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Tittel [sv]
Dynamic Intelligent Sensor Intensive Systems
Tittel [en]
Dynamic Intelligent Sensor Intensive Systems
Abstract [sv]

This project is about how to best support services which need information about the current state of an environment where people are present and may interact with the services. The main challenges concern how to make use of heterogeneous sensor data and to make use of input by people to the system (e.g. user feedback). Further, in order to support services, including the implementation of new service, the project also address challenges of how to support: smart configuration and information security. The challenge of smart configuration, in particular, concerns the rapid configuration of the software for the detection of states. Information security concerns the influence and protection against non-benevolent users. The project intends to explore machine learning and Interactive Machine Learning (IML) to enhance the previously introduced concept of Dynamic Intelligent Virtual Sensor in different use cases, such as, activity detection in office spaces and people count in large buildings etc. It further aims to improve the design of the system-interaction for learning in order to improve the performance

Collaborators: Axis Communications and Sigma Connectivity.

Abstract [en]

This project is about how to best support services which need information about the current state of an environment where people are present and may interact with the services. The main challenges concern how to make use of heterogeneous sensor data and to make use of input by people to the system (e.g. user feedback). Further, in order to support services, including the implementation of new service, the project also address challenges of how to support: smart configuration and information security. The challenge of smart configuration, in particular, concerns the rapid configuration of the software for the detection of states. Information security concerns the influence and protection against non-benevolent users. The project intends to explore machine learning and Interactive Machine Learning (IML) to enhance the previously introduced concept of Dynamic Intelligent Virtual Sensor in different use cases, such as, activity detection in office spaces and people count in large buildings etc. It further aims to improve the design of the system-interaction for learning in order to improve the performance

Collaborators: Axis Communications and Sigma Connectivity.

Publikasjoner (1 av 1) Visa alla publikasjoner
Persson, J. A., Bugeja, J., Davidsson, P., Holmberg, J., Kebande, V. R., Mihailescu, R.-C., . . . Tegen, A. (2023). The Concept of Interactive Dynamic Intelligent Virtual Sensors (IDIVS): Bridging the Gap between Sensors, Services, and Users through Machine Learning. Applied Sciences, 13(11), Article ID 6516.
Åpne denne publikasjonen i ny fane eller vindu >>The Concept of Interactive Dynamic Intelligent Virtual Sensors (IDIVS): Bridging the Gap between Sensors, Services, and Users through Machine Learning
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2023 (engelsk)Inngår i: Applied Sciences, E-ISSN 2076-3417, Vol. 13, nr 11, artikkel-id 6516Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

This paper concerns the novel concept of an Interactive Dynamic Intelligent Virtual Sensor (IDIVS), which extends virtual/soft sensors towards making use of user input through interactive learning (IML) and transfer learning. In research, many studies can be found on using machine learning in this domain, but not much on using IML. This paper contributes by highlighting how this can be done and the associated positive potential effects and challenges. An IDIVS provides a sensor-like output and achieves the output through the data fusion of sensor values or from the output values of other IDIVSs. We focus on settings where people are present in different roles: from basic service users in the environment being sensed to interactive service users supporting the learning of the IDIVS, as well as configurators of the IDIVS and explicit IDIVS teachers. The IDIVS aims at managing situations where sensors may disappear and reappear and be of heterogeneous types. We refer to and recap the major findings from related experiments and validation in complementing work. Further, we point at several application areas: smart building, smart mobility, smart learning, and smart health. The information properties and capabilities needed in the IDIVS, with extensions towards information security, are introduced and discussed.

sted, utgiver, år, opplag, sider
MDPI, 2023
HSV kategori
Identifikatorer
urn:nbn:se:mau:diva-60144 (URN)10.3390/app13116516 (DOI)001004726600001 ()2-s2.0-85163091186 (Scopus ID)
Tilgjengelig fra: 2023-06-07 Laget: 2023-06-07 Sist oppdatert: 2023-09-05bibliografisk kontrollert
Project OfficerPersson, Jan A.
Co-InvestigatorDavidsson, Paul
Co-InvestigatorMihailescu, Radu-Casian
Co-InvestigatorSarkheyli-Hägele, Arezoo
Co-InvestigatorGhajargar, Maliheh
Koordinerande organisasjon
Malmö universitet
Forskningsfinansiär
Tidsperiod
2020-01-01 - 2021-12-31
Identifikatorer
DiVA, id: project:2742

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