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Internet of Things and People
Internet of Things and People (IoTaP) is a research centre that studies how people can get the most out of the Internet of Things. The work involves computer scientists, interaction designers, professionals and users. Through applied research, IoTaP addresses a range of current challenges in society within areas such as energy, transportation, health, learning and home automation.
Our vision is to be the leading research environment in making the Internet of Things useful and usable.
Paul Davidsson, Director
The evolution of IoT has largely been driven by developments in technology. Computing power and connectivity are becoming smaller, cheaper and more energy efficient, making it possible to connect and augment an increasing range of objects. How people can make meaningful use of these new technical possibilities is, however, still an open question. In order to develop successful products and services, the perspective of the users must be integrated in the studies on the Internet of Things.
IoTaP's mission is to:
- address important societal challenges through IoT research
- produce new knowledge that when applied will provide value for IoT users
- contribute to innovation through co-production with industrial and societal organisations
- publish research results regularly in well-reputed scientific journals and present the results at leading scientific conferences
- inform organisations and a broad audience about research results through seminars, popular science articles, and media appearances
- provide an attractive working environment
A list of completed projects can be found on our project archive page.
Intelligent and Trustworthy IoT Systemspaul.email@example.com
Research project | DOCTORAL PROJECT
Autonomous transport and connected firstname.lastname@example.org
Context-aware travel support in public transport email@example.com
Pain App: Predicting neuropathic pain episodes in spinal cord injury patients through portable EEG and machine firstname.lastname@example.org
Realizing the Potential of Agent-Based Social Simulationpaul.email@example.com
Welfare Technology of Knowledge Transfer: Cross-Community Knowledge Sharing (TechKnow)firstname.lastname@example.org
AVANS project: "Internet of Things Master's Program"email@example.com
Towards integrated and adaptive public firstname.lastname@example.org
Edge vs. Cloud Computing
mHealth in pandemic situations: Smartphone based portable and wearable sensors for COVID-19 email@example.com
2022 | Conference paper
ROUTE: A Framework for Customizable Smart Mobility Planners
Fahed Alkhabbas, Martina De Sanctis, Antonio Bucchiarone, Antonio Cicchetti, Romina Spalazzese, Paul Davidsson, Ludovico Iovino
2022 | Conference paper
More Sanity Checks for Saliency Maps
Lars Holmberg, Carl Johan Helgstrand, Niklas Hultin
2022 | Article in journal
Human Factors in Interactive Online Machine Learning
2022 | Doctoral thesis, comprehensive summary
Interactive Online Machine Learning
Agnes Tegen, Paul Davidsson, Jan A. Persson, Georg Krempl
2022 | Article, review/survey
Artificial Intelligence and Machine Learning Approaches in Digital Education: A Systematic Revision
Hussan Munir, Bahtijar Vogel, Andreas Jacobsson
2022 | Article in journal
Static magnetic field stimulation over motor cortex modulates resting functional connectivity in humans
Vanesa Soto-Leon, Mabel Torres-Llacsa, Laura Mordillo-Mateos, Carmen Carrasco-Lopez, Jose A. Pineda-Pardo, Ana, I Velasco, Laura Abad-Toribio, Jesus Tornero, Guglielmo Foffani, Bryan A. Strange, Antonio Oliviero
2022 | Licentiate thesis, comprehensive summary
Towards designing a flexible multimodal learning analytics system
Hamza Ouhaichi, Daniel Spikol, Bahtijar Vogel
2022 | Article in journal
Potential Benefits of Demand Responsive Transport in Rural Areas: A Simulation Study in Lolland, Denmark
Sergei Dytckov, Jan A. Persson, Fabian Lorig, Paul Davidsson
2022 | Article in journal
Modeling, reasoning, and application of fuzzy Petri net model: a survey
Wei Jiang, Kai-Qing Zhou, Arezoo Sarkheyli-Hägele, Azlan Mohd Zain
2022 | Conference paper
Mobistudy: Mobile-based, platform-independent, multi-dimensional data collection for clinical studies
Dario Salvi, Carl Magnus Olsson, Gent Ymeri, Carmen Carrasco-Lopez, Kevin C.H. Tsang, Seyed Ahmar Shah
Our research focusses on interaction technology, embedded intelligence and user-centred development.
The research area interaction technology deals with how users interact with the connected devices. Key questions in this research area include:
- How can people interact with hybrid things?
- How do you design place-specific interactions?
- How do you leverage the co-creation of hybrid things?
- How much of the infrastructures should be accessible to different users?
Interaction design, as well as computer science, has a legacy of addressing primarily virtual interaction surfaces. Innovative interaction models such as gestural interaction, gaze tracking, and augmented reality are established elements of seminal IoT research. They form important parts of the design repertoire being explored in Interaction Technology research. Moreover, in a broader perspective, the emergent infrastructures of the Internet of Things imply that the hardware increasingly becomes part of what can be designed and modified in the context of new products and services – in other words, the “design material” changes from being a predominantly virtual one to a hybrid physical/virtual one, cf. embodied interaction.
The products and services being designed and developed become hybrid things, where physical form and digital hardware – as well as the software – are open for change and experimentation.
This in turn raises a whole range of research questions at the borders of interaction design and computer science:
How can people interact with hybrid things?
At the most general level, it is clear that new hybrid materials enable new interaction models that need to be explored and assessed. Specific technologies, such as motion and gesture-based interaction and tangible interfaces, are merely indications of this new area of design-led inquiry that addresses embodied interaction in various ways. Mobile devices, such as smartphones, are expected to serve as important transitional interaction points to hybrid things. However, insights regarding their significance in the long term is that new hybrid materials actually drive innovation in terms of new interaction models.
How do you design place-specific interactions?
When designing interaction surfaces in software on generic mobile devices, there was an understandable focus on anytime-anywhere interaction. Since the hybrid materials make it possible to design physical form and digital hardware, it becomes relevant to consider products and services that are not generically mobile but rather embedded in architecture and urban space, tied to specific places and to physical structures. Previous work in ubiquitous computing and mobile services demonstrates that a great deal of design and research remains to be done in order to better understand the potential of designing place-specific hybrid things.
How to leverage the co-creation of hybrid things?
IoT is not a simple one-way operation of connecting existing physical things to the Internet. Rather, recent developments in 3D printing, open-source hardware, and other collaborative-creation frameworks illustrate how physical things can be open-sourced, disseminated, and transformed to degrees that only software was previously capable of. What this means is that the power of grassroots creation and open source will have an increasing impact on physical products and hybrid things. Research is needed to explore the potential of this development for product development, building and construction, urban planning, and a range of other domains into which IoT infrastructure extends.
How much of the infrastructures should be accessible to different users?
Traditionally, in the physical world as well as the virtual, infrastructures have been considered part of preconditions, receding more or less into the background. The hybrid physical/virtual nature of the IoT implies that infrastructure becomes customisable, visible, and generally much more present in the design and use of products and services. This has positive as well as negative consequences. On one hand, it empowers users to tailor their environments to their needs, but on the other hand it sometimes entails unreasonable requirements on users to install, set up, update, and tweak. Such trade-offs and other consequences of the emerging infrastructures must be explored from an interaction design perspective.
The research area embedded intelligence investigates how intelligence embedded in the devices can improve the usability and functionality of IoT services and products. Key issues in this research area include:
- intelligence of the individual devices
- interaction between entities
- management of data
Intelligence of the individual devices
Since large volumes of data will be generated in the IoT, it seems reasonable to embed mechanisms for data processing and decision-making in the devices (or close to the devices, e.g., in a gateway) to enable decentralised processing of information. In some applications, there are real-time requirements that may be difficult to handle by remote processing at a server or in a cloud. Also, the robustness of the system can be increased if processing is distributed, as there often is no critical single point of failure. Thus, the scalability can be enhanced in several ways if intelligence is embedded in the individual devices. The research can be characterised as 'modern' Artificial Intelligence (AI) where the intelligence is embodied in an 'intelligent agent'.
IOTAP focusses on the following crucial issues concerning the intelligence of the individual devices:
- What are the appropriate models for context-awareness in IoT applications? A device should be able to identify in which situation the device and/or its user currently is, and use this to bring added value. For example, context-awareness can be used to adjust the level of autonomy so that the degree of automation depends on the current situation and user preference or ability, or to adapt the interaction surface.
- How can the behaviour of the devices be improved through learning from experience? This could be achieved by adapting the behaviour based on direct feedback provided by the user. Another approach is to improve decision-making by learning from sensory input in a more autonomous manner. Moreover, devices may learn from each other, for example, by sharing their experiences. In some situations, it is important that the algorithms comprising the intelligence of the devices are efficient, e.g., when a large amount of data needs to be processed and the response time is crucial. Also, the power supply limitations of many devices place further requirements on efficient processing and communication.
Interaction between entities
There are a number of interesting research questions concerning the interaction between entities. Agreement technologies refer to computer systems in which entities, often called (software) agents, negotiate with one another, typically on behalf of humans, in order to come to mutually acceptable agreements. Semantic web and ontologies are two important concepts to realise such systems. Some other key concepts used to specify and verify such systems are semantic alignment, negotiation, virtual organisations, norms, and obligations. Agents can be seen as encapsulating functionality (possibly implemented as web services), and can be orchestrated to create new, higher-level functionality, which could be deployed and executed in a distributed fashion. Such orchestrations are often referred to as multi-agent systems.
Important research questions that IOTAP addresses in relation to interaction between entities are:
- How can relevant devices and services automatically be discovered by other devices and services? When more and more devices are connected to the Internet, the problem of finding the relevant one for a particular situation becomes more difficult, especially in new environments. To reduce the cognitive load of the user, service discovery of this kind may be carried out by software agents that do not need continuous user intervention.
- How can we make the devices, services, and users understand each other in an IoT context? The units need to be semantically interoperable, for example by using ontologies and other semantic web technologies. This is important, for instance, to implement service discovery functionality, as well as for making use of data that have been made publicly available. Also, in order to achieve a task, an agent (a device or a service) often needs to collaborate, or at least coordinate, with other agents. An interaction protocol defines a set of rules that guides the interaction between agents for supporting structured collaboration and negotiation in order to achieve a common or individual goal.
- What are appropriate architectural designs for heterogeneous distributed IoT systems? What is the best distribution of functionality between smart devices and the supporting infrastructure? How can we make complex open IoT system of systems more robust? For instance, reliability may be increased through redundancies that can cover up for the loss of entities, or norm systems that guide the behaviour of the entities can be introduced. Moreover, risk analysis can be made beforehand, as well as validation through simulation. Another challenge is how to identify and avoid potential undesired effects of embedded intelligence with respect to resource utilization and user behaviour. For instance, bad system design could cause unnecessary system resource utilization peaks or undesirable influence of user behaviour.
Management of data
As the number of connected devices grows at a fast rate, the amount of data they generate will explode, in particular different types of sensor data. Regarding the management of data, we will address the following questions:
- What are the best ways of utilising the large amounts of data that becomes available? Different methods for achieving this will be studied. For instance, we will investigate data mining methods for extracting relevant data and discovering patterns, data fusion methods for combining different data sources, and visualization techniques to make the data more comprehensible for human users.
- How can individual user privacy be sustained in a super-connected and data-intense surrounding? In principle, it is desired that as much as possible of the data generated is made available to other services and devices. However, the ways in which user-related data can be collected, analysed, and utilised for various purposes – benign and commercial, as well as selfish and malicious – in a digital ecosystem are uncountable. It is thus important to study the need for and the design of privacy-enhancing mechanisms in order to ensure the privacy of the users. In this respect, other aspects directly linked with human interactions, such as the management of data ownership, the gathering of consent from users, and the robustness of data security methods are also important to study.
This research area explores how users can be involved in the development of new IoT services and products. Key questions in this research area include:
- How can existing methods for user-centred development be adapted to the IoT context?
- How can user feedback be efficiently integrated into the different development phases of products and services?
- What are the most efficient techniques for continuing to improve IoT products and services also after deployment to users?
As IoT will become widely deployed, is important to better understand the needs and requirements of users and how these can be efficiently integrated throughout the development process. Traditionally, users have been actively involved in pre-development phases, i.e., in requirements engineering and in prototyping activities, and there is extensive research within areas such as participatory design, practice-based design, contextual design, and collaborative design on how to involve users as co-designers. This phase is critical and with new areas of deployment for IoT, as well as emergence of new technologies, there is a need to explore new and innovative ways to involve users in the early stages of development.
Moreover, embedded software with sensor technology and communication and processing capabilities allow for users to be actively involved also in the post-development phase, i.e., after the product and/or service has been deployed. During this phase there is the opportunity to continuously collect data on user behaviour and, as a result, continuously improve the quality of new products and services based on real-time user feedback. Thus, there is the need to find mechanisms to collect, analyse, and experiment based on user feedback.
In this way, the area of user-centred development will involve both the pre-development phases in which users provide feedback based on active collaboration with designers, and the post-development phase in which users provide feedback based on their real-time usage of products and services.
There are a number of interesting research questions related to user-centred development:
- How can existing methods for user-centred development be adapted to the IoT context? IOTAP studies how they relate to (1) contemporary developments in Living Labs methodology and other forms of participatory design for heterogeneous constituencies, and (2) to the increasingly hybrid physical/virtual nature of new products and services (i.e., new design materials). IOTAP also studies how established methods for rapid prototyping and collaborative exploratory design can be adapted to the new materials. One aim is to continuously learn from user groups and user behaviour patterns. With an increasing number of digital products and services it will be possible to improve our ways of learning about user behaviour and how products and services contribute to specific contexts.
- How can user feedback be efficiently integrated into the different development phases of products and services? Solutions include ways in which user feedback can be collected before any development starts. What are the feedback mechanisms necessary for continuously collecting user data? Solutions may include tools, techniques, and organizational processes that allow the organization to more rapidly receive user feedback on functionality before the product/service is fully developed. How can agile and lean development practices facilitate active user involvement in pre-development of IoT products/services, during development, and after product/service deployment? A specific question of interest is how insights from Living Labs and other participatory design practices can inform existing development methods and approaches.
- What are the most efficient techniques for continuing to improve IoT products and services also after deployment to users? How can user feedback be efficiently translated into improvement of current functionality, as well as future innovative products and services? Specifically, how can the deep levels of sustained user participation associated with Living Labs and related practices, and related concepts such as continuing-design-in-use and infrastructuring, inform existing notions of feedback and continuous improvement in contemporary deployment-driven methodologies?
The research at IOTAP is carried out in application areas such as energy, transportation, health, learning, and home automation. Research and development for these application areas is done through projects where researchers, industry partners, and users work together.
The integration of Internet of Things technologies and urban development places Smart Cities in a good position to address contemporary societal challenges. Applications include sustainable energy consumption, traffic management, waste management, public safety and security, and other city-level issues. But equally important are other types of value creation, such as including ICTs in government systems and bringing ICTs and people together to enhance the innovation and knowledge that they offer.
Contact: Per Linde
Health is the most valued aspect of life. By using IoT technologies to measure biometrics as well as other context cues, Smart Health can empower people to proactively engage in their health as well as to manage their recovery from illness or injury. In addition, Smart Health can be used in healthcare settings to involve patients in their treatment and to share data to improve outcomes. Thus, Smart Health is about using IoT technologies to enable and improve health-related services using a network of context-aware things.
Contact: Nancy Russo
For a more detailed introduction to the Smart Health area, please see Nancy Russo's article Smart Health and IoT: Opportunities and Challenges.
What IOTAP is doing in this area
At Malmö University, we have a track record of research in the Smart Health area. Here are a few examples of initiatives we are or have been part of:
- A Smart Health Check-Up | We hosted a Smart Health workshop where we focused on how IoT-based technologies can play a role in future healthcare development.
- Serious games for rehabilitation: Walk the Ward | This project was about encouraging patients to activity and movement during hospitalisation. The project created an application which motivates the patient to be active and involved in their care. The application consists of a program on a tablet and sensors and QR codes set in different locations in the care unit.
- IoT for dementia care: AppSam | The project explored IoT concepts that can contribute to the improvement of the quality of life for the elderly, relatives, and support health professionals.
The following researchers are involved in the Smart Health application area:
- Nancy Russo (application area coordinator)
- Suzan Boztepe
- Jonas Christensen
- Jeanette Eriksson
- Åse Jevinger
- Magnus Johnsson
- Carl Johan Orre
The connected tools for life-wide learning provide new opportunities for bringing together technology, data and people to provide creative and personalized education. Society is connected through the use of personal technology across diverse landscapes that provide opportunities for IoT services that provoke curiosity and playfulness while engaging people in relevant learning activities at school, home, work, and on the go. Making sense about how to understand, use, and share data between people and services that provides privacy, control, and security that empower people is at the centre of our research.
Contact: Daniel Spikol
The connected lifestyle of people today, through their use of mobile and wearable technology for tracking and various interactive and self-adapting IoT services, places Smart Living as a natural point of connection between everyday life and special events or activities, as well as between spare time and work. This includes technology for activity and self tracking as well as infotainment services that promote convenience, safety and entertainment in a secure and privacy-preserving manner.
Contact: Carl Magnus Olsson
A vital aspect of the society is the movement of people and goods. By using IoT in transport systems for planning, guiding users, and support autonomous acting (e.g. self-driving cars) etc., the transports can be improved. The improvement concerns efficiency, experiences and comfort for the user, reduced environmental impact, as well as increased security. In particular, individualizing transport services and providing better control and information of transported goods are areas where IoT can make a difference.
Contact: Jan Persson
The IoTaP lab
The IoTaP lab is a creative environment for research and development of IoT-based infrastructure and user interfaces. The lab is open to researchers and students working in IoTaP-related projects, and to existing and future IoTaP partners, both commercial and academic.
Contact: Lab coordinator Johan Holmberg
Who is it for?
The lab is open to our researchers, students working in IOTAP-related projects, and to IOTAP partners, both commercial and academic.
Do you want to spend time in the lab?
We provide access to the lab depending on relevance to the IOTAP research center and on currently available space.
What can the lab be used for?
The lab can be used for rapid development of interactive and embedded IoT systems. The lab provides a suitable environment for demonstrating new concepts and prototypes.
What kind of equipment is there?
The lab offers a variety of equipment for IoT prototyping and rapid development including cloud deployment with support for virtual and augmented reality (VR and AR). We also offer a physical space for your project to happen in.
We have a strong focus on the Arduino platform with a large selection of diverse shields to extend the projects’ connectivity. Additionally, we work with Raspberry Pi and other microcontroller boards. We offer a wide variety of sensors and actuators for both platforms that include off-the-shelf products like Philips Hue kits and commercial products from our partners.
We also offer 3D printing capabilities. For exploring interaction and visualization, we work with different gesture, haptic, voice, VR, and AR platforms to extend data beyond the 2D screen.
We offer a dedicated network for all things IoT, wireless as well as wired. We also offer several ways of connecting your projects through e.g. Zigbee, WiFi, GPRS, as well as more passive technologies such as Bluetooth beacons and NFC/RFID.
What kind of help can I get?
The lab offers help with most aspects of prototype development. We can get you started with designing your IoT artefact and we are happy to help in choosing and getting up to speed with a relevant development platform, e.g. Arduino, Raspberry Pi, or Hololens.
Our network of competencies includes people experienced in:
- Interaction design and technology
- Sensor network architecture
- Data gathering and analysis
- Rapid prototyping and digital fabrication
A smart campus links connected devices, infrastructure, applications, and people to make a university campus as a platform for innovation with opportunities for enabling new experience, services and improving operational efficiency. This interaction will make a university campus smarter when IoT and artificial intelligence (AI) come together for deriving the knowledge from IoT data. This results in elevating user experiences to an unprecedented new level. For example, the students, researchers, staff, and visitors can benefit from location-aware and context-aware services for using campus equipment and collaboration services.
Value through innovation
The research of Carl Magnus Olsson and Dario Salvi regarding Mobistudy (www.mobistudy.org) is included in The Royal Swedish Academy of Engineering Sciences' list – IVA's 100 List 2021 listing research projects focusing on sustainable emergency preparedness with the potential to create value through innovation.
Computer science and interaction design students often collaborate with IOTAP researchers and partners when doing their bachelor's or master's thesis projects. This kind of collaboration is a good way in for companies that want to establish a connection with IOTAP. If you are interested in collaboration, see contact details at the bottom of this page.
Organisation and Partners
Muhammad Adil Abid - Doctoral firstname.lastname@example.org
Alberto Enrique Alvarez Uribe - Doctoral email@example.com
Sally Bagheri - Doctoral firstname.lastname@example.org
Michael Belfrage - Doctoral email@example.com
Patrik Berander - Program director/Senior firstname.lastname@example.org
Joseph Bugeja - Postdocjoseph.email@example.com
Jonas Christensen - Senior firstname.lastname@example.org
David Cuartielles - Lecturerdavid.email@example.com
Paul Davidsson - Professorpaul.firstname.lastname@example.org
Sergei Dytckov - Doctoral email@example.com
Jimmy Engström - Doctoral firstname.lastname@example.org
Jeanette Eriksson - Senior email@example.com
Maliheh Ghajargar - Associate senior firstname.lastname@example.org
Clint Heyer - Senior email@example.com
Lars Holmberg - Doctoral firstname.lastname@example.org
Andreas Jacobsson - Dean/Associate Professorandreas.email@example.com
Åse Jevinger - Director of research studies/Associate Professorase.firstname.lastname@example.org
Emil Johansson - Doctoral email@example.com
Sara Leckner - Senior lecturer/Head of firstname.lastname@example.org
Per Linde - Head of unit/Senior email@example.com
Fabian Lorig - Associate senior firstname.lastname@example.org
Benjamin Maus - Lecturerbenjamin.email@example.com
Fisseha Mekuria - Senior firstname.lastname@example.org
Radu-Casian Mihailescu - Senior email@example.com
Hussan Munir - Associate senior firstname.lastname@example.org
Carl Magnus Olsson - Associate Professorcarl.email@example.com
Hamza Ouhaichi - Doctoral firstname.lastname@example.org
Jan Persson - Senior email@example.com
Nancy Russo - Senior firstname.lastname@example.org
Tautgirdas Ruzgas - Assistant head of dep./Professortautgirdas.email@example.com
Dario Salvi - Associate Professordario.firstname.lastname@example.org
Arezoo Sarkheyli-Hägele - Senior email@example.com
Romina Spalazzese - Senior firstname.lastname@example.org
Daniel Spikol - Timeemployeedaniel.email@example.com
Bahtijar Vogel - Head of unit/Senior firstname.lastname@example.org
Gent Ymeri - Doctoral email@example.com
Paul Davidsson - Professor
Per Linde - Head of unit/Senior lecturer
Reza Malekian - Professor/Assistant head of dep.
Carl Magnus Olsson - Associate Professor
Jan Persson - Senior lecturer
Nancy Russo - Senior lecturer
Romina Spalazzese - Senior lecturer
- Johan Eker, Ericsson, Lund University (Chair)
Anna Gillquist, Region Skåne
- Andreas Jacobsson, Malmö University (Faculty of Technology and Society)
- Anders Kottorp, Malmö University (Faculty of Health and Society)
- Niklas Malmros, Sigma Technology
- Annika Olsson, Malmö University (School of Arts and Communications)
- Andrej Petef, Sony Mobile
- Maria Stellinger Ernblad, City of Malmö
- Jonas Bergh, Sigma Connectivity
- Lars Bierlein, E.On
- Fredrik Hertzberg, Axis
- Thomas Höglund, Data Ductus
- Anders Larsson, TOPP
- Per Lindquist, Cybercom
- Niklas Malmros, Sigma Technology
- Andrej Petef, Sony Mobile
- Prof. Jan Bosch, Chalmers University of Technology, Gothenburg, Sweden. Director of Software Center.
- Prof. Peter Gall Krogh, Aarhus School of Architecture, Denmark. Director of REform – designing social innovation for sustainability.
- Prof. Sascha Ossowski, Rey Juan Carlos University, Madrid, Spain. Director of Centre for Intelligent Information Technologies.
Current and past partners which have collaborated with IOTAP on various projects:
NMSA – Network for Mobile Services and Applications
Internet of Things Sweden
K2 National Knowledge Centre for Public Transport
ITS Postgraduate School
Health Guide IRL
Perch Dynamic Solutions
Scandinavian CleanTech Group
Sony Mobile Communications
Ziggy Creative Colony
Copenhagen Institute of Interaction Design
IVL – Swedish Environmental Research Institute
SICS – Swedish ICT
SIK – the Swedish Institute for Food and Biotechnology
SP – Technical Research Institute of Sweden
Viktoria – Swedish ICT
European Network of Living Labs
Friskis & Svettis
Stockholm Consumer Cooperative Society
NTM – Network for Transport Measures
Stockholm Innovation & Growth
Citilab – Cornella
Municipality of Karlshamn
NetPort Science Park
City of Lund
City of Malmö
Blekinge Institute of Technology
Technical University of Denmark
Royal Institute of Technology
National College of Art and Design (Dublin)
Scuola Superiore Sant`Anna
University of Bremen
University of Craiova
University of London, Institute of Education
Prototypes, services and products
These are some of the prototypes, services and products IOTAP researchers and students have contributed to developing. These have typically been developed in collaboration with industry and/or end-users.