Human action recognition and posture prediction aim to recognize and predict respectively
the action and postures of persons in videos. They are both active research topics in …

Automated techniques for evaluating sports activities inside dynamic frames are highly
dependent on advanced sports analysis by smart machines. The monitoring of individuals …

In this paper, we propose a lightweight neural network for real-time electrocardiogram (ECG)
anomaly detection and system level power reduction of wearable Internet of Things (IoT) …

Human activity recognition is an emerging and important area in computer vision which
seeks to determine the activity an individual or group of individuals are performing. The …

Human activity recognition (HAR) is a process of identifying the daily living activities of an
individual using a set of sensors and appropriate learning algorithms. Most of the works on …

Recent advancements in the Internet of Medical Things (IoMT) have revolutionized the
healthcare sector, making it an active research area in the academic and industrial sectors …

In recent years, slow feature analysis (SFA) has been successfully employed to deal with the
air handling unit (AHU) system's time-varying dynamic properties. However, since the …

In this paper, we propose a novel approach to video action recognition that integrates a
modified and optimized 3D Convolutional Neural Network, a Long Short-Term Memory …

The integration of artificial intelligence (AI) into human activity recognition (HAR) in smart
surveillance systems has the potential to revolutionize behavior monitoring. These systems …

Smartphones and wearable devices have built-in sensors that can collect multivariant time-
series data that can be used to recognize human activities. Research on human activity …