVis. A strong emerging trend for CPS is the close interaction with biological systems, not only for healthcare, but also as a novel digital technology, programming life through engineered logic gene circuits. Finally, systems have to be designed considering Ethics and considerations for Business Innovation, Processes and Models.

Projects

Bridge project

Embedded AI

Embedded AI will revert the current AI processing flow from collecting data at the edge and processing it at the cloud, to a flow where AI algorithms are migrated from the cloud to a distributed network of AI enabled edge-devices, which will increase responsiveness and functionality, reduced data transfer, and increased resilience, security, and privacy.

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Bridge project

Edge-based AI Systems for Predictive Maintenance

Downtime of equipment is costly and a source of safety, security and legal issues. Today, organisations adopt a conservative schedule of preventive maintenance independent of the condition of equipment. This results in unnecessary service costs and occasional interruptions of production due to unexpected failures.

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Bridge project

Deep Learning and Automation of Image-Based Quality of Seeds and Grains

Today, manual visual inspection of grain is still one of the most important quality assurance procedures throughout the value chain of bringing cereals from the field to the table. 

Together with industrial partners, this project aims to develop and validate a method of automated imaging-based solutions that can replace subjective manual inspection and improve performance, robustness and consistency of the inspection. 

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Bridge project

Mobility Analytics using Sparse Mobility Data and Open Spatial Data

The amount of mobility-related data has increased massively which enables an increasingly wide range of analyses. When combined with digital representations of road networks and building interiors, this data holds the potential for enabling a more fine-grained understanding of mobility and for enabling more efficient, predictable, and environmentally friendly mobility.

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Workstream manager

Xenofon Fafoutis

Associate Professor

Technical University of Denmark
DTU Compute

E: xefa@dtu.dk
T: +45 45 25 52 78

Contributing researchers

Kim G. Larsen

Professor

Aalborg University
Department of Computer Science

IT University of Copenhagen
Department of Computer Science

University of Southern Denmark
The Maersk Mc-Kinney Moller Institute

University of Southern Denmark
The Maersk Mc-Kinney Moller Institute

Jan Damsgaard

Professor

Copenhagen Business School
Department of Digitalization

Jan Madsen

Professor

Technical University of Denmark
Department of Applied Mathematics and Computer Science

Emmanouil Vasilomanolakis

Associate Professor

Technical University of Denmark
DTU Compute

Technical University of Denmark
DTU Compute