Deep Learning Applications on Human Activity Recognition
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Artificial Intelligence".
Deadline for manuscript submissions: 20 December 2025 | Viewed by 42
Special Issue Editors
Interests: point cloud analysis and registration; differential entropy analysis; machine vision; human pose estimation; deep learning application
Interests: discrete geometries; 3D scanning; geometric segmentation; augmented reality
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Human activity recognition (HAR) has become a key technology with transformative applications in healthcare, smart environments, security, sports analytics, and human–computer interaction. The adoption of deep learning has significantly enhanced HAR capabilities, enabling the more accurate and scalable recognition of human activities from sensor data, video streams, and multimodal sources.
This Special Issue aims to showcase cutting-edge applications of deep learning in HAR, emphasizing real-world implementations and their impact on various domains. We invite high-quality original research articles and comprehensive reviews that explore how deep learning is being leveraged to improve activity recognition in practical settings. Contributions that address challenges related to data collection, deployment in real-world scenarios, and integration with emerging technologies such as the IoT, wearable devices, and smart cities are particularly encouraged.
Topics of interest include, but are not limited to, the following:
- Industrial and workplace safety applications.
- Healthcare applications of HAR, including rehabilitation monitoring.
- Activity recognition in sports and fitness tracking.
- HAR in human–computer interaction and augmented reality.
- Real-time HAR applications in smart environments.
- HAR in autonomous systems and robotics.
- HAR for security and surveillance.
- Smart home and smart city applications using HAR.
- Sensor-based activity recognition using deep learning.
- Computer-vision-based HAR.
- Multimodal data fusion for HAR.
We welcome contributions that present novel applications, case studies, and implementations demonstrating the impact of deep learning on HAR across various domains.
Dr. Emmanuele Barberi
Dr. Emanuele Guardiani
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 submissions that pass pre-check are 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. Electronics 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 2400 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
- human activity recognition
- deep learning applications
- computer vision
- healthcare and smart environments
- sports analytics
- wearable sensor technology
- real-time HAR
- security and surveillance
- IoT and smart cities
Benefits of Publishing in a Special Issue
- Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
- Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
- Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
- External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
- Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.
Further information on MDPI's Special Issue policies can be found here.
