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Alkhabbas, F., Alawadi, S., Ayyad, M., Spalazzese, R. & Davidsson, P. (2023). ART4FL: An Agent-Based Architectural Approach for Trustworthy Federated Learning in the IoT. In: 2023 Eighth International Conference on Fog and Mobile Edge Computing (FMEC): . Paper presented at 2023 Eighth International Conference on Fog and Mobile Edge Computing (FMEC), Tartu, Estonia, 18-20 September 2023. Institute of Electrical and Electronics Engineers (IEEE)
Åpne denne publikasjonen i ny fane eller vindu >>ART4FL: An Agent-Based Architectural Approach for Trustworthy Federated Learning in the IoT
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2023 (engelsk)Inngår i: 2023 Eighth International Conference on Fog and Mobile Edge Computing (FMEC), Institute of Electrical and Electronics Engineers (IEEE), 2023Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

The integration of the Internet of Things (IoT) and Machine Learning (ML) technologies has opened up for the development of novel types of systems and services. Federated Learning (FL) has enabled the systems to collaboratively train their ML models while preserving the privacy of the data collected by their IoT devices and objects. Several FL frameworks have been developed, however, they do not enable FL in open, distributed, and heterogeneous IoT environments. Specifically, they do not support systems that collect similar data to dynamically discover each other, communicate, and negotiate about the training terms (e.g., accuracy, communication latency, and cost). Towards bridging this gap, we propose ART4FL, an end-to-end framework that enables FL in open IoT settings. The framework enables systems' users to configure agents that participate in FL on their behalf. Those agents negotiate and make commitments (i.e., contractual agreements) to dynamically form federations. To perform FL, the framework deploys the needed services dynamically, monitors the training rounds, and calculates agents' trust scores based on the established commitments. ART4FL exploits a blockchain network to maintain the trust scores, and it provides those scores to negotiating agents' during the federations' formation phase.

sted, utgiver, år, opplag, sider
Institute of Electrical and Electronics Engineers (IEEE), 2023
HSV kategori
Identifikatorer
urn:nbn:se:mau:diva-63749 (URN)10.1109/fmec59375.2023.10306036 (DOI)001103180200036 ()2-s2.0-85179515213 (Scopus ID)979-8-3503-1697-1 (ISBN)979-8-3503-1698-8 (ISBN)
Konferanse
2023 Eighth International Conference on Fog and Mobile Edge Computing (FMEC), Tartu, Estonia, 18-20 September 2023
Tilgjengelig fra: 2023-11-20 Laget: 2023-11-20 Sist oppdatert: 2023-12-28bibliografisk kontrollert
Spalazzese, R., De Sanctis, M., Alkhabbas, F. & Davidsson, P. (2023). Shaping IoT Systems Together: The User-System Mixed-Initiative Paradigm and Its Challenges. In: Bedir Tekinerdogan, Catia Trubiani, Chouki Tibermacine, Patrizia Scandurra, Carlos E. Cuesta (Ed.), Software Architecture: 17th European Conference, ECSA 2023, Istanbul, Turkey, September 18–22, 2023, Proceedings. Paper presented at 17th European Conference, ECSA 2023, Istanbul, Turkey, September 18–22, 2023 (pp. 221-229). Springer
Åpne denne publikasjonen i ny fane eller vindu >>Shaping IoT Systems Together: The User-System Mixed-Initiative Paradigm and Its Challenges
2023 (engelsk)Inngår i: Software Architecture: 17th European Conference, ECSA 2023, Istanbul, Turkey, September 18–22, 2023, Proceedings / [ed] Bedir Tekinerdogan, Catia Trubiani, Chouki Tibermacine, Patrizia Scandurra, Carlos E. Cuesta, Springer, 2023, s. 221-229Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Internet of Things (IoT) systems are often complex and have to deal with many challenges at the same time, both from a human and technical perspective. In this vision paper, we (i) describe IoT-Together , the Mixed-initiative Paradigm that we devise for IoT user-system collaboration and (ii) critically analyze related architectural challenges.

sted, utgiver, år, opplag, sider
Springer, 2023
Serie
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 14212
Emneord
Mixed-initiative paradigm, User-System Collaboration, Intelligent IoT Systems, Novel Experiences, Goal-driven IoT Systems
HSV kategori
Identifikatorer
urn:nbn:se:mau:diva-64271 (URN)10.1007/978-3-031-42592-9_15 (DOI)2-s2.0-85172136763 (Scopus ID)978-3-031-42591-2 (ISBN)978-3-031-42592-9 (ISBN)
Konferanse
17th European Conference, ECSA 2023, Istanbul, Turkey, September 18–22, 2023
Tilgjengelig fra: 2023-12-12 Laget: 2023-12-12 Sist oppdatert: 2023-12-12bibliografisk kontrollert
Alkhabbas, F., De Sanctis, M., Bucchiarone, A., Cicchetti, A., Spalazzese, R., Davidsson, P. & Iovino, L. (2022). ROUTE: A Framework for Customizable Smart Mobility Planners. In: IEEE 19TH INTERNATIONAL CONFERENCE ON SOFTWARE ARCHITECTURE (ICSA 2022): . Paper presented at 19th IEEE International Conference on Software Architecture (ICSA), MAR 12-15, 2022, Honolulu, HI, USA (pp. 169-179). Institute of Electrical and Electronics Engineers (IEEE)
Åpne denne publikasjonen i ny fane eller vindu >>ROUTE: A Framework for Customizable Smart Mobility Planners
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2022 (engelsk)Inngår i: IEEE 19TH INTERNATIONAL CONFERENCE ON SOFTWARE ARCHITECTURE (ICSA 2022), Institute of Electrical and Electronics Engineers (IEEE), 2022, s. 169-179Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Multimodal journey planners are used worldwide to support travelers in planning and executing their journeys. Generated travel plans usually involve local mobility service providers, consider some travelers' preferences, and provide travelers information about the routes' current status and expected delays. However, those planners cannot fully consider the special situations of individual cities when providing travel planning services. Specifically, authorities of different cities might define customizable regulations or constraints of movements in the cities (e.g., due to construction works or pandemics). Moreover, with the transformation of traditional cities into smart cities, travel planners could leverage advanced monitoring features. Finally, most planners do not consider relevant information impacting travel plans, for instance, information that might be provided by travelers (e.g., a crowded square) or by mobility service providers (e.g., changing the timetable of a bus). To address the aforementioned shortcomings, in this paper, we propose ROUTE, a framework for customizable smart mobility planners that better serve the needs of travelers, local authorities, and mobility service providers in the dynamic ecosystem of smart cities. ROUTE is composed of an architecture, a process, and a prototype developed to validate the feasibility of the framework. Experiments' results show that the framework scales well in both centralized and distributed deployment settings.

sted, utgiver, år, opplag, sider
Institute of Electrical and Electronics Engineers (IEEE), 2022
Emneord
Multimodal Journey Planners, Software Framework, Multi-tier Architecture, Smart Mobility
HSV kategori
Identifikatorer
urn:nbn:se:mau:diva-55117 (URN)10.1109/ICSA53651.2022.00024 (DOI)000838691200016 ()2-s2.0-85132012974 (Scopus ID)978-1-6654-1728-0 (ISBN)978-1-6654-1729-7 (ISBN)
Konferanse
19th IEEE International Conference on Software Architecture (ICSA), MAR 12-15, 2022, Honolulu, HI, USA
Tilgjengelig fra: 2022-09-23 Laget: 2022-09-23 Sist oppdatert: 2024-01-11bibliografisk kontrollert
Alkhabbas, F., Spalazzese, R. & Davidsson, P. (2021). Human-Centric Emergent Configurations: Supporting the User Through Self-configuring IoT Systems. In: Hasan Ayaz; Umer Asgher; Lucas Paletta (Ed.), Advances in Neuroergonomics and Cognitive Engineering: Proceedings of the AHFE 2021 Virtual Conferences on Neuroergonomics and Cognitive Engineering, Industrial Cognitive Ergonomics and Engineering Psychology, and Cognitive Computing and Internet of Things, July 25-29, 2021, USA. Paper presented at AHFE 2021 Virtual Conferences on Neuroergonomics and Cognitive Engineering, Industrial Cognitive Ergonomics and Engineering Psychology, and Cognitive Computing and Internet of Things, July 25-29, 2021, USA (pp. 411-418). Springer
Åpne denne publikasjonen i ny fane eller vindu >>Human-Centric Emergent Configurations: Supporting the User Through Self-configuring IoT Systems
2021 (engelsk)Inngår i: Advances in Neuroergonomics and Cognitive Engineering: Proceedings of the AHFE 2021 Virtual Conferences on Neuroergonomics and Cognitive Engineering, Industrial Cognitive Ergonomics and Engineering Psychology, and Cognitive Computing and Internet of Things, July 25-29, 2021, USA / [ed] Hasan Ayaz; Umer Asgher; Lucas Paletta, Springer, 2021, s. 411-418Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

The Internet of Things (IoT) is revolutionizing our environments with novel types of services and applications by exploiting the large number of diverse connected things. One of the main challenges in the IoT is to engineer systems to support human users to achieve their goals in dynamic and uncertain environments. For instance, the mobility of both users and devices makes it infeasible to always foresee the available things in the users’ current environments. Moreover, users’ activities and/or goals might change suddenly. To support users in such environments, we developed an initial approach that exploits the notion of Emergent Configurations (ECs) and mixed initiative techniques to engineer self-configuring IoT systems. An EC is a goal-driven IoT system composed of a dynamic set of temporarily connecting and cooperating things. ECs are more flexible and usable than IoT systems whose constituents and interfaces are fully specified at design time

sted, utgiver, år, opplag, sider
Springer, 2021
Serie
Lecture Notes in Networks and Systems, ISSN 2367-3370, E-ISSN 2367-3389 ; 259
Emneord
Dynamic generation of user interfaces, Human-centric emergent configurations, Internet of Things
HSV kategori
Identifikatorer
urn:nbn:se:mau:diva-45120 (URN)10.1007/978-3-030-80285-1_48 (DOI)2-s2.0-85112111445 (Scopus ID)9783030802844 (ISBN)
Konferanse
AHFE 2021 Virtual Conferences on Neuroergonomics and Cognitive Engineering, Industrial Cognitive Ergonomics and Engineering Psychology, and Cognitive Computing and Internet of Things, July 25-29, 2021, USA
Tilgjengelig fra: 2021-08-23 Laget: 2021-08-23 Sist oppdatert: 2023-12-28bibliografisk kontrollert
Becker, S., Camara, J., Challita, S., Fehling, C., Jansen, A., Kopp, O., . . . Trubiani, C. (2021). Message from the SAIP, NEMI, ECRF, Journal First, and Workshops Track Chairs. Paper presented at 18th IEEE International Conference on Software Architecture (ICSA 2021), 22-26 March 2021, Stuttgart, Germany. Proc. - IEEE Int. Conf. Softw. Archit. Companion, ICSA-C, 18, x-xi, Article ID 9425850.
Åpne denne publikasjonen i ny fane eller vindu >>Message from the SAIP, NEMI, ECRF, Journal First, and Workshops Track Chairs
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2021 (engelsk)Inngår i: Proc. - IEEE Int. Conf. Softw. Archit. Companion, ICSA-C, Vol. 18, s. x-xi, artikkel-id 9425850Artikkel i tidsskrift, Editorial material (Annet vitenskapelig) Published
Abstract [en]

The 18th IEEE International Conference on Software Architecture (ICSA 2021) solicited different types of submissions structured into the following tracks: The main Technical Track (included in the ICSA main proceedings), the Software Architecture in Practice (SAIP) track, the New and Emerging Ideas (NEMI) track, the Early Career Researchers Forum (ECRF), the Journal First track, and the Workshop track (included in the companion volume of ICSA 2021 proceedings). Each of these tracks, except for the Technical Track, is presented in the following sections. © 2021 IEEE.

sted, utgiver, år, opplag, sider
IEEE, 2021
HSV kategori
Identifikatorer
urn:nbn:se:mau:diva-44134 (URN)10.1109/ICSA-C52384.2021.00006 (DOI)2-s2.0-85106629685 (Scopus ID)
Konferanse
18th IEEE International Conference on Software Architecture (ICSA 2021), 22-26 March 2021, Stuttgart, Germany
Tilgjengelig fra: 2021-06-23 Laget: 2021-06-23 Sist oppdatert: 2023-12-28bibliografisk kontrollert
Ashouri, M., Davidsson, P. & Spalazzese, R. (2021). Quality attributes in edge computing for the Internet of Things: A systematic mapping study. Internet of Things: Engineering Cyber Physical Human Systems, 13, Article ID 100346.
Åpne denne publikasjonen i ny fane eller vindu >>Quality attributes in edge computing for the Internet of Things: A systematic mapping study
2021 (engelsk)Inngår i: Internet of Things: Engineering Cyber Physical Human Systems, E-ISSN 2542-6605, Vol. 13, artikkel-id 100346Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Many Internet of Things (IoT) systems generate a massive amount of data needing to be processed and stored efficiently. Cloud computing solutions are often used to handle these tasks. However, the increasing availability of computational resources close to the edge has prompted the idea of using these for distributed computing and storage. Edge computing may help to improve IoT systems regarding important quality attributes like latency, energy consumption, privacy, and bandwidth utilization. However, deciding where to deploy the various application components is not a straightforward task. This is largely due to the trade-offs between the quality attributes relevant for the application. We have performed a systematic mapping study of 98 articles to investigate which quality attributes have been used in the literature for assessing IoT systems using edge computing. The analysis shows that time behavior and resource utilization are the most frequently used quality attributes; further, response time, turnaround time, and energy consumption are the most used metrics for quantifying these quality attributes. Moreover, simulation is the main tool used for the assessments, and the studied trade-offs are mainly between only two qualities. Finally, we identified a number of research gaps that need further study.

sted, utgiver, år, opplag, sider
Elsevier, 2021
Emneord
Internet of Things, Edge computing, Quality attributes, Metrics, Systematic mapping study
HSV kategori
Identifikatorer
urn:nbn:se:mau:diva-39120 (URN)10.1016/j.iot.2020.100346 (DOI)000695695700015 ()2-s2.0-85106740791 (Scopus ID)
Tilgjengelig fra: 2021-01-13 Laget: 2021-01-13 Sist oppdatert: 2024-02-05bibliografisk kontrollert
Alkhabbas, F., Murturi, I., Spalazzese, R., Davidsson, P. & Dustdar, S. (2020). A Goal driven Approach for Deploying Self-adaptive IoT Systems. In: Lisa O’Conner (Ed.), Proceedings: 2020 IEEE International Conference on Software Architecture (ICSA), Salvador, Brazil, 16-20 March 2020. Paper presented at IEEE International Conference on Software Architecture (ICSA), Salvador, Brazil, 16-20 March 2020 (pp. 146-156).
Åpne denne publikasjonen i ny fane eller vindu >>A Goal driven Approach for Deploying Self-adaptive IoT Systems
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2020 (engelsk)Inngår i: Proceedings: 2020 IEEE International Conference on Software Architecture (ICSA), Salvador, Brazil, 16-20 March 2020 / [ed] Lisa O’Conner, 2020, s. 146-156Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Engineering Internet of Things (IoT) systems is a challenging task partly due to the dynamicity and uncertainty of the environment including the involvement of the human in the loop. Users should be able to achieve their goals seamlessly in different environments, and IoT systems should be able to cope with dynamic changes. Several approaches have been proposed to enable the automated formation, enactment, and self-adaptation of goal-driven IoT systems. However, they do not address deployment issues. In this paper, we propose a goal-driven approach for deploying self-adaptive IoT systems in the Edge-Cloud continuum. Our approach supports the systems to cope with the dynamicity and uncertainty of the environment including changes in their deployment topologies, i.e., the deployment nodes and their interconnections. We describe the architecture and processes of the approach and the simulations that we conducted to validate its feasibility. The results of the simulations show that the approach scales well when generating and adapting the deployment topologies of goal-driven IoT systems in smart homes and smart buildings.

HSV kategori
Identifikatorer
urn:nbn:se:mau:diva-36984 (URN)10.1109/ICSA47634.2020.00022 (DOI)000584237000014 ()2-s2.0-85085928360 (Scopus ID)978-1-7281-4659-1 (ISBN)978-1-7281-4660-7 (ISBN)
Konferanse
IEEE International Conference on Software Architecture (ICSA), Salvador, Brazil, 16-20 March 2020
Tilgjengelig fra: 2020-11-26 Laget: 2020-11-26 Sist oppdatert: 2024-02-05bibliografisk kontrollert
Alkhabbas, F., Alawadi, S., Spalazzese, R. & Davidsson, P. (2020). Activity Recognition and User Preference Learning for Automated Configuration of IoT Environments. In: IoT '20: Proceedings of the 10th International Conference on the Internet of Things. Paper presented at IoT '20: 10th International Conference on the Internet of Things, Malmö Sweden 6-9 October, 2020 (pp. 1-8). New York, United States: ACM Digital Library, Article ID 3.
Åpne denne publikasjonen i ny fane eller vindu >>Activity Recognition and User Preference Learning for Automated Configuration of IoT Environments
2020 (engelsk)Inngår i: IoT '20: Proceedings of the 10th International Conference on the Internet of Things, New York, United States: ACM Digital Library, 2020, s. 1-8, artikkel-id 3Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Internet of Things (IoT) environments encompass different types of devices and objects that offer a wide range of services. The dynamicity and uncertainty of those environments, including the mobility of users and devices, make it hard to foresee at design time available devices, objects, and services. For the users to benefit from such environments, they should be proposed services that are relevant to the specific context and can be provided by available things. Moreover, environments should be configured automatically based on users' preferences. To address these challenges, we propose an approach that leverages Artificial Intelligence techniques to recognize users' activities and provides relevant services to support users to perform their activities. Moreover, our approach learns users' preferences and configures their environments accordingly by dynamically forming, enacting, and adapting goal-driven IoT systems. In this paper, we present a conceptual model, a multi-tier architecture, and processes of our approach. Moreover, we report about how we validated the feasibility and evaluated the scalability of the approach through a prototype that we developed and used.

sted, utgiver, år, opplag, sider
New York, United States: ACM Digital Library, 2020
HSV kategori
Identifikatorer
urn:nbn:se:mau:diva-36986 (URN)10.1145/3410992.3411003 (DOI)2-s2.0-85123041965 (Scopus ID)978-1-4503-8758-3 (ISBN)
Konferanse
IoT '20: 10th International Conference on the Internet of Things, Malmö Sweden 6-9 October, 2020
Tilgjengelig fra: 2020-11-26 Laget: 2020-11-26 Sist oppdatert: 2024-02-05bibliografisk kontrollert
Alkhabbas, F., Spalazzese, R. & Davidsson, P. (2020). An Agent-based Approach to Realize Emergent Configurationsin the Internet of Things. Electronics, 9(9), Article ID 1347.
Åpne denne publikasjonen i ny fane eller vindu >>An Agent-based Approach to Realize Emergent Configurationsin the Internet of Things
2020 (engelsk)Inngår i: Electronics, E-ISSN 2079-9292, Vol. 9, nr 9, artikkel-id 1347Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

The Internet of Things (IoT) has enabled physical objects and devices, often referred to as things, to connect and communicate. This has opened up for the development of novel types of services that improve the quality of our daily lives. The dynamicity and uncertainty of IoT environments, including the mobility of users and devices, make it hard to foresee at design time available things and services. Further, users should be able to achieve their goals seamlessly in arbitrary environments. To address these challenges, we exploit Artificial Intelligence (AI) to engineer smart IoT systems that can achieve user goals and cope with the dynamicity and uncertainty of their environments. More specifically, the main contribution of this paper is an approach that leverages the notion of Belief-Desire-Intention agents and Machine Learning (ML) techniques to realize Emergent Configurations (ECs) in the IoT. An EC is an IoT system composed of a dynamic set of things that connect and cooperate temporarily to achieve a user goal. The approach enables the distributed formation, enactment, adaptation of ECs, and conflict resolution among them. We present a conceptual model of the entities of the approach, its underlying processes, and the guidelines for using it. Moreover, we report about the simulations conducted to validate the feasibility of the approach and evaluate its scalability. View Full-Text

sted, utgiver, år, opplag, sider
MDPI, 2020
Emneord
emergent configurations; artificial intelligence; self-adaptive IoT systems
HSV kategori
Identifikatorer
urn:nbn:se:mau:diva-36985 (URN)10.3390/electronics9091347 (DOI)000580061200001 ()2-s2.0-85089677698 (Scopus ID)
Tilgjengelig fra: 2020-11-26 Laget: 2020-11-26 Sist oppdatert: 2024-02-05bibliografisk kontrollert
Ashouri, M., Lorig, F., Davidsson, P., Spalazzese, R. & Svorobej, S. (2020). Analyzing Distributed Deep Neural Network Deployment on Edge and Cloud Nodes in IoT Systems. In: IEEE International Conference on Edge Computing (EDGE), Virtual conference, October 18–24, 2020.: . Paper presented at IEEE International Conference on Edge Computing (EDGE) 2020. 19-23 Oct. 2020. Beijing, China (pp. 59-66).
Åpne denne publikasjonen i ny fane eller vindu >>Analyzing Distributed Deep Neural Network Deployment on Edge and Cloud Nodes in IoT Systems
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2020 (engelsk)Inngår i: IEEE International Conference on Edge Computing (EDGE), Virtual conference, October 18–24, 2020., 2020, s. 59-66Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

For the efficient execution of Deep Neural Networks (DNN) in the Internet of Things, computation tasks can be distributed and deployed on edge nodes. In contrast to deploying all computation to the cloud, the use of Distributed DNN (DDNN) often results in a reduced amount of data that is sent through the network and thus might increase the overall performance of the system. However, finding an appropriate deployment scenario is often a complex task and requires considering several criteria. In this paper, we introduce a multi-criteria decision-making method based on the Analytical Hierarchy Process for the comparison and selection of deployment alternatives. We use the RECAP simulation framework to model and simulate DDNN deployments on different scales to provide a comprehensive assessment of deployments to system designers. In a case study, we apply the method to a smart city scenario where different distributions and deployments of a DNN are analyzed and compared.

Emneord
Edge Computing, Internet of Things, Distributed Deep Neural Networks, Simulation, Smart Cities
HSV kategori
Identifikatorer
urn:nbn:se:mau:diva-37023 (URN)10.1109/EDGE50951.2020.00017 (DOI)000659316400010 ()2-s2.0-85100251401 (Scopus ID)978-1-7281-8254-4 (ISBN)978-1-7281-8255-1 (ISBN)
Konferanse
IEEE International Conference on Edge Computing (EDGE) 2020. 19-23 Oct. 2020. Beijing, China
Tilgjengelig fra: 2020-11-27 Laget: 2020-11-27 Sist oppdatert: 2024-02-05bibliografisk kontrollert
Prosjekter
Forskningsprofilen Internet of Things and People; Malmö universitet; Publikasjoner
Banda, L., Mjumo, M. & Mekuria, F. (2022). Business Models for 5G and Future Mobile Network Operators. In: 2022 IEEE Future Networks World Forum (FNWF): . Paper presented at IEEE Future Networks World Forum FNWF 2022, Montreal, QC, Canada, 10-14 October 2022. IEEE, Article ID M17754.
Emergent Configurations for IoT Systems – ECOS+; Malmö universitetAVANS projekt: "Internet of Things Master's Program"; Malmö universitetInteraktion mellan människor och omgivning i Internet of Things-ekosystem: Design av uppkopplade system för energi-management i smarta byggnader för hållbarhet; Malmö universitet, Internet of Things and People (IOTAP)
Organisasjoner
Identifikatorer
ORCID-id: ORCID iD iconorcid.org/0000-0003-0326-0556