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Next Generation Mobile Sensors: Review Regarding the Significance of Deep Learning and Privacy Techniques for Data-Driven Soft Sensors

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Advanced Information Networking and Applications (AINA 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 655))

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Abstract

The increasing usage of mobile devices amounts to around 6.8 billion by 2022. This implies a substantial increase in the quantity of personal data that are managed. The paper surveys the most relevant contributions that pertain to human activity, behavioural patterns detection, demographics, health and body parameters. Moreover, significant aspects regarding data privacy are also analyzed. The paper also defines relevant research questions and challenges.

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Authors and Affiliations

  1. Department of Mathematics and Computer Science, Transilvania University of Brasov, 500036, Brașov, Romania

    Razvan Bocu & Dorin Bocu

  2. Department of Research and Technology, Siemens Industry Software, 500203, Brașov, Romania

    Razvan Bocu

Authors
  1. Razvan Bocu
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  2. Dorin Bocu
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Correspondence to Razvan Bocu .

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Editors and Affiliations

  1. Department of Information and Communication Engineering, Faculty of Information Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

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Bocu, R., Bocu, D. (2023). Next Generation Mobile Sensors: Review Regarding the Significance of Deep Learning and Privacy Techniques for Data-Driven Soft Sensors. In: Barolli, L. (eds) Advanced Information Networking and Applications. AINA 2023. Lecture Notes in Networks and Systems, vol 655. Springer, Cham. https://doi.org/10.1007/978-3-031-28694-0_1

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