Now showing items 1-6 of 6
Real-Time Sensor Observation Segmentation For Complex Activity Recognition Within Smart Environments
Activity Recognition (AR) is at the heart of any types of assistive living systems. One of the key challenges faced in AR is segmentation of the sensor events when inhabitant performs simple or composite activities of daily ...
Semantic modelling for learning styles and learning material in an e-learning environment
Various learners with various requirements have led to the raise of a crucial concern in the area of e-learning. A new technology for propagating learning to learners worldwide, has led to an evolution in the e-learning ...
Privacy Modelling and Management for Assisted Living within Smart Homes
Ambient Assisted Living (AAL) technologies create intelligent systems to assist the aging population for a healthier and safer life in their living environment. Such systems usually offer context-aware, personalized and ...
Wearable accelerometer based extended sleep position recognition
Sleep positions have an impact on sleep quality and therefore need to be further analyzed. Current research on position tracking includes only the four basic positions. In the context of wearable devices, energy efficiency ...
Semantic segmentation of real-time sensor data stream for complex activity recognition
Data segmentation plays a critical role in performing human activity recognition in the ambient assistant living systems. It is particularly important for complex activity recognition when the events occur in short bursts ...
Reality and Perception: Activity monitoring and data collection within a real-world smart home
Smart home technologies have been developing rapidly in the last few years. However, there is still a lack of annotated rich datasets that can be used for different analysis purposes by researchers. The motivation for ...