Transforming large-size to lightweight deep neural networks for IoT applications

R Mishra, H Gupta - ACM Computing Surveys, 2023‏ - dl.acm.org
Deep Neural Networks (DNNs) have gained unprecedented popularity due to their high-
order performance and automated feature extraction capability. This has encouraged …

[HTML][HTML] Large language models for wearable sensor-based human activity recognition, health monitoring, and behavioral modeling: a survey of early trends, datasets …

E Ferrara - Sensors, 2024‏ - mdpi.com
The proliferation of wearable technology enables the generation of vast amounts of sensor
data, offering significant opportunities for advancements in health monitoring, activity …

Tasked: transformer-based adversarial learning for human activity recognition using wearable sensors via self-knowledge distillation

S Suh, VF Rey, P Lukowicz - Knowledge-Based Systems, 2023‏ - Elsevier
Wearable sensor-based human activity recognition (HAR) has emerged as a principal
research area and is utilized in a variety of applications. Recently, deep learning-based …

Practically adopting human activity recognition

H Xu, P Zhou, R Tan, M Li - Proceedings of the 29th Annual International …, 2023‏ - dl.acm.org
Existing inertial measurement unit (IMU) based human activity recognition (HAR)
approaches still face a major challenge when adopted across users in practice. The severe …

X-char: A concept-based explainable complex human activity recognition model

JV Jeyakumar, A Sarker, LA Garcia… - Proceedings of the ACM …, 2023‏ - dl.acm.org
End-to-end deep learning models are increasingly applied to safety-critical human activity
recognition (HAR) applications, eg, healthcare monitoring and smart home control, to reduce …

AIoT-Based Smart Healthcare in Everyday Lives: Data Collection and Standardization from Smartphones and Smartwatches

G Ji, J Woo, G Lee, C Msigwa… - IEEE Internet of Things …, 2024‏ - ieeexplore.ieee.org
Artificial Intelligence of Things (AIoT)-based smart healthcare system that utilize smart
devices can provide personalized, proactive care to patients, reducing the reliance on …

Difformer: Multi-resolutional differencing transformer with dynamic ranging for time series analysis

B Li, W Cui, L Zhang, C Zhu, W Wang… - … on Pattern Analysis …, 2023‏ - ieeexplore.ieee.org
Time series analysis is essential to many far-reaching applications of data science and
statistics including economic and financial forecasting, surveillance, and automated …

Artificial intelligence of things: A survey

SI Siam, H Ahn, L Liu, S Alam, H Shen, Z Cao… - ACM Transactions on …, 2025‏ - dl.acm.org
The integration of the Internet of Things (IoT) and modern Artificial Intelligence (AI) has given
rise to a new paradigm known as the Artificial Intelligence of Things (AIoT). In this survey, we …

Deep triplet networks with attention for sensor-based human activity recognition

B Khaertdinov, E Ghaleb… - 2021 IEEE International …, 2021‏ - ieeexplore.ieee.org
One of the most significant challenges in Human Activity Recognition using wearable
devices is inter-class similarities and subject heterogeneity. These problems lead to the …

Smartphone-based human activities recognition system using random forest algorithm

V Radhika, CR Prasad… - … for Advancement in …, 2022‏ - ieeexplore.ieee.org
The advancements of smartphone technology, bring together doctors and patients for
monitoring clinical activities, remote assistants, and preemptive measures, specifically for …