The Concept of Interactive Dynamic Intelligent Virtual Sensors (IDIVS): Bridging the Gap between Sensors, Services, and Users through Machine Learning

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 d...

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Bibliographic Details
Published in:Applied sciences 2023-05, Vol.13 (11), p.6516
Main Authors: Persson, Jan A., Bugeja, Joseph, Davidsson, Paul, Holmberg, Johan, Kebande, Victor R., Mihailescu, Radu-Casian, Sarkheyli-Hägele, Arezoo, Tegen, Agnes
Format: Article
Language:English
Subjects:
Access control
Data integration
Distance learning
Feedback
Interactive learning
interactive machine learning
Internet of Things
Learning algorithms
Machine learning
Multimedia industry
Multisensor fusion
online learning
sensor data fusion
Sensors
Smartphones
soft sensors
Software
Transfer learning
Virtual reality
Virtual sensors
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Summary: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.
ISSN:2076-3417
2076-3417
DOI:10.3390/app13116516