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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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Published in: | Applied sciences 2023-05, Vol.13 (11), p.6516 |
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creator | Persson, Jan A. Bugeja, Joseph Davidsson, Paul Holmberg, Johan Kebande, Victor R. Mihailescu, Radu-Casian Sarkheyli-Hägele, Arezoo Tegen, Agnes |
description | 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. |
doi_str_mv | 10.3390/app13116516 |
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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 |
title | The Concept of Interactive Dynamic Intelligent Virtual Sensors (IDIVS): Bridging the Gap between Sensors, Services, and Users through Machine Learning |
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