Anomaly detection for IoT time-series data: A survey

AA Cook, G Mısırlı, Z Fan - IEEE Internet of Things Journal, 2019 - ieeexplore.ieee.org
Anomaly detection is a problem with applications for a wide variety of domains; it involves
the identification of novel or unexpected observations or sequences within the data being …

[HTML][HTML] Internet of things architectures, technologies, applications, challenges, and future directions for enhanced living environments and healthcare systems: a …

G Marques, R Pitarma, N M. Garcia, N Pombo - Electronics, 2019 - mdpi.com
Internet of Things (IoT) is an evolution of the Internet and has been gaining increased
attention from researchers in both academic and industrial environments. Successive …

Smart cities: concepts, architectures, research opportunities

R Khatoun, S Zeadally - Communications of the ACM, 2016 - dl.acm.org
Smart cities: concepts, architectures, research opportunities Page 1 46 COMMUNICATIONS
OF THE ACM | AUGUST 2016 | VOL. 59 | NO. 8 contributed articles DOI:10.1145/2858789 The …

Sensor data acquisition and multimodal sensor fusion for human activity recognition using deep learning

S Chung, J Lim, KJ Noh, G Kim, H Jeong - Sensors, 2019 - mdpi.com
In this paper, we perform a systematic study about the on-body sensor positioning and data
acquisition details for Human Activity Recognition (HAR) systems. We build a testbed that …

Wearable sensors based human behavioral pattern recognition using statistical features and reweighted genetic algorithm

MAK Quaid, A Jalal - Multimedia Tools and Applications, 2020 - Springer
Human behavior pattern recognition (BPR) from accelerometer signals is a challenging
problem due to variations in signal durations of different behaviors. Analysis of human …

Industrial wearable system: the human-centric empowering technology in Industry 4.0

XTR Kong, H Luo, GQ Huang, X Yang - Journal of Intelligent …, 2019 - Springer
The Industry 4.0 program and corresponding international initiatives continue to transform
the industrial workforce and their work. The service-oriented, customer-centric and demand …

Unsupervised deep learning for IoT time series

Y Liu, Y Zhou, K Yang, X Wang - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
Internet of Things (IoT) time-series analysis has found numerous applications in a wide
variety of areas, ranging from health informatics to network security. Nevertheless, the …

Wearable sensor-based human behavior understanding and recognition in daily life for smart environments

A Jalal, MAK Quaid, AS Hasan - 2018 International Conference …, 2018 - ieeexplore.ieee.org
Behavior recognition using motion sensors is getting prominence over other systems such
as e-healthcare and life-log analysis systems especially in the healthcare domain for …

A Triaxial acceleration-based human motion detection for ambient smart home system

A Jalal, MAK Quaid, MA Sidduqi - 2019 16th International …, 2019 - ieeexplore.ieee.org
Health industry off late has been driven heavily by sensors ie accelerometers,
magnetometers etc. which has allowed instant medical response to any injurious activity in …

Activity recognition and anomaly detection in smart homes

LG Fahad, SF Tahir - Neurocomputing, 2021 - Elsevier
Physical and cognitive impairments decline the ability of elderly in execution of daily
activities, such as eating, slee** or taking medication. The proposed approach recognizes …