- In this paper, we present the application case of semantic IoT platform technology to WISE project in Korea Meteorological Services. Current M2M platform technology applied to weather service is mainly focused on remote data collection. Therefore, it is difficult to analyze the domain context for decision support and provide the better customized semantic related weather information. In WISE project, big data such as high-resolution weather data and model data are collected. Moreover, it aims to support the interoperability and convergence of IoT data for urban and rural meteorology services.
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As shown in Figure 2, WISE Platform consists of three subsystems such as M2M platform, Semantic IoT platform and user service platform. Using M2M platform, diverse source of high-resolution weather data should be collected remotely and stably. Realtime M2M data and legacy weather information are stored in cloud DB which provides scalability and highperformance. Big data from cloud DB can be translated into new semantic knowledge by integrating with domain data and LODs. Semantic IoT platform provide semantic annotation and semantic processing. The translated semantic data, which is RDF base data, is managed into semantic repository. Using the semantic open API of semantic IoT platform, various user portal services are supported by the user service platform.
Several kinds of ontologies are defined to support the WISE semantic service: platform ontologies, service domain ontologies and service ontologies. Platform ontologies mean the commonly applied ontologies that are independent with specific WISE service. Figure 4 show the relationships of WISE ontologies.
Therefore, platform ontologies generate description and process information to derive the abstracted real world event from sensing.
TABLE I PLATFORM ONTOLOGY INPUT/OUTPUT DATA
Type Description INPUT - RDF based sensing data
- Resource sub-ontology instance value OUTPUT - Abstracted realtime event - Processed event ontology instance value
The semantic processor performs the sensing data translation by using the translation rules and WISE ontology model. The semantic translator is a processor for converting non-semantic data(non RDF data) to semantic data(RDF data). The translation rules define the method of mapping each elements of the RDF triple pattern into the target ontology model or the value and type of the literal.
The translated RDF data are stored into semantic repository. To support scalability and performance of inference, semantic repository is implemented by using Hbase of Hadoop platform. Due to the nature of distributed and parallel processing of Hbase, our repository shows more high performance than any other existing RDF repositories.
The platform provides semantic query interface of SPARQL. The WISE applications or user service platform can query to derive more abstracted knowledge from semantic repository. In order to use the semantic platform easily, semantic query browser /visualization tool are required as shown in Figure 5.
The implemented semantic IoT platform was applied to WISE project to generate semantic weather data and to provide better customized semantic related weather service. Based on the semantic platform, disaster management service was improved the functionalities of user context detection and prediction.
ACKNOWLEDGEMENTS