A systematic review of smartphone-based human activity recognition methods for health research
Smartphones are now nearly ubiquitous; their numerous built-in sensors enable continuous
measurement of activities of daily living, making them especially well-suited for health …
measurement of activities of daily living, making them especially well-suited for health …
Context-awareness for mobile sensing: A survey and future directions
The evolution of smartphones together with increasing computational power has
empowered developers to create innovative context-aware applications for recognizing user …
empowered developers to create innovative context-aware applications for recognizing user …
Efficient data aggregation with node clustering and extreme learning machine for WSN
I Ullah, HY Youn - The Journal of Supercomputing, 2020 - Springer
Wireless sensor network is effective for data aggregation and transmission in IoT
environment. Here, the sensor data often contain a significant amount of noises or …
environment. Here, the sensor data often contain a significant amount of noises or …
A “one-size-fits-most” walking recognition method for smartphones, smartwatches, and wearable accelerometers
The ubiquity of personal digital devices offers unprecedented opportunities to study human
behavior. Current state-of-the-art methods quantify physical activity using “activity counts,” a …
behavior. Current state-of-the-art methods quantify physical activity using “activity counts,” a …
An adaptive bayesian system for context-aware data fusion in smart environments
The adoption of multi-sensor data fusion techniques is essential to effectively merge and
analyze heterogeneous data collected by multiple sensors, pervasively deployed in a smart …
analyze heterogeneous data collected by multiple sensors, pervasively deployed in a smart …
Ensemble of rnn classifiers for activity detection using a smartphone and supporting nodes
Nowadays, sensor-equipped mobile devices allow us to detect basic daily activities
accurately. However, the accuracy of the existing activity recognition methods decreases …
accurately. However, the accuracy of the existing activity recognition methods decreases …
A survey of context-aware middleware designs for human activity recognition
The ever increasing technological advances in embedded systems engineering, together
with the proliferation of small-size sensor designs and deployment, have enabled smart …
with the proliferation of small-size sensor designs and deployment, have enabled smart …
Power management techniques in smartphone-based mobility sensing systems: A survey
R Pérez-Torres, C Torres-Huitzil… - Pervasive and Mobile …, 2016 - Elsevier
The rapidly enhancing sensing capabilities of smartphones are enabling the development of
a wide range of innovative mobile sensing applications that are impacting on everyday life of …
a wide range of innovative mobile sensing applications that are impacting on everyday life of …
Enabling resource-efficient edge intelligence with compressive sensing-based deep learning
A Machidon, V Pejović - Proceedings of the 19th ACM international …, 2022 - dl.acm.org
Billions of sensor-enabled computing devices open tremendous opportunities for AI-
powered context-aware services. Yet, democratizing AI so that heterogeneous devices can …
powered context-aware services. Yet, democratizing AI so that heterogeneous devices can …
Transportation mode recognition based on low-rate acceleration and location signals with an attention-based multiple-instance learning network
C Siargkas, V Papapanagiotou… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Transportation mode recognition (TMR) is a critical component of human activity recognition
(HAR) that focuses on understanding and identifying how people move within transportation …
(HAR) that focuses on understanding and identifying how people move within transportation …