Data Driven Human Activity Recognition in Smart World
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".
Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 3017
Special Issue Editors
Interests: human activity recognition; wearables; sensors
Interests: audio analyzing; AI; computer vision; robotics; deep learning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Human behavior recognition integrates multi-disciplinary knowledge, such as artificial intelligence, image processing, computer vision theory, sensors, and cognitive science. It has a wide range of application scenarios in video surveillance, human–computer interaction, automatic driving, health and fitness detection, meta-universe, and other aspects. It is also a research hotspot and a key direction for researchers from various countries in recent years.
Currently, the research work in the field of behavior recognition mainly focuses on the following three aspects: based on wearable sensors, video image detection, and radio frequency signal recognition. However, no matter these methods are inseparable from sensors, human behavior data acquisition needs a variety of sensor cooperation. The leading equipment based on sensor behavior recognition is an infrared sensor, acceleration sensor, photoelectric sensor, and so on. Of course, it cannot be separated from other intelligent sensor equipment. During identification, testers need to wear or be in the detection range of sensor equipment, which can judge the behavior by calculating the data characteristics of the joint. The research of behavior recognition based on sensors gradually emerged, which enabled humans to enter the era of intelligent wearable technology. Although these behavior recognition methods have achieved many excellent results in their respective fields, they are mostly applied in some scenes. For behavior recognition in people's daily life, there is an urgent need for a simple, convenient, and inexpensive detection method that does not need to be worn and is not affected by the environment.
This Special Issue, therefore, aims to put together original research and review articles on the latest research advances, technologies, and solutions for identifying data-driven human activities in an intelligent world.
Dr. Wen Qi
Dr. Stavros Ntalampiras
Guest Editors
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