Mobile and wearable devices have enabled numerous applications, including activity
tracking, wellness monitoring, and human–computer interaction, that measure and improve …

Federated learning (FL) is a kind of distributed machine learning framework, where the
global model is generated on the centralized aggregation server based on the parameters of …

Human activity recognition (HAR) plays a pivotal role in various domains, including
healthcare, sports, robotics, and security. With the growing popularity of wearable devices …

Test-time adaptation (TTA) is an emerging paradigm that addresses distributional shifts
between training and testing phases without additional data acquisition or labeling cost; only …

Smartphones are now nearly ubiquitous; their numerous built-in sensors enable continuous
measurement of activities of daily living, making them especially well-suited for health …

In the last decade, Human Activity Recognition (HAR) has become a vibrant research area,
especially due to the spread of electronic devices such as smartphones, smartwatches and …

Advancements in smartphone sensor technologies have significantly enriched the field of
human activity recognition, facilitating a wide array of applications from health monitoring to …

Ubiquitous computing has been a green research area that has managed to attract and
sustain the attention of researchers for some time now. As ubiquitous computing …

Recent advancements in ultra-low-power machine learning (TinyML) hardware promises to
unlock an entirely new class of smart applications. However, continued progress is limited …

Smart living, a concept that has gained increasing attention in recent years, revolves around
integrating advanced technologies in homes and cities to enhance the quality of life for …