Bridge projects

Bridge projects are multidisciplinary research and innovation projects directed by DIREC researchers in collaboration with companies, the public sector and GTS institutes with the aim of increasing the companies’ digitalisation and innovation capacity.

Bridge project

Verified Voting Protocols and Blockchains

There is constant interest for Internet Voting by election commissions around the world. At the same time, there is a need for online voting in blockchain governance. However, building an internet voting system is not easy: the design of new cryptographic protocols is error prone and public trust in the elected body easily threatened. Switzerland, which is leading in e-voting, requires very high standards for the protocols and their implementation: it requires cryptographic proofs of security.

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Bridge project

Low-Code Programming of Spatial Contexts for Logistic Tasks in Mobile Robotics

Logistics tasks in low-volume production represent an important opportunity for automatization via mobile robots. However, for successful application easy programming solutions are needed that address the variability of the spatial context in full 3D. The project partners SDU and RUC aim to provide an adaptive and re-configurable low-code programming approach to this problem and demonstrate the approach with the mobile platform of Enabled Robotics.

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Bridge project

Trust through Software Independence and Program Verification

There is constant interest for Internet Voting by election commissions around the world. Greenland illustrates this well. Greenland’s election law was changed in 2020, which now permits the use of Internet Voting. However, building Internet Voting system is not easy: the design of new cryptographic protocols is error-prone and public trust in the elected body easily threatened. A software-independent voting protocol is one where an undetected change or error in software cannot cause an undetectable change or error in an election outcome.

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Bridge project

Multimodal Data Processing of Earth Observation Data

The Danish partnership for digitalization has concluded that there is a need to support the digital acceleration of the green transition. This includes strengthening efforts to establish a stronger data foundation for environmental data. Based on observations of the Earth a range of Danish public organizations build and maintain important data foundations. Such foundations are used for decision making, e.g., for executing environmental law or making planning decisions in both private and public organizations in Denmark.

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Bridge project

REWORK – The future of hybrid work

Working remotely and in hybrid work arrangements is the future. This research is focused on developing the “Futures of Hybrid work.” We will design and develop artefacts and processes to support organizations in exploring and preparing for successful collaboration in the future. In particular we will focus on the role and representation of embodiment, artefact interaction, and physical surroundings in a digital/analog setting.

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Bridge project

SIOT – Secure Internet of Things – Risk analysis in design and operation

When developing novel IoT services or products today, it is essential to consider the potential security implications of the system and to take those into account before deployment. Due to the criticality and widespread deployment of many IoT systems, the need for security in these systems has even been recognised at the government and legislative level, e.g., in the US and the UK, resulting in proposed legislation to enforce at least a minimum of security consideration in deployed IoT products.

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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

EXPLAIN-ME: Learning to collaborate via explainable AI in medical education

Most research in medical AI never makes it to the clinic. We aim to create more clinically useful AI and increase technology acceptance among clinicians by establishing Human-AI collaboration as a target that can be optimized similarly to predictive performance. In terms of explainable AI, this defines a shift from researching what we can explain to also researching how we explain it well.

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Bridge project

AI and Blockchains for Complex Business Processes

Business processes in private companies and public organisations are today widely supported by Enterprise Resource Planning, Business Process Management and Electronic Case Management systems, put into use with the aim to improve efficiency of the business processes. Recently, also blockchain technologies are being proposed as a means to provide guarantees for security, computational integrity and pseudonymous agency.

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Bridge project

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

Today, the 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. In order to improve performance, robustness and consistency of this inspection, there is a need for automated imaging-based solutions to replace subjective manual inspection.

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Bridge project

Verifiable and Safe AI for Autonomous Systems

The rapidly growing application of machine learning techniques in Cyber-Physical Systems leads to better solutions and products in terms of adaptability, performance, efficiency, functionality and usability. However, Cyber-Physical Systems are often safety critical (e.g., self-driving cars or medical devices), and the resulting need for verification against potentially fatal accidents is self-evident and of key importance.

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