Abstract
Sensors play an increasingly critical role in capturing and distributing observations of phenomena in our environment. The vision of the semantic sensor web is to enable the interoperability of various applications that use sensor data provided by semantically heterogeneous sensor services. However, several challenges still need to be addressed to achieve this vision. More particularly, mechanisms that can support context-aware semantic mapping and that can adapt to the dynamic metadata of sensors are required. Semantic mapping for the sensor web is required to support sensor data fusion, sensor data discovery and retrieval, and automatic semantic annotation, to name only a few tasks. This paper presents a context-aware ontology-based semantic mediation service for heterogeneous sensor services. The semantic mediation service is context-aware and dynamic because it takes into account the real-time variability of thematic, spatial, and temporal elements that describe sensor data in different contexts. The semantic mediation service integrates rule-based reasoning to support the resolution of semantic heterogeneities. An application scenario is presented showing how the semantic mediation service can improve sensor data interpretation, reuse, and sharing in static and dynamic settings.
Highlights
The development of sensor networks is opening a wide range of opportunities in a variety of domains, ranging from environmental monitoring to health-care, urban traffic management, and satellite imaging
This paper has addressed the challenges related to semantic interoperability in the sensor web, and the issue of finding semantic mappings for sensor data
We focused on the need for providing comprehensive semantics describing the context of sensor observations and their context, and we have provided a metadata model
Summary
The development of sensor networks is opening a wide range of opportunities in a variety of domains, ranging from environmental monitoring to health-care, urban traffic management, and satellite imaging. Semantics of sensor observations cannot be dealt with in the exact same way as that of geospatial data, notably because sensor semantics are more likely to be dynamic, as the context within www.josis.org which data is produced is often evolving, especially in the case of mobile sensors [17, 31] Taking these aspects into consideration, in this paper we present a context-aware and dynamic semantic mediation system for the semantic sensor web. The conceptual basis of the proposed context-aware semantic mediation system is a sensor metadata model for sensor observations that has been proposed in previous research published in the W2GIS 2012 conference [4]. It is shown in this paper how this model is adaptable to dynamic changes with context rules.
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