This paper proposes an ontology-enabled system for context management for smart environments. Central to the system is ontological sensor modelling, which attaches metadata and meaning to sensor data, thus supporting data repurposing and high-level content recognition. In addition, semantic sensor descriptions allow sensors to be automatically identified whenever they are put into an environment. Based on this, a novel plug-n-measure data acquisition mechanism has been developed to automatically detect and recognise new devices and update the contextual data relating to these devices on a real-time basis. The context management system has been developed based on the latest semantic technologies and deployed in an intelligent meeting room. T...
Abstract: Context-aware ubiquitous computing environments tend to be highly distributed and heteroge...
Smart home environments have a significant potential to provide for long-term monitoring of users wi...
Part 1: Machine Learning (ML), Deep Learning (DL), Internet of Things (IoT)International audienceSma...
Contextual information within smart environments varies greatly. Whilst upper-level ontologies for c...
This paper introduces a framework for integrating ontology- and logic-based approaches for context-a...
This paper reports results from the ongoing research relating to the development on the context onto...
Context modeling has attracted increasing attention due to the prevalence of context-aware applicati...
Abstract—Sensor plays an important role in context-aware computing. While sensor modeling is usually...
This paper introduces a framework for enabling context-aware behaviors in smart environment applicat...
Context aware applications utilize environmental information which is usually collected by different...
Any of our living environments can form a smart space that provides services and applications for th...
A framework is introduced that is aimed at integrating ontology- and logic-based approaches for cont...
Smart home environments have a significant potential to provide for long-term monitoring of users wi...
It has been proposed that Semantic Web technologies would be key enablers in achieving context-aware...
The integration of cheap and powerful sensors in smartphones has enabled the emergence of several co...
Abstract: Context-aware ubiquitous computing environments tend to be highly distributed and heteroge...
Smart home environments have a significant potential to provide for long-term monitoring of users wi...
Part 1: Machine Learning (ML), Deep Learning (DL), Internet of Things (IoT)International audienceSma...
Contextual information within smart environments varies greatly. Whilst upper-level ontologies for c...
This paper introduces a framework for integrating ontology- and logic-based approaches for context-a...
This paper reports results from the ongoing research relating to the development on the context onto...
Context modeling has attracted increasing attention due to the prevalence of context-aware applicati...
Abstract—Sensor plays an important role in context-aware computing. While sensor modeling is usually...
This paper introduces a framework for enabling context-aware behaviors in smart environment applicat...
Context aware applications utilize environmental information which is usually collected by different...
Any of our living environments can form a smart space that provides services and applications for th...
A framework is introduced that is aimed at integrating ontology- and logic-based approaches for cont...
Smart home environments have a significant potential to provide for long-term monitoring of users wi...
It has been proposed that Semantic Web technologies would be key enablers in achieving context-aware...
The integration of cheap and powerful sensors in smartphones has enabled the emergence of several co...
Abstract: Context-aware ubiquitous computing environments tend to be highly distributed and heteroge...
Smart home environments have a significant potential to provide for long-term monitoring of users wi...
Part 1: Machine Learning (ML), Deep Learning (DL), Internet of Things (IoT)International audienceSma...