Internet of Things (IoT) based activity recognition strategies in smart homes: A review

L Babangida, T Perumal, N Mustapha… - IEEE Sensors …, 2022 - ieeexplore.ieee.org
A smart home, which is an extension of a traditional home, is equipped with ubiquitous
sensors embedded in consumer appliances, connected via sensing technologies such as …

Mobile edge computing enabled 5G health monitoring for Internet of medical things: A decentralized game theoretic approach

Z Ning, P Dong, X Wang, X Hu, L Guo… - IEEE Journal on …, 2020 - ieeexplore.ieee.org
The prompt evolution of Internet of Medical Things (IoMT) promotes pervasive in-home
health monitoring networks. However, excessive requirements of patients result in …

Deep learning for computer vision based activity recognition and fall detection of the elderly: a systematic review

FX Gaya-Morey, C Manresa-Yee, JM Buades-Rubio - Applied Intelligence, 2024 - Springer
As the proportion of elderly individuals in developed countries continues to rise globally,
addressing their healthcare needs, particularly in preserving their autonomy, is of paramount …

Artificial intelligence internet of things for the elderly: From assisted living to health-care monitoring

K Qian, Z Zhang, Y Yamamoto… - IEEE Signal Processing …, 2021 - ieeexplore.ieee.org
An aging population is increasingly prevalent in both developed and develo** countries,
raising a series of social challenges and economic burdens. In particular, more elderly …

Selective encryption on ECG data in body sensor network based on supervised machine learning

H Qiu, M Qiu, Z Lu - Information Fusion, 2020 - Elsevier
Abstract Body Sensor Networks (BSNs) are develo** rapidly in recent years as it
combines the Internet-of-Things (IoT) and data analytic techniques for building a remote …

Detection of sitting posture using hierarchical image composition and deep learning

A Kulikajevas, R Maskeliunas, R Damaševičius - PeerJ computer science, 2021 - peerj.com
Human posture detection allows the capture of the kinematic parameters of the human body,
which is important for many applications, such as assisted living, healthcare, physical …

SmartWall: Novel RFID-enabled ambient human activity recognition using machine learning for unobtrusive health monitoring

GA Oguntala, RA Abd-Alhameed, NT Ali, YF Hu… - IEEE …, 2019 - ieeexplore.ieee.org
Human activity recognition (HAR) from sensor readings has proved to be an effective
approach in pervasive computing for smart healthcare. Recent approaches in ambient …

Human activity recognition based on dynamic active learning

H Bi, M Perello-Nieto… - IEEE Journal of …, 2020 - ieeexplore.ieee.org
Activity of daily living is an important indicator of the health status and functional capabilities
of an individual. Activity recognition, which aims at understanding the behavioral patterns of …

CSI-based location-independent human activity recognition using feature fusion

Y Zhang, Q Liu, Y Wang, G Yu - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Channel state information (CSI)-based human activity recognition (HAR) has important
application prospects, such as smart homes, medical monitoring, and public security. Due to …

[HTML][HTML] Human activity classification using deep learning based on 3D motion feature

ES Rahayu, EM Yuniarno, IKE Purnama… - Machine Learning with …, 2023 - Elsevier
Human activity classification is needed to support various fields. The health sector, for
example, requires the ability to monitor the activities of patients, the elderly, or people with …