=Paper=
{{Paper
|id=Vol-1383/paper13
|storemode=property
|title=WISE: An Applying of Semantic IoT Platform for Weather Information Service Engine
|pdfUrl=https://ceur-ws.org/Vol-1383/paper13.pdf
|volume=Vol-1383
|dblpUrl=https://dblp.org/rec/conf/semweb/LeeKK14
}}
==WISE: An Applying of Semantic IoT Platform for Weather Information Service Engine==
https://ceur-ws.org/Vol-1383/paper13.pdf
Semantic WISE: An Applying of Semantic IoT Platform for
Weather Information Service Engine
Junwook Leea, Youngwoo Kima, Soonhyun Kwonb,*
a
Platform Research Division, Handysoft Inc., Korea
b
Electronics and Telecommunications Research Institute, Daejeon, Korea
Abstract— In this paper, we present the application case of architecture and developed semantic technology is described.
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.
I. INTRODUCTION
With the development of new communication technology
and sensor technology, various attempts for supporting human Figure 1. Overview of Semantic IoT technology for WISE platform
life more conveniently are increasing. M2M technology is
focused on the remote sensing and transport information to
another machine via cellar network. Weather information II. WISE PLATFORM
service based on M2M technology is limited to a simple data WISE[4], which is a recently launched project of the Korea
acquisition and processing and is insufficient to provide a data Meteorological Administration (KMA) aimed at developing a
integration and interoperability. On the other hand, more next-generation Weather Information Service Engine (WISE).
recent research on IoT(Internet of Things) technology[1] is WISE represents an investment over eight years for efforts to
trying to allow things to judge and operate autonomously and resolve urban environmental issues, through scientific
collaboratively by working through the Internet between things. advances in high-resolution weather forecasting, urban flood
Recently, the attempts for applying semantic web prediction, road meteorology and urban carbon dynamics, and
technology to decision support M2M/IoT services are new urban service systems to minimize and mitigate the
increasing. E.g. the SemSorGrid4Env project of EC[2] and impacts of natural disasters and climate change on urban
Australian Climate Observations Reference Network - Surface dwellers. The main objectives of WISE platform are the
Air Temperature (ACORN-SAT) dataset[3]. Unlike improvements of technology & infrastructure for the implementation
conventional meteorological services, semantic weather of urban & rural meteorology information services, decision support
information service combined semantic web technology should for disaster relief, information production support for national agenda,
be able to solve the data interoperability of diverse weather and building up a mashup service platform for easy customized
services.
data and application domain data. However, due to the diverse
and heterogeneous nature of IoT data, it is difficult to analyze
user’s context and better customized weather related semantic
information. 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. As shown in Figure 1, 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. Figure 2. Architecture of WISE platform
In this paper, we present the application case of semantic
IoT platform technology to WISE project in Korea As shown in Figure 2, WISE Platform consists of three sub-
Meteorological Services. More in detail, the platform systems 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 B. Semantic Processing
are stored in cloud DB which provides scalability and high- The semantic processor performs the sensing data
performance. Big data from cloud DB can be translated into translation by using the translation rules and WISE ontology
new semantic knowledge by integrating with domain data and model. The semantic translator is a processor for converting
LODs. Semantic IoT platform provide semantic annotation non-semantic data(non RDF data) to semantic data(RDF data).
and semantic processing. The translated semantic data, which The translation rules define the method of mapping each
is RDF base data, is managed into semantic repository. Using elements of the RDF triple pattern into the target ontology
the semantic open API of semantic IoT platform, various user model or the value and type of the literal.
portal services are supported by the user service platform. The translated RDF data are stored into semantic repository.
To support scalability and performance of inference, semantic
III. WISE SEMANTIC IOT PLATFORM repository is implemented by using Hbase of Hadoop platform.
The semantic IoT platform consists of five main modules as Due to the nature of distributed and parallel processing of
Figure 3: semantic ontology, semantic processor, semantic Hbase, our repository shows more high performance than any
query engine, semantic repository and semantic open API. other existing RDF repositories.
C. Semantic Queries and Open API
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.
Figure 3. Overview of Semantic IoT Platform Architecture
A. WISE Platform Ontology
Several kinds of ontologies are defined to support the WISE
semantic service: platform ontologies, service domain
ontologies and service ontologies. Platform ontologies mean
Figure 5. Semantic Service Development Support
the commonly applied ontologies that are independent with
specific WISE service. Figure 4 show the relationships of
IV. IMPLEMENTATION AND CONCLUSION
WISE ontologies.
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
This work was supported by the project “Integrated Weather
Services for Urban and Rural Area” of CATER.
Figure 4. Relationship of WISE Ontologies
REFERENCES
[1] Luigi Atzori, Antonio Iera, Giacomo Morabito, “The Internet of Things:
Therefore, platform ontologies generate description and A survey,” Computer Networks, vol.54, pp.2787-2805, June, 2010.
[2] European Commission project SemSorGrid4Env (FP7-223913).
process information to derive the abstracted real world event http://www.semsorgrid4env.eu
from sensing. [3] BOM. Australian Climate Observations Reference Network - Surface
TABLE I PLATFORM ONTOLOGY INPUT/OUTPUT DATA Air Temperature (ACORN-SAT).
Type Description http://www.bom.gov.au/climate/change/acorn-sat/, 2012.
INPUT - RDF based sensing data [4] Choi, Youngjean, and et al, A Next-Generation Weather Information
- Resource sub-ontology instance value
OUTPUT - Abstracted realtime event Service Engine (WISE) Customized for Urban and Surrounding Rural
- Processed event ontology instance value Areas. Bull. Amer. Meteor. Soc., 94, ES114–ES117, 2013