sensors-logo

Journal Browser

Journal Browser

Special Issue "Sensors Technology and Machine Learning for Human Activity Recognition"

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensors and Robotics".

Deadline for manuscript submissions: 31 August 2021.

Special Issue Editors

Prof. Alain Pegatoquet
E-Mail Website
Guest Editor
Université Côte d’Azur, CNRS, LEAT, 06903 Sophia Antipolis, France
Interests: edge computing; AI for embedded systems; wireless sensor networks for the IoT; power efficiency; low-power management policies
Prof. Benoît Miramond
E-Mail Website
Guest Editor
Université Côte d’Azur, CNRS, LEAT, 06903 Sophia Antipolis, France
Interests: embedded AI; artificial neural networks; bio-inspired AI; neuromorphic engineering; power efficiency; SoC design
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue of the Sensors journal entitled “Sensors Technology and Machine Learning for Human Activity Recognition” will focus on all aspects of research and development related to this area. Human Activity Recognition (HAR) has gained significant attention over the last few decades due to its wide range of applications and its promise in different domains such as health, sports, and entertainment. Moreover, the advent of the Internet of Things and wearable devices leads to a proliferation of use cases producing large datasets in various domains. A large amount of data can indeed be collected for the recognition of human activities using vision sensors, wearable devices, and smartphone sensors. Moreover, recent improvements in sensors industry leads to smaller, less expensive and less power consuming sensors, leading to emerging HAR applications and devices. In addition, HAR can be performed into or close to the sensor (near-sensor processing) bringing at the same time low-power consumption, low-latency and privacy properties. This new trend of bringing HAR at the edge can use different classification and machine learning approaches, with the aim at predicting the activity a user is performing among a set of known activities. Therefore, this Special Issue also intends to prompt emerging machine learning techniques, either supervised or unsupervised, for human activity recognition.

Despite continuous efforts, activity recognition is still a difficult task and faces many challenges, especially in an embedded context. This Special Issue aims at collecting the most recent advances in the area of human activity recognition. We are inviting the submission of original and unpublished work addressing several research topics of interest for HAR, including but not limited to the following issues:

  • Vision-based, wearable devices or smartphones sensors for HAR;
  • New sensor technologies;
  • IoT-based sensors for HAR;
  • Embedded Deep Learning;
  • Near-sensor processing (HAR at the edge);
  • Supervised, unsupervised learning methods for HAR;
  • HAR on microcontrollers;
  • HAR on wearable devices;
  • Sensors fusion for HAR (multi-modality);
  • Online learning for HAR.

All submitted papers will be peer-reviewed and selected based on both their quality and relevance. The guest editors maintain the right to reject papers they deem to be out of scope of this Special Issue. Only originally unpublished contributions will be considered for the issue. The papers should be formatted according to the journal guidelines.

Human Activity Recognition (HAR) has gained significant attention due to its wide range of applications and its promise in different domains such as health, sports, and entertainment. In this Special Issue of the Sensors journal entitled “Sensors Technology and Machine Learning for Human Activity Recognition”, we aim at collecting the most recent advances in the area of human activity recognition leveraging both sensors technology and machine learning approaches in the context of embedded systems.

Prof. Alain Pegatoquet
Prof. Benoît Miramond
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • health monitoring
  • IoT-based HAR
  • vision-based HAR
  • wearable devices or smartphones sensors
  • embedded machine learning
  • supervised learning
  • unsupervised learning
  • online learning

Published Papers

This special issue is now open for submission.
Back to TopTop