Green edge AI: A contemporary survey
Artificial intelligence (AI) technologies have emerged as pivotal enablers across a multitude
of industries, including consumer electronics, healthcare, and manufacturing, largely due to …
of industries, including consumer electronics, healthcare, and manufacturing, largely due to …
Deep learning models for real-time human activity recognition with smartphones
With the widespread application of mobile edge computing (MEC), MEC is serving as a
bridge to narrow the gaps between medical staff and patients. Relatedly, MEC is also …
bridge to narrow the gaps between medical staff and patients. Relatedly, MEC is also …
[HTML][HTML] GTSNet: Flexible architecture under budget constraint for real-time human activity recognition from wearable sensor
Human activity recognition is an essential task for human-centered intelligent systems such
as healthcare and smart vehicles, which can be accomplished by analyzing time-series …
as healthcare and smart vehicles, which can be accomplished by analyzing time-series …
Meta-learning meets the Internet of Things: Graph prototypical models for sensor-based human activity recognition
With the rapid growth of the Internet of Things (IoT), smart systems and applications are
equipped with an increasing number of wearable sensors and mobile devices. These …
equipped with an increasing number of wearable sensors and mobile devices. These …
Step by step towards effective human activity recognition: A balance between energy consumption and latency in health and wellbeing applications
Human activity recognition (HAR) is a classification process that is used for recognizing
human motions. A comprehensive review of currently considered approaches in each stage …
human motions. A comprehensive review of currently considered approaches in each stage …
Dana: Dimension-adaptive neural architecture for multivariate sensor data
Motion sensors embedded in wearable and mobile devices allow for dynamic selection of
sensor streams and sampling rates, enabling several applications, such as power …
sensor streams and sampling rates, enabling several applications, such as power …
Green Edge AI: A Contemporary Survey
Artificial intelligence (AI) technologies have emerged as pivotal enablers across a multitude
of industries, including consumer electronics, healthcare, and manufacturing, largely due to …
of industries, including consumer electronics, healthcare, and manufacturing, largely due to …
Instance-wise dynamic sensor selection for human activity recognition
Abstract Human Activity Recognition (HAR) is an important application of smart
wearable/mobile systems for many human-centric problems such as healthcare. The multi …
wearable/mobile systems for many human-centric problems such as healthcare. The multi …
Energy-accuracy tradeoff for efficient noise monitoring and prediction in working environments
We explore the tradeoff between energy consumption and measurement accuracy for noise
monitoring and prediction based on continuously collected data by wireless, energy …
monitoring and prediction based on continuously collected data by wireless, energy …
Multitemporal sampling module for real-time human activity recognition
Human activity recognition, which recognizes human activities from time-series signals
collected by sensors, is an important task in human-centered intelligent systems such as in …
collected by sensors, is an important task in human-centered intelligent systems such as in …