Ambient Intelligence
The Ambient Intelligence Research Group realises state-of-the-art digital technologies that makes 'everything' smart, where deemed necessary. We focus on robust and sustainable future ready IT for a ‘smart world’.
This primarily concerns utilising sensor technologies, artificial intelligence and augmented reality. We use these to develop prototype applications related to safety, healthcare, smart industry, sustainable energy systems, animal monitoring, and several other domains. We are not restricted to specific application domains. We are domain agnostic. We focus on bridging novel research knowledge, methods and tools and industry by helping businesses and organisations improve their process efficiency, product quality and processes with the help of data. Our group’s research core lies in data acquisition/IoT (sense), extracting interpretable hidden insights and learning from the measured data (think) and providing feedback to the user (act).
Our areas of expertise
Connected embedded systems
This line of research focuses on making the latest developments in the field of internet-linked embedded systems applicable within existing engineering practice. We develop practical knowledge and prototypes concerned with obtaining data from sensors (measuring), sensor fusion and filtering, data distribution, communication protocols and (embedded) software development.
Applied data and AI
This line of research focuses on how to arrive at ‘situational awareness’ from measured “sensor” data: who is present, what are they doing, what is going on, or even what are the intentions. In addition to data storage and management, this mainly involves (big) data analysis, data mining, statistical and machine learning (ML) systems, ML engineering and decision support.
Augmented interaction
The Augmented Interaction line of research uses various technologies to achieve natural, intuitive interaction. We use cross reality (augmented, mixed and virtual reality), combined with physical representations such as robots, to make the invisible visible and interactive in a natural way. In our view, there is no longer a separation between interaction with computers and interaction with the real world.
Questions?
Please get in touch!
dr. ir. Wouter Teeuw & dr. Jeroen Linssen
Our focus
We focus on the following areas:
IoT Platform
We are investigating (in collaboration with our industrial partners) standardised architectures for secure data exchange. These architectures prioritise data monitoring, cybersecurity, and federated systems, addressing the urgent need for robust and reliable data exchange solutions that many businesses are seeking. Within the research group, we have our own IoT platform: IECON. This platform is ideal for experimentation. It is also the basis for a ‘Data Space’ that we use in the energy domain.
Edge Intelligence
Here we focus on embedded systems from a software engineering perspective (e.g. algorithms, embedded software, frameworks and distribution systems), enabling the creation of embedded intelligent solutions instead of the hardware development of embedded platforms. In this sense, our focus is on understanding the different hardware architectures and available solutions that best suit a specific application and so bring intelligence to the software. The question is always what you do ‘in the cloud’ and what you do in the ‘embedded system’.
Secure IoT
Cybersecurity is a research area that examines security aspects including confidentiality, integrity and availability, in relation to communication and data infrastructures, where cyber-physical systems need to be protected from unauthorised access. In particular for IoT and cloud applications where data is transferred over insecure communication channels such as the internet. Research topics focus on the field of cyber-secure data distribution systems for IoT applications.
eXplainable AI
Key to the discussions concerning AI is the trade-off between man and machine: who has the upper hand in such systems used by humans? This can be linked to eXplainable AI (XAI). You need to be able to find out how a learnt model reaches a specific conclusion. Due to their good performance, machine learning and deep learning methods are increasingly being used to classify errors, for example. This means that the explainability of such models is undermined. To combat this, we investigate how reasoning steps in these models can still be explained, and we focus on finding the balance between their performance and their explainability.
Data and ML Engineering (DataOps and MLOps)
The value of data and the corresponding learning models lies in the information and patterns that can be mined/extracted/learnt from it. However, the challenge also lies in continuously ensuring that (i) up-to-date, high quality and reliable information is available and (ii) models are updated based on newly available data. But how do we get from data to meaningful information? To help do this we focus on the operational aspects of data and machine learning. That is engineering and validating methods, tools and frameworks to continuously obtain smart data-driven insights in a scalable and robust manner. We want to ensure that data and model management is well organised and that issues such as data and model drift are handled with due care and, where possible, automatically. This is in essence the core DataOps and MLOps: how do we make data and machine learning operationally available and reliable?
Data visualisation and graph literacy
How do you make information accessible to users in a good way? Only when ‘ordinary people’ use an application or website, read the information correctly, understand what it means for their situation, and become motivated, can it lead to, for example, the desired behavioural change. Here we focus on a good connection between the data visualisation and the data and graph literacy of the target group.
Changing behaviour
Gamification, or the application of elements from games, is a way to use psychological motivations to motivate people to show certain behaviour. Anyone who has ever tried to learn a language with Duolingo knows how motivating a simple progress bar can be to practise Spanish vocabulary for just a few minutes. We use similar techniques, for example, to motivate patients in healthcare to do their exercises for longer and more often. We use gamification to stimulate better energy-use behaviour among residents. We also apply elements from game design and micro-interactions to augmented reality instructions in the manufacturing industry, to help ensure that employees can perform their tasks with more focus and pleasure.
Augmented reality
Whereas in previous years we were more concerned with Virtual Reality (VR), the scope is increasingly shifting to Augmented Reality (AR): adding information to the real world. In the manufacturing industry, we are not only working on optimising AR instructions in the workplace, but also how we can use AR hardware in combination with artificial intelligence to capture professional knowledge and then feed this back to new employees. There are many projects running in the health domain, for example improving online sessions between physiotherapists and patients through information analysis and visualisation, AR rehabilitation training in the Intensive Care Unit or training anaesthesiologists using VR.
“I see enormous added value in applied research with higher education. Not only because we benefit greatly from it as a manufacturer, but also in a broader perspective. Our industry will soon have professionals from MBO and HBO who will have to help our country move forward. With these technicians of the future, we as Scania, will remain part of the world around us. We are not autonomous, but need our environment and a new generation of technicians, also for sustainability challenges."
Let’s find a solution together
See optionsOur researchers
dr. ir. Wouter Teeuw
Lector Ambient Intelligence
dr. Jeroen Linssen
Lector Ambient Intelligence
dr. Danny Plass - Oude Bos
Associate Lector
dr. Javier Ferreira Gonzalez
Associate lector
dr. Deepak Tunuguntla
Associate lector
ir. Chris Baten
Guest Professor ('t Roessingh R&D)
dr. ir. Alex Chiumento
Guest Professor (University of Twente)
ir. Bernard van Veelen
Company Professor (Thales)
dr. Faizan Ahmed
Teacher/researcher
Selin Çolakhasanoglu, MSc
Teacher/researcher
dr. Eyuel Debebe Ayele
Teacher/researcher
dr. Tatiana Goering-Zaburnenko
Teacher/researcher
Iris Heerlien, MSc
Teacher/researcher
dr. ir. Gerald Hilderink
Teacher/researcher
Eelco Jannink, MSc
Teacher/researcher
Annemarie Jutte, MSc
Teacher/researcher
ir. Michael de Louwere
Teacher/researcher
dr. Alejandro Moreno
Teacher/researcher
dr. Ben van Oeveren
Teacher/researcher
Susan van der Poel
Senior project support
ir. Etto Salomons
Teacher/researcher
Hans Schokker, MSc
Teacher/researcher
Martine Soepenberg
Project support
dr. ir. Bram Ton
Teacher/researcher
Jan Veltman
Researcher
dr. Jelte van Waterschoot
Teacher/researcher
Kevin Wilmink, MSc
Teacher/researcher
Sjoerd Zagema, MSc
Teacher/researcher
Pieter Zeilstra, MSc
Teacher/researcher
Fabian Wientjes
Student Applied Data Science - Hogeschool Utrecht
Joost van Veenhuizen
Teacher/researcher
Evander van Wolfswinkel
Teacher/researcher
The research group in the media
- Jeroen Linssen was a guest together with professor Wouter Teeuw, on the podcast ‘De Dataloog’: the biggest podcast on data and AI in the Netherlands. Listen to the full episode here.
- ‘We want to make cycling safer and more enjoyable’ – Read an article by U-Today about our Smart Connected Bikes project here.
- Article: https://www.rtvoost.nl/nieuws/2073078/saxion-brengt-sociaal-aanraken-op-afstand-dichterbij, Danny Plass, 20 March 2022
- Video clip by RTV Oost: ‘https://www.youtube.com/watch?v=3w52czc8XFo’, Danny Plass, 20 March 2022
- Radio: https://www.rtvoost.nl/radio/aflevering/klaarwakker/2072370_20220321060000 (from 16:50), Danny Plass, 21 March 2022
- Successful co-operation between SMEs and Saxion in IoT lab | Oost NL, Jeroen Linssen, 6 April 2022
- B. Kranenburg, Controlling computers with your brain, interview with Danny Plas, NPO Radio 5, 17 July 2019
https://www.nporadio5.nl/fragmenten/bertop5/23fb0478-ae41-472e-8d41-5fe2a0bcf63f/2019-07-17-computers-besturen-met-je-hersenen - F. Krommendijk, Saxion helps businesses navigate the smart world, INN’twente, no. 7, summer 2019
https://www.yumpu.com/nl/document/fullscreen/62717737/inn039twente-7-zomer-2019/10
The research group is involved in the following study programmes:
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