Human activity recognition with smartphone and wearable sensors using deep learning techniques: A review
E Ramanujam, T Perumal… - IEEE Sensors Journal, 2021 - ieeexplore.ieee.org
Human Activity Recognition (HAR) is a field that infers human activities from raw time-series
signals acquired through embedded sensors of smartphones and wearable devices. It has …
signals acquired through embedded sensors of smartphones and wearable devices. It has …
Machine learning and AI technologies for smart wearables
The recent progress in computational, communications, and artificial intelligence (AI)
technologies, and the widespread availability of smartphones together with the growing …
technologies, and the widespread availability of smartphones together with the growing …
Lara: Creating a dataset for human activity recognition in logistics using semantic attributes
Optimizations in logistics require recognition and analysis of human activities. The potential
of sensor-based human activity recognition (HAR) in logistics is not yet well explored …
of sensor-based human activity recognition (HAR) in logistics is not yet well explored …
Activity recognition using wearable physiological measurements: Selection of features from a comprehensive literature study
Activity and emotion recognition based on physiological signal processing in health care
applications is a relevant research field, with promising future and relevant applications …
applications is a relevant research field, with promising future and relevant applications …
Detection of health-related events and behaviours from wearable sensor lifestyle data using symbolic intelligence: a proof-of-concept application in the care of multiple …
In this paper, we demonstrate the potential of a knowledge-driven framework to improve the
efficiency and effectiveness of care through remote and intelligent assessment. More …
efficiency and effectiveness of care through remote and intelligent assessment. More …
Machine learning based attrition prediction
AN Ray, J Sanyal - 2019 Global Conference for Advancement …, 2019 - ieeexplore.ieee.org
The use of machine learning techniques and models has become widespread with diverse
industries using them to glean greater insights from available data. Probabilistic estimation …
industries using them to glean greater insights from available data. Probabilistic estimation …
[HTML][HTML] Ensem-DeepHAR: Identification of human activity in smart environments using ensemble of deep learning methods and motion sensor data
SMM Islam, KH Talukder - Measurement: Sensors, 2024 - Elsevier
Recognizing human activity plays a crucial role in many applications such as medical care
services in smart healthcare environments. Inertial or motion sensors can measure …
services in smart healthcare environments. Inertial or motion sensors can measure …
Graph powered machine learning in smart sensor networks
A generic representation of sensor network data can be done by inherent graph structure
within IoT sensor networks. We can develop a standardized graph-based framework and …
within IoT sensor networks. We can develop a standardized graph-based framework and …
Human Activity Recognition using Attribute-Based Neural Networks and Context Information
We consider human activity recognition (HAR) from wearable sensor data in manual-work
processes, like warehouse order-picking. Such structured domains can often be partitioned …
processes, like warehouse order-picking. Such structured domains can often be partitioned …
Applications of human activity recognition in industrial processes--Synergy of human and technology
Human-technology collaboration relies on verbal and non-verbal communication. Machines
must be able to detect and understand the movements of humans to facilitate non-verbal …
must be able to detect and understand the movements of humans to facilitate non-verbal …