Smartphone-Based Human Activities Recognition System Using Deep Learning

Dear Colleagues,

Over the past decade, smartphones have revolutionized the way we interact with technology and each other, thanks to their widespread adoption, affordable prices, and advanced sensor capabilities. These devices are now central to many aspects of our daily lives, making them an invaluable tool for research and development in various fields.

This Special Issue aims to explore the potential of smartphones as powerful human activity recognition systems using deep learning techniques. By leveraging the power of smartphones' built-in sensors and the advancements in deep learning, researchers can develop innovative applications to enhance our understanding of human behavior, improve healthcare services, and contribute to a better quality of life.

We invite authors to submit original research articles, works in progress, or surveys on topics related to smartphone-based human activity recognition systems using deep learning. Relevant topics include, but are not limited to, the following:

• Deep learning algorithms for interpreting smartphone sensor data;
• Human activity recognition using smartphone sensors and deep learning methods;
• Context-aware analysis of sensor data for improved activity recognition;
• Applications of deep learning in healthcare, including injury prevention, rehabilitation, and medication compliance;
• The evaluation and benchmarking of deep learning methods for human activity recognition;
• Privacy and security considerations in smartphone-based activity recognition systems;
• Real-time processing and energy efficiency in deep learning-based activity recognition;
• The integration of smartphone sensor data with other sources for enhanced activity recognition.

By focusing on the intersection of smartphones, deep learning, and human activity recognition, this Special Issue aims to foster interdisciplinary research and drive innovations that will benefit individuals and society as a whole.

Dr. Chifumi Iseki
Guest Editor

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. 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 2600 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.