Now showing items 1-6 of 6
Extending knowledge-driven activity models through data-driven learning techniques
(Pergamon Press, Inc. Tarrytown, NY, USA, 2015-04-15)
We combine knowledge- and data-driven approaches for activity modeling.We develop a novel clustering algorithm that uses prior domain expert knowledge.A new learning algorithm to model activities from extracted clusters.We ...
Combining ontological and temporal formalisms for composite activity modelling and recognition in smart homes
Activity recognition is essential in providing activity assistance for users in smart homes. While significant progress has been made for single-user single-activity recognition, it still remains a challenge to carry out ...
From Activity Recognition to Intention Recognition for Assisted Living Within Smart Homes
(IEEE Transactions on Human-Machine Systems, 2017-01-05)
The global population is aging; projections show that by 2050, more than 20% of the population will be aged over 64. This will lead to an increase in aging related illness, a decrease in informal support, and ultimately ...
Audio-based Event Recognition System for Smart Homes
Building an acoustic-based event recognition system for smart homes is a challenging task due to the lack of high-level structures in environmental sounds. In particular, the selection of effective features is still an ...
Guest Editorial Special Issue on Situation, Activity, and Goal Awareness in Cyber-Physical Human–Machine Systems
The papers in this special section focus on cyber-physical man-machine systems with particular emphasis on situation, activity, and goal awareness deployed in these systems. Recent advances in sensing technologies, the ...
Energy-based decision engine for household human activity recognition
We propose a framework for energy-based human activity recognition in a household environment. We apply machine learning techniques to infer the state of household appliances from their energy consumption data and use ...