Embedded and Intelligent Systems (EIS)
The School Information Technology conducts research within the research environment Embedded and Intelligent Systems (EIS). The purpose is to contribute to solutions of societal challenges within the University’s profile areas Health Innovation and Smart Cities and Communities.
About research environment EIS
In the research environment Embedded and Intelligent Systems (EIS), research is conducted within aware intelligent systems, smart electronic systems, cyber physical systems and digital service innovation. These four areas constitute the four Technology Areas of the research environment.
Research goal
The research goal within EIS is to provide and develop knowledge (solutions, theories, methods, tools) that are relevant for the creation of innovative IT-based products and services – from enabling technologies, via system solutions and applications, to value-creating IT utilisation. With this, we intend to contribute to strengthening the competitiveness of Swedish industry.
Research leader at the School of Information Technology and the research environment EIS is Slawomir Nowaczyk.
Four Technology Areas and one Center
Research at EIS is conducted within four Technology Areas:
- Digital Service Innovation
- Aware Intelligent Systems
- Smart Electronic Systems
- System of Cyber Physical Systems
The competence in these technology areas include signals and systems, informatics, mathematics, computer science and engineering, forensics, electronics and physics. These competences form the research environment EIS.
Center for Applied Intelligent Systems Research (CAISR), is a long-term research program on intelligent systems established by Halmstad University. The program is funded by the University and the Knowledge Foundation with support from Swedish Industry.
Research news from EIS
Research in collaboration
Through our joint competences we can be an attractive partner and deal with projects where the whole range is treated, from enabling technologies – like low-power technologies and semiconductor sensors – to value-adding IT use, considering user aspects. In between, system and application aspects are treated, that is intelligent algorithms, application-specific computer architectures and efficient interconnection technologies.
Our strategy is to focus on a limited number of application areas in which we get recognised by industry and society as a key player and natural cooperation partner. Currently, the selected application areas are: health technology, traffic and transport systems, process industry, high-performance signal processing applications, experience industry, together with the (non-application) area of ground breaking electronics.
- EIS shall be an internationally recognised research environment with advanced and postgraduate education.
- EIS shall be characterised by well-developed research collaborations with the business sector and the public sector.
- EIS should be a leading environment within embedded and intelligent systems in Europe.
More information
The research environment Embedded and Intelligent Systems (EIS) belongs to the School of Information Technology (ITE). Publications from researchers at EIS are collected from DiVA.
The School of Information Technology
Doctoral education in Information Technology
Doctoral and licentiate theses at EIS
Embedded and Intelligent Systems Industrial Graduate School (EISIGS)
Halmstad Colloquium – Halmstad University distinguished speaking series
Technology Area Aware Intelligent Systems
Our research is carried out in close collaboration with industrial partners and is largely about development within artificial intelligence (AI). The focus is on creating systems that, as autonomously as possible, can be developed based on real-life data.
Research focus
The goal with artificial intelligence (AI) research and development is to construct systems that behave intelligently. Today it is common to assume that human experts define the task to be performed, what data should be collected, how should it be represented, and what metrics to use for performance evaluation. This means that these systems are designed or programmed, which leads to them breaking when the context changes.
Our aim with Aware Intelligent Systems research is to approach the construction of systems that can do life-long learning; systems that require less supervision and can handle surprising situations. In order to do so, the systems must become more aware and able to learn on their own, to handle events that are unknown at the time of design. Our research focuses on creation of systems that, as autonomously as possible, can construct knowledge from real life data capturing the interaction with the environment.
Technology Area Leader: Sepideh Pashami
When large amounts of data are collected and analysed by intelligent systems, new solutions to several of today's societal problems can be developed.
The aim of the research is to, in collaboration with our surrounding society, create conscious and intelligent systems that have the ability to develop themselves.
Application areas
When large amounts of data are collected and analysed by these intelligent systems, new solutions to several of today's societal problems can be developed. For example, recent developments in wearable sensors has inspired a vision of personalised health; modern energy production is becoming more volatile, diverse and distributed; transport efficiency depends on better maintenance and monitoring solutions. All those areas require novel solutions that build upon available data and require autonomous knowledge creation.
The research questions we explore include selecting what data to collect and how to find general and robust representations; how to do (semi-)autonomous deviation detection, dealing with concept drift and seasonal variations; how to associate events from different data sources; is it possible to explain why certain things have happened.
Aware systems research is a systems science, so there are many interconnected parts and the results need to address several aspects, tying them together. To enable this, we build demonstrators to showcase what this means, with sets of tools for all levels.
About artificial intelligence
Artificial intelligence (AI) can be divided into general AI and narrow AI. General AI is not yet developed, but narrow AI is used in a number of different areas today. For example, in autonomous vehicles and when scanning images on the internet. Machine learning is part of AI where algorithms and computer programs learn by repeating examples. Machine learning is a way to reach narrow AI or ultimately to general AI. Deep learning is an area within machine learning where algorithms find special features and properties for making decisions on their own.
Collaboration
Technology Area Aware Intelligent Systems is closely linked to the innovation centre Leap for Life, the lab Halmstad Intelligent Home and the Center for Applied Intelligent Systems Research.
Education
The Technology Area is responsible for carrying through and developing courses within artificial intelligens, image analysis, learning systems, mechatronics systems, signals and systems, and control theory. Education of doctoral students is done within the doctoral education in information technology:
Organisation
Technology Area Aware Intelligent Systems is, together with Technology Area Digital Service Innovation, organised under department ISDD at the School of Information Technology.
Technology Area Digital Service Innovation
At Halmstad University, we profile Informatics towards Digital Service Innovation (DSI). This implies a focus on how value is created for users, organisations and societies through combining, re-combining and integrating resources into digital services.
Research focus
Informatics at Halmstad University develops the Scandinavian Informatics tradition, which integrates Information Systems (IS) and Human Computer Interaction (HCI) research. We profile Informatics towards Digital Service Innovation (DSI). This implies a focus on how value is created for users, organizations and societies through combining, re-combining and integrating resources into digital services. We also investigate how and why DSI may promote or create improvements in the wellbeing of different societal actors, by studying for example stakeholder involvement in innovation processes, digital service logics and architectures, innovation ecosystems and value network governance.
DSI research in Informatics combines theorizing (identifying models, patterns, structures, relations, processes) with applied and action-oriented research in co-creation with industrial and public-sector partners, and covers process innovation research focused on stakeholder involvement and value co-creation as well as the intersection between digital services and business. The core competence areas include innovation process knowledge, digital service and business innovation, interaction design and design science. We often use qualitative research methods such as qualitative interviews, focus group and workshop methods (e.g. co-design, participatory design, personas) participant observation, and design ethnography. Research output includes insights, theory and method development, prototypes and demonstrators.
Technology Area Leader: Magnus Bergquist
Digital service innovation is an area based on research in informatics, service sciences and innovation sciences.
Application areas
Empirically Informatics research at Halmstad University focus on DSI in different application areas in companies, public sector and for individuals. Healthcare studies aims develop an understanding of digitalization of hospitals and healthcare to empower health professionals in their work. This is done by studying the use and meaning of health technologies, and developing innovative solutions to health-related challenges for individuals, groups, organisations, companies and society at large.
In the transport sector, we study how for exampel embedded sensors in buses and intelligent systems create new opportunities for digital service innovation. A growing strand of research focuses on users’ appropriation of autonomous driving (AD) cars and digital service design for future mobility solutions.
The media application area has been the main focus for Informatics at Halmstad University for long. In collaboration with the Swedish and international media industry research has centered on exploring new IT concepts and services enabling new forms of value creation and value capture.
Research on public sector DSI focus on how digitisation in the form of civic services transforms the relationship between citizens and government, and what innovation means for the services purchased by public authorities.
We often use qualitative research methods such as qualitative interviews, focus group and workshop methods, participant observation, and design ethnography.
Blog
Technology Area Digital Service Innovation runs a blog: Digital Service Innovation blog
Education
Research is channelled into education on Bachelor, Master and PhD levels. Informatics has two Bachelor programmes, one international Master programme and Doctoral education in Informatics:
Staff
Staff at the School of Information Technology who are linked to the Technology Area Digital Service Innovation:
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Dimitrios Gkouskos | Associate Senior Lecturer | |
Dulce Goncalves | Industrial PhD student at Combitech | |
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Industrial PhD student at Volvo Cars | ||
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Organisation
Technology Area Digital Service Innovation is, together with Technology Area Aware Intelligent Systems, organised under department ISDD at the School of Information Technology.
Technology Area Aware Intelligent Systems
Department ISDD at the School of Information Technology
Technology Area Smart Electronic Systems
Technology Area Smart Electronic Systems focus on the challenges and opportunities that the ongoing digitisation of society entails. Embedded electronics are integrated in everything from smart everyday gadgets to robots and cars. Smart electronics are developing at a rapid pace and the possibilities of new innovations are endless.
Research focus
Connected technology is everywhere. Artificial intelligence and the Internet of Things have changed our world. New innovations in health, energy, future homes and cities, autonomous vehicles and everyday technology all require a smart core of electronics. This massive integration of electronics everywhere introduces challenges like integration, miniaturisation, building practice, new sensors, low energy consumption, electromagnetic interference (EMI), architectures for high performance computing, resource efficient communication and affordable components.
Within the Technology Area Smart Electronic Systems we have ongoing research on antenna design, electromagnetic interference and compatibility, nanoelectronics and photonics, radar and radio systems, high performance computing architectures, and building practice for components and systems.
Technology Area Leader: Ross Friel
New innovations in health, energy, future homes and cities, autonomous vehicles and everyday technology all require a smart core of electronics.
We have ongoing research on for example antenna design, electromagnetic interference and compatibility and nanoelectronics.
What is Internet of Things?
The Internet of Things (IoT) can be everyday items such as household appliances, clothes and accessories, but also machines, vehicles and buildings, with built-in electronics and internet connection, which allows them to be controlled or exchanged data over the Internet.
The "things" can be controlled and share information from other locations, which facilitates integration with computer systems and can result in higher efficiency and accuracy. When the IoT contains sensors, it becomes an example of something called cyber physical systems, such as intelligent houses, smart electricity grids and intelligent transport systems.
Collaboration
Technology Area Smart Electronic Systems is closely linked to the collaboration arenas Electronics Centre in Halmstad and Rydberg Core Laboratory:
Education
The Technology Area Smart Electronic Systems is responsible for carrying through and developing courses within electronics, radio communication, electromagnetic computation and physics. Education of doctoral students is done within the doctoral education in information technology:
Organisation
The Technology Area Smart Electronic Systems is, together with Technology Area Systems of Cyber Physical Systems, organised under department CERES at the School of Information Technology.
Technology Area System of Cyber Physical Systems
When the Internet of Things (IoT) contains sensors, it becomes an example of something called cyber physical systems (CPS), such as intelligent houses, smart electricity networks and intelligent transport systems. This is the focus of the Technology Area Systems for Cyber Physical Systems.
Research focus
There is growing consensus that many important future innovations will involve closely coupled computational (or “cyber”) and physical components, often in a networked or distributed setting. Cyber-Physical Systems (CPSs) is a term coined to describe such systems, and has served as a flag for a large community of researchers working in this area.
At the Technology Area, we develop model-based methods that enable innovation within CPS. New methods are being developed for specification, simulation, and testing. Specification is the process of creating the models, which serve as the central artefact in model-based methods. Simulation provides a mechanism for “animating” or “running” models, and provides a fundamental tool for understanding the dynamics of a given model. At Halmstad University, focus has been on rigorous simulation methods which take into account round, discretization, and quantization errors and are guaranteed to produce correct results. Research on testing focuses on developing notions of conformance of software product lines and hybrid systems, as well as test-case generation.
Application areas for the research within cyber physical systems include robotics, automotive, and healthcare systems.
Technology Area Leader: Wojciech Mostowski
New methods are being developed for specification, simulation, and testing, Application areas include robotics, automotive, and healthcare systems.
Cyber physical systems are for example intelligent houses, smart electricity networks and intelligent transport systems.
What are cyber physical systems?
The Internet of Things (IoT) can be everyday items such as household appliances, clothes and accessories, but also machines, vehicles and buildings, with built-in electronics and internet connection, which allows them to be controlled or exchanged data over the Internet.
The "things" can be controlled and share information from other locations, which facilitates integration with computer systems and can result in higher efficiency and accuracy. When the IoT contains sensors, it becomes an example of something called cyber physical systems, such as intelligent houses, smart electricity grids and intelligent transport systems.
Education
The Technology Area is responsible for carrying through and developing courses within Computer Communication, Computer Science, Computer Systems Engineering, Parallel Architectures and Real-Time Systems. Education of doctoral students is done within the doctoral education in information technology:
ELLIIT – Strategic Research Environment
Halmstad University, through ITE, is part of the ELLIIT strategic research environment (SFO) aimed at encouraging research in information technology and mobile communications. The overarching objective of ELLIIT is to support scientific excellence in combination with industrial relevance and impact.
ELLIIT stands for Excellence Center at Linköping-Lund in Information Technology and has four partners:
- Linköping University
- Lund University
- Halmstad University
- Blekinge Institute of Technology
ELLIIT constitutes a platform for both fundamental and applied research, and for cross-fertilization between disciplines and between academic researchers and industry experts. ELLIIT stands out by the quality and visibility of its publications, and its ability to attract and retain top talented researchers, and aims at being recognized as a top international research organization.
ELLIIT achieves its goals by a judicious choice of funded focus projects, a structured process for international recruitment, a balanced way of stimulating cooperation between research areas and between the sites involved, and a proactive approach towards fostering and maintaining cooperation with Swedish industry.
Halmstad University contributes to in ELLIIT in the following way:
ELLIIT Professorships
Walid Taha
Research by Halmstad University within ELLIT
Researcher: Alexey Vinel
Scalable Language Tools for Cyber-Physical Systems
Researcher: Walid Taha
Stream Computing Infrastructures
Researcher: Zain Ul-Abdin
Organisation
The Technology Area Systems of Cyber Physical Systems is, together with Technology Area Smart Electronic Systems, organised under department CERES at the School of Information Technology.
Technology Area Smart Electronic Systems
Department CERES at the School of Information Technology
During the period 2003 to 2015, research was conducted in this area at the Center for Research on Embedded Systems (then CERES).
Center for Applied Intelligent Systems Research (CAISR)
The Center for Applied Intelligent Systems Research (CAISR), is a research and education center for AI at Halmstad University. The center is funded by the University and the Knowledge Foundation with support from Swedish Industry.
The scientific focus for the Center for Applied Intelligent System Research (CAISR) is “aware” intelligent systems – human aware, situation aware and self-aware. Such systems can combine different sources of information to get an overall picture and monitor themselves. The subject expertise in the center is in signal analysis, machine learning and mechatronics. CAISR also has an emphasis on cooperating systems, in line with the research focus for the research environment Embedded and Intelligent Systems (EIS).
Several industrial partners are collaborating with researchers from Halmstad University in joint projects, and also take an active part in the development of CAISR. The industrial partners include multinational companies as well as research-based growing companies. The key application areas for CAISR's research are information driven care and intelligent vehicles & predictive maintenance.
CAISR is a multidisciplinary research center with researchers from different areas. Our research directions are governed by the needs of society and are done in collaboration with our industrial partners.
Collaboration and organisaton
CAISR is closely linked to the innovation centre Leap for Life, the lab Halmstad Intelligent Home and Technology Area Aware Intelligent Systems:
CAISR Partners
- Affecto Sweden
- AI Sweden
- Air Liquide
- Alfa Laval
- Berkeley University
- Chicago University
- CGI
- Cubist
- EasyServ Sweden
- Essity
- European DLB Consortium
- FacePhi Biometria Ltd.
- Getinge
- Hallandia V
- Halland municipalities (Falkenberg, Halmstad, Hylte, Kungsbacka and Varberg)
- Harvard Medical School
- HEM (Halmstad Energi och Miljö)
- High Five
- HMS Industrial Networks
- HotSwap Norden
- Karolinska Institute
- Linköping University Hospital
- Lund University
- NEAT Electronics
- Novartis
- Novo Nordisk
- Region Halland
- Region Skåne
- Region Stockholm
- Region Västra Götaland
- Region Örebro län
- RISE (Research Institutes of Sweden)
- Sahlgrenska at Gothenburg University
- SKR (Swedish Association of Local Authorities and Regions)
- Stena Recycling
- Sydpumpen
- Takeda
- Tappa Service
- Toyota Material Handling
- Viscando
- Volvo Technology / Volvo Group Trucks Technology
- Volvo Bus Corporation
- Volvo Group Connected Solutions
- Volvo Trucks Corporation
- Öresundskraft
With support from the Knowledge Foundation
CAISR Management
- Thorsteinn Rögnvaldsson (project manager for CAISR)
- Magnus Clarin
- Josef Bigun
- Mattias Ohlsson
- Mark Dougherty
- Slawomir Nowaczyk
- Stefan Byttner
CAISR Industrial Advisory Board
The CAISR partners have decided to create an Industrial advisory board (IAB), consisting of representatives from each industrial partner. This group will follow the project development with respect to the co-production and co-operation between the Parties. The Industrial Advisory Group will meet twice a year. The Industrial Advisory Group will express themselves on issues of potential new partners in the project, changes in financing and project development from business perspective.
CAISR Reference Group
The reference group consists mainly of representatives from national and international research institutions. The reference group gives advice and comment on the project development from the academic perspective, not least by the University’s perspective. They will also give their view on research, innovation and education perspectives. The reference group can also provide suggestions for concrete actions to improve the project.
CAISR straff
- Abbas Orand
- Abdallah Alabdallah
- Alexander Galozy
- Alexey Vinel
- Amira Soliman
- Arianna Engström
- Awais Ashfaq
- Björn Åstrand
- Cristofer Englund
- Ece Calikus
- Eren Erdal Aksoy
- Eric Järpe
- Fernando Alonso-Fernandez
- Hadi Fanaee
- Jennifer David
- Johannes van Esch
- Kobra Etminani
- Kunru Chen
- Magnus Clarin
- Mahboubeh Jennasary
- Mahmoud Rahat
- Maria Luiza Recenta Menezes
- Martin Cooney
- Mark Dougherty
- Mattias Ohlsson
- Mohamed-Rafik Bourgelia
- Mohammed Ghaith Altarabichi
- Nicholas Wickström
- Onur Dikmen
- Pablo del Moral
- Peyman Mashhadi
- Pontus Wärnestål
- Reeben Ali Hamad
- Reza Khoshkangini
- Roger Carlsson
- Roland Thörner
- Sepideh Pashami
- Shiraz Farouq
- Slawomir Nowaczyk
- Stefan Byttner
- Taha Khan
- Thomas Munther
- Thorsteinn Rögnvaldsson
- Tiago Cortinhal
- Tommy Salomonsson
- Wagner De Morais
- Zahra Taghiyarrenani
- Yuantao Fan
Research projects and application areas
The mission of CAISR is to serve and promote the development of industry and society. It is a center for industrially motivated research on the future technologies for and application opportunities with aware intelligent systems. CAISR will serve as a partner for industry's own research and development, as a recruitment base for those who seek staff with state-of-the-art knowledge in intelligent systems technologies, and as a competence resource for industry and society. Read more about the research focus and application areas of CAISR:
Links to articles about CAISR researchers and research projects can be found under "Articles" below. The research projects are also described on CAISR’s wiki pages:
Articles
Scientific articles published by CAISR researchers are collected under:
Articles about CAISR researchers:
Joint human-machine learning can improve district heating
(about Ece Calikus)
Artificial intelligence could predict and prevent diseases
(about Kobra Etminani)
Increased security with facial recognition
(about Fernando Alonso-Fernandez)
Robots that understand, learn and imitate humans
(about Eren Erdal Aksoy)
Slawomir wants to create an artificial, truly intelligent system
(about Slawomir Nowaczyk)
Driven to contribute to something larger
(about Thorsteinn Rögnvaldsson)
From punch cards to artificial intelligence – from east to west
(about Antanas Verikas)
An Engineer with a Passion for Health
(about Anita Pinheiro Sant´Anna)
Anita’s company wants to forge the link between researchers and facts
(about Anita Pinheiro Sant´Anna)
The researcher who wants to teach machines to see
(about Josef Bigun)
Articles about CAISR research projects:
Halmstad University in second place in an international AI competition
Personalised digital intervention to battle high blood pressure
Eight new projects within Research for innovation
Successful research venture within AI
Using AI to individualise care for heart patients in Halland
International cross collaboration to help dementia patients
Victory in research competition for quality assurance of patient data
Reshaping healthcare through Artificial Intelligence
European initiative develops better healthcare solutions for patients with dementia
Intelligent maps will help robots navigate in your home
Scary or safe when monitored day and night?
Digital tools that motivate patients to take their medication
News article from March, 2021:
Joint human-machine learning can improve district heating
New article from November, 2020: Halmstad University in second place in an international AI competition
Annual reports
The key application areas for CAISR's research are healthcare technology and intelligent vehicles – something that is well in line with Halmstad University two profile areas Health Innovation and Smart Cities and Communities. Read more in CAISR's annual reports:
- CAISR Annual report 2019
- CAISR Annual report 2018
- CAISR Annual report 2017
- CAISR Annual report 2016
- CAISR Annual report 2015
- CAISR Annual report 2014
- CAISR Annual report 2013
- CAISR Annual report 2012
Halmstad University Profile Area Health Innovation
Halmstad University Profile Area Smart Cities and Communities
Publications EIS
The publications by ITE researchers registered in DiVA, which is Halmstad University’s online academic archive for scientific publishing, sorted after type of publication.
The 50 latest publications are listed below. See DiVA för a complete listing.
- Article in journal
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Guarese, Renan,
Andreasson, Pererik,
Nilsson, Emil,
Maciel, Anderson (2021). Augmented situated visualization methods towards electromagnetic compatibility testing. Computers & graphics, 94, s. 1 - 10.
View detailed record in DiVA
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Thunberg, Johan,
Sidorenko, Galina,
Sjöberg, Katrin,
Vinel, Alexey (2021). Efficiently Bounding the Probabilities of Vehicle Collision at Intelligent Intersections. IEEE Open Journal of Intelligent Transportation Systems.
View detailed record in DiVA
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Zhang, Chi,
Fanaee Tork, Hadi,
Thoresen, Magne (2021). Feature extraction from unequal length heterogeneous EHR time series via dynamic time warping and tensor decomposition. Data mining and knowledge discovery.
View detailed record in DiVA
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Corizzo, Roberto,
Ceci, Michelangelo,
Fanaee Tork, Hadi,
Gama, Joao (2021). Multi-aspect renewable energy forecasting. Information Sciences, 546, s. 701 - 722.
View detailed record in DiVA
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Sheikholharam Mashhadi, Peyman,
Nowaczyk, Sławomir,
Pashami, Sepideh (2021). Parallel orthogonal deep neural network. Neural Networks.
View detailed record in DiVA
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Khan, Taha,
Jacobs, Peter G. (2021). Prediction of Mild Cognitive Impairment Using Movement Complexity. IEEE journal of biomedical and health informatics, 25 (1), s. 227 - 236.
View detailed record in DiVA
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Chowdhury, Soumitra,
Åkesson, Maria,
Thomsen, Michel (2021). Service innovation in digitalized product platforms: An illustration of the implications of generativity on remote diagnostics of public transport buses. Technology in society, 65 (May).
View detailed record in DiVA
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Ullah, Sami,
Daud, Hanita,
Zainuddin, Nooraini,
Dass, Sarat C.,
Khalil, Alamgir,
Fanaee Tork, Hadi,
Khan, Ilyas (2021). Space-Time Cluster Analysis of Accidental Oil Spills in Rivers State, Nigeria, 2011–2019. Computers, Materials & Continua, 66 (3), s. 3065 - 3074.
View detailed record in DiVA
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Chalangar, Ebrahim,
Nur, Omer,
Willander, Magnus,
Gustafsson, Anders,
Pettersson, Håkan (2021). Synthesis of Vertically Aligned ZnO Nanorods Using Sol-gel Seeding and Colloidal Lithography Patterning. Nanoscale Research Letters, 16 (1).
View detailed record in DiVA
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Fernandes, Sofia,
(2021). Tensor decomposition for analysing time-evolving social networks: an overview. Artificial Intelligence Review, 54, s. 2891 - 2916.
View detailed record in DiVA
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Dai, Liang,
Bouguelia, Mohamed-Rafik (2021). Testing Exchangeability With Martingale for Change-Point Detection. International Journal of Ambient Computing and Intelligence (IJACI), 12 (2), s. 1 - 20.
View detailed record in DiVA
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Vinel, Alexey (2021). Welcome to Network: A New Open-Access Scientific Journal. Network.
View detailed record in DiVA
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Molinaro, Antonella,
Campolo, Claudia,
Härri, Jérôme,
Rothenberg, Christian Esteve,
Vinel, Alexey (2020). 5G-V2X Communications and Networking for Connected and Autonomous Vehicles. Future Internet, 12 (7).
View detailed record in DiVA
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Cohen, Tom,
Stilgoe, Jack,
Stares, Sally,
Akyelken, Nihan,
Cavoli, Clemence,
Day, Jennie,
Dickinson, Janet,
Fors, Vaike,
Hopkins, Debbie,
Lyons, Glenn,
Marres, Noortje,
Newman, Jonathan,
Reardon, Louise,
Sipe, Neil,
Tennant, Chris,
Wadud, Zia,
Wigley, Edward (2020). A constructive role for social science in the development of automated vehicles. Transport Research Interdisciplinary Perspectives, 6.
View detailed record in DiVA
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Savas, Süleyman,
Ul-Abdin, Zain,
Nordström, Tomas (2020). A Framework to Generate Domain-Specific Manycore Architectures from Dataflow Programs. Microprocessors and microsystems, 72.
View detailed record in DiVA
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Rabbani, Mahdi,
Wang, Young Li,
Khoshkangini, Reza,
Jelodar, Hamed,
Zhao, Ruxin,
Hu, Peng (2020). A Hybrid Machine Learning Approach for Malicious Behaviour Detection and Recognition in Cloud Computing. Journal of Network and Computer Applications, 151.
View detailed record in DiVA
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Aboelwafa, Mariam M. N.,
Seddik, Karim G.,
Eldefrawy, Mohamed Hamdy,
Gadallah, Yasser,
Gidlund, Mikael (2020). A Machine-Learning-Based Technique for False Data Injection Attacks Detection in Industrial IoT. IEEE Internet of Things Journal, 7 (9), s. 8462 - 8471.
View detailed record in DiVA
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Khan, Taha,
Zeeshan, Ali,
Dougherty, Mark (2020). A novel method for automatic classification of Parkinson gait severity using front-view video analysis. Technology and Health Care, s. 1 - 11.
View detailed record in DiVA
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Aramrattana, Maytheewat,
Larsson, Tony,
Englund, Cristofer,
Jansson, Jonas,
Nåbo, Arne (2020). A Simulation Study on Effects of Platooning Gaps on Drivers of Conventional Vehicles in Highway Merging Situations. IEEE transactions on intelligent transportation systems (Print).
View detailed record in DiVA
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Hylving, Lena,
Schultze, Ulrike (2020). Accomplishing the layered modular architecture in digital innovation : The case of the car’s driver information module. Journal of strategic information systems, 29 (3).
View detailed record in DiVA
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Duracz, Adam,
Aljarbouh, Ayman,
Bartha, Ferenc A.,
Masood, Jawad,
Philippsen, Roland,
Eriksson, Henrik,
Duracz, Jan,
Xu, Fei,
Zeng, Yingfu,
Grante, Christian (2020). Advanced Hazard Analysis and Risk Assessment in the ISO 26262 Functional Safety Standard Using Rigorous Simulation. Lecture Notes in Computer Science, 11971, s. 108 - 126.
View detailed record in DiVA
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Lyamin, Nikita,
Bellalta, Boris,
Vinel, Alexey (2020). Age-of-Information-Aware Decentralized Congestion Control in VANETs. IEEE Networking Letters, 2 (1), s. 33 - 37.
View detailed record in DiVA
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Penders, Bart,
Lutz, Peter,
Shaw, David M.,
Townend, David M. R. (2020). Allonymous science : the politics of placing and shifting credit in public-private nutrition research. Life, 16 (1).
View detailed record in DiVA
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Mansour, Osama,
Ghazawneh, Ahmad,
Askenäs, Linda (2020). An Affordances Apparatus for Enterprise Social Media. Scandinavian Journal of Information Systems, 32 (2), s. 3 - 42.
View detailed record in DiVA
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Järpe, Eric (2020). An alternative Diffie-Hellman protocol. Cryptography, 4 (1).
View detailed record in DiVA
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Lindgren, Thomas,
Fors, Vaike,
Pink, Sarah,
Osz, Katalin (2020). Anticipatory experience in everyday autonomous driving. Personal and Ubiquitous Computing, 24, s. 747 - 762.
View detailed record in DiVA
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Vedder, Benjamin,
Svensson, Bo Joel,
Vinter, Jonny,
Jonsson, Magnus (2020). Automated Testing of Ultrawideband Positioning for Autonomous Driving. Journal of Robotics, 2020.
View detailed record in DiVA
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Pelliccione, Patrizio,
Knauss, Eric,
Ågren, S. Magnus,
Heldal, Rogardt,
Bergenhem, Carl,
Vinel, Alexey,
Brunnegård, Oliver (2020). Beyond connected cars : A systems of systems perspective. Science of Computer Programming, 191.
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Ursby, Thomas,
Friel, R. J. (2020). BioMAX – the first macromolecular crystallography beamline at MAX IV Laboratory. Journal of Synchrotron Radiation, 27 (5), s. 1415 - 1429.
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Ortiz-Barrios, Miguel Angel,
Lundström, Jens,
Synnott, Jonathan,
Järpe, Eric,
Pinheiro Sant'Anna, Anita (2020). Complementing real datasets with simulated data : a regression-based approach. Multimedia tools and applications (79), s. 34301 - 34324.
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- Conference paper
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Baiocchi, Andrea,
Turcanu, Ion,
Lyamin, Nikita,
Sjöberg, Katrin,
Vinel, Alexey (2021). Age of Information in IEEE 802.11p. .
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Delooz, Quentin,
Riebl, Raphael,
Festag, Andreas,
Vinel, Alexey (2021). Design and Performance of Congestion-Aware Collective Perception. 2020 IEEE Vehicular Networking Conference (VNC).
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Chen, Kunru,
Pashami, Sepideh,
Nowaczyk, Sławomir,
Johansson, Emilia,
Sternelöv, Gustav,
Rögnvaldsson, Thorsteinn (2021). Forklift Truck Activity Recognition from CAN Data. IoT Streams for Data-Driven Predictive Maintenance and IoT, Edge, and Mobile for Embedded Machine Learning : Second International Workshop, IoT Streams 2020, and First International Workshop, ITEM 2020, Co-located with ECML/PKDD 2020, Ghent, Belgium, September 14-18, 2020, Revised Selected Papers. S. 119 - 126.
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Marques Marinho, Marco Antonio,
Gustafson, Per,
Antreich, Felix,
Caizzone, Stefano,
Vinel, Alexey (2021). Multi-Band Antenna Array Geometry Impact on Array Interpolation. .
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Hylving, Lena,
Lindberg, Susanne (2021). Practical Wisdom and Big Data Dilemmas : The Case of the Swedish Transport Administration. Proceedings of the 54th Hawaii International Conference on System Sciences. S. 5120 - 5129.
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Svanström, Fredrik,
Englund, Cristofer,
Alonso-Fernandez, Fernando (2021). Real-Time Drone Detection and Tracking With Visible, Thermal and Acoustic Sensors. .
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Cortinhal, Tiago,
Tzelepi, George,
Aksoy, Eren (2021). SalsaNext : Fast, Uncertainty-aware Semantic Segmentation of LiDAR Point Clouds for Autonomous Driving. Advances in Visual Computing : 15th International Symposium, ISVC 2020, San Diego, CA, USA, October 5–7, 2020, Proceedings, Part II.
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Alonso-Fernandez, Fernando,
Barrachina, Javier,
Hernandez-Diaz, Kevin,
Bigun, Josef (2021). SqueezeFacePoseNet : Lightweight Face Verification Across Different Poses for Mobile Platforms. .
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Aramrattana, Maytheewat,
Larsson, Tony,
Englund, Cristofer,
Jansson, Jonas,
Nåbo, Arne (2020). A Novel Risk Indicator for Cut-In Situations. 2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC).
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Duracz, A.,
Aljarbouh, A.,
Bartha, F. A.,
Masood, J.,
Philippsen, Roland,
Eriksson, H.,
Duracz, Jan,
Xu, Fei,
Zeng, Y.,
Grante, C. (2020). Advanced Hazard Analysis and Risk Assessment in the ISO 26262 Functional Safety Standard Using Rigorous Simulation. Cyber Physical Systems. Model-Based Design : 9th International Workshop, CyPhy 2019, and 15th International Workshop, WESE 2019, New York City, NY, USA, October 17-18, 2019, Revised Selected Papers. S. 108 - 126.
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Giambene, G.,
Rahman, M.D.S.,
Vinel, Alexey (2020). Analysis of V2V Sidelink Communications for Platoon Applications. .
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Englund, Cristofer (2020). Aware and intelligent infrastructure for action intention recognition of cars and bicycles. Proceedings of the 6th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1 : VEHITS. S. 281 - 288.
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Khoshkangini, Reza,
Nowaczyk, Sławomir,
Pashami, Sepideh (2020). Baysian Network for Failure Prediction in Different Seasons. Proceedings of the 30th European Safety and Reliability Conference and the 15th Probabilistic Safety Assessment and Management Conference. S. 1710 - 1710.
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Tkauc, Nathalie,
Tran, Thao,
Hernandez-Diaz, Kevin,
Alonso-Fernandez, Fernando (2020). Cloud-Based Face and Speech Recognition for Access Control Applications. .
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Carvajal, Gisela K.,
Keskin, Musa Furkan,
Aydogdu, Canan,
Eriksson, Olof,
Herbertsson, Hans,
Hellsten, Hans,
Nilsson, Emil,
Rydström, Mats,
Vanäs, Karl,
Wymeersch, Henk (2020). Comparison of Automotive FMCW and OFDM Radar Under Interference. 2020 IEEE Radar Conference (RadarConf20). S. 1 - 6.
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Araujo, Hugo,
Hoenselaar, Ties,
Mousavi, Mohammad Reza,
Vinel, Alexey (2020). Connected Automated Driving : A Model-Based Approach to the Analysis of Basic Awareness Services. 2020 IEEE 31st Annual International Symposium on Personal, Indoor and Mobile Radio Communications. S. 1 - 7.
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Hernandez-Diaz, Kevin,
Alonso-Fernandez, Fernando,
Bigun, Josef (2020). Cross-Spectral Periocular Recognition with Conditional Adversarial Networks. .
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- Licentiate thesis, comprehensive summary
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Galozy, Alexander,
(2021). Data-driven personalized healthcare
: Towards personalized interventions via reinforcement learning for Mobile Health. Lic.-avh. (sammanfattning). Halmstad : Halmstad University Press, 2021.
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Goncalves, Dulce,
(2021). Organizational Agility and Digital Innovation Capability in Automotive Startups. Lic.-avh. (sammanfattning). Halmstad : Halmstad University Press, 2021.
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- Other
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(2020). CAISR Center for Applied Intelligent Systems Research
: Annual Report 2019. , Halmstad. 63 s. .
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Research projects within EIS
The following research projects are currently ongoing within the research environment Embedded and Intelligent Systems (EIS) at the School of Information Technology (ITE).
Technology Area Aware Intelligent Systems
Technology Area Digital Service Innovation
Technology Area Smart Electronics Systems
Technology Area System of Cyber Physical Systems
Dissertations at EIS
The following doctoral and licentiate theses have been published within the research environment Embedded and Intelligent Systems (EIS):
CAISR Health
CAISR Health is a research profile within information driven care at Halmstad University, where research on the development of AI tools meet research on how these tools can be implemented in healthcare.
CAISR Health is a cross diciplinary research profile, gathering three research environments at Halmstad University. The research is carried out in close collaboration with Region Halland and Swedish companies. The abbreviation CAISR stands for Center for Applied Intelligent Systems Research which is a research center at Halmstad University that is strongly connected to the profile.
News and publications
CAISR Health partners.
