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Chih Yuan Huang
Center for Space and Remote Sensing Research, National Central University, Taoyuan, Taiwan

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Journal article
Published: 18 June 2021 in Computers & Geosciences
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In recent years, the concept of the Internet of Things (IoT) has been attracting attention from various fields as IoT devices can continuously monitor various environmental properties. While the number of IoT devices increases rapidly, managing large volume of IoT data faces a serious scalability issue. To address this issue, many studies have shown that the performance of key-value storages is better than traditional relational databases. However, IoT data have multi-dimensional attributes including spatial, temporal and thematic attributes. How to construct an efficient multi-attribute combined index is an important topic. In this research, we consider four main types of attributes and their corresponding queries, which are spatial, temporal, keyword, and value attributes. While each attribute has its own suitable index method, integrating the indexes into a combined index usually requires a certain sequence of indexes, which significantly decides the query performance. As many literatures directly present their designed combined index, this research proposes an adaptive method to decide the most efficient combined index by estimating the selectivity and query performance of individual query criterion. The main idea is that highly-selective queries should be performed first to reduce the number of intermediate results, which can improve the query performance of following queries. Hence, this research proposes an index framework considering every possible sequence and automatically identifying the most efficient combined index for each query. According to the result, the proposed system has 94–99% chance to save 25 to 51 times response time compared to using a single combined index, and is twice faster than PostGIS on average when querying a one-million-record real-world dataset.

ACS Style

Chih Yuan Huang; Yu Jui Chang. An adaptively multi-attribute index framework for big IoT data. Computers & Geosciences 2021, 155, 104841 .

AMA Style

Chih Yuan Huang, Yu Jui Chang. An adaptively multi-attribute index framework for big IoT data. Computers & Geosciences. 2021; 155 ():104841.

Chicago/Turabian Style

Chih Yuan Huang; Yu Jui Chang. 2021. "An adaptively multi-attribute index framework for big IoT data." Computers & Geosciences 155, no. : 104841.

Conference paper
Published: 22 October 2020 in Transactions on Petri Nets and Other Models of Concurrency XV
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Smart cities effectively integrate human, physical, and digital systems operating in the built environment to provide automatic and efficient applications. While 3D city models, Internet of Things (IoT), and domain models are essential components of smart cities, the integration of IoT resources and 3D city models is a central information backbone for smart city cyber-infrastructures. However, we argue that most of the existing solutions integrating 3D city models and IoT resources are usually customized according to applications and lack of interoperability. To improve the interoperability between smart city modules, this study proposes a semantic-based methodology to integrate OGC CityGML and SensorThings API standards. Based on the data models from these two standards, this study proposes an integration ontology to connect information from these two standards. Due to the flexible definition of Thing in the IoT, the proposed ontology also considers multiple views of Thing. As a result, information from the CityGML and SensorThings API can be connected and queried via SPARQL queries. In general, this proposed integration ontology can facilitate the integration of IoT and 3D city models to achieve interoperable smart city.

ACS Style

Yao-Hsin Chiang; Chih-Yuan Huang; Masaaki Fuse. The Integration of OGC SensorThings API and OGC CityGML via Semantic Web Technology. Transactions on Petri Nets and Other Models of Concurrency XV 2020, 55 -67.

AMA Style

Yao-Hsin Chiang, Chih-Yuan Huang, Masaaki Fuse. The Integration of OGC SensorThings API and OGC CityGML via Semantic Web Technology. Transactions on Petri Nets and Other Models of Concurrency XV. 2020; ():55-67.

Chicago/Turabian Style

Yao-Hsin Chiang; Chih-Yuan Huang; Masaaki Fuse. 2020. "The Integration of OGC SensorThings API and OGC CityGML via Semantic Web Technology." Transactions on Petri Nets and Other Models of Concurrency XV , no. : 55-67.

Journal article
Published: 04 February 2020 in Remote Sensing
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Thermal infrared (TIR) satellite images are generally employed to retrieve land surface temperature (LST) data in remote sensing. LST data have been widely used in evapotranspiration (ET) estimation based on satellite observations over broad regions, as well as the surface dryness associated with vegetation index. Landsat-8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) can provide LST data with a 30-m spatial resolution. However, rapid changes in environmental factors, such as temperature, humidity, wind speed, and soil moisture, will affect the dynamics of ET. Therefore, ET estimation needs a high temporal resolution as well as a high spatial resolution for daily, diurnal, or even hourly analysis. A challenge with satellite observations is that higher-spatial-resolution sensors have a lower temporal resolution, and vice versa. Previous studies solved this limitation by developing a spatial and temporal adaptive reflectance fusion model (STARFM) for visible images. In this study, with the primary mechanism (thermal emission) of TIRS, surface emissivity is used in the proposed spatial and temporal adaptive emissivity fusion model (STAEFM) as a modification of the original STARFM for fusing TIR images instead of reflectance. For high a temporal resolution, the advanced Himawari imager (AHI) onboard the Himawari-8 satellite is explored. Thus, Landsat-like TIR images with a 10-minute temporal resolution can be synthesized by fusing TIR images of Himawari-8 AHI and Landsat-8 TIRS. The performance of the STAEFM to retrieve LST was compared with the STARFM and enhanced STARFM (ESTARFM) based on the similarity to the observed Landsat image and differences with air temperature. The peak signal-to-noise ratio (PSNR) value of the STAEFM image is more than 42 dB, while the values for STARFM and ESTARFM images are around 31 and 38 dB, respectively. The differences of LST and air temperature data collected from five meteorological stations are 1.53 °C to 4.93 °C, which are smaller compared with STARFM’s and ESATRFM’s. The examination of the case study showed reasonable results of hourly LST, dryness index, and ET retrieval, indicating significant potential for the proposed STAEFM to provide very-high-spatiotemporal-resolution (30 m every 10 min) TIR images for surface dryness and ET monitoring.

ACS Style

Tri Wandi Januar; Tang-Huang Lin; Chih-Yuan Huang; Kuo-En Chang. Modifying an Image Fusion Approach for High Spatiotemporal LST Retrieval in Surface Dryness and Evapotranspiration Estimations. Remote Sensing 2020, 12, 498 .

AMA Style

Tri Wandi Januar, Tang-Huang Lin, Chih-Yuan Huang, Kuo-En Chang. Modifying an Image Fusion Approach for High Spatiotemporal LST Retrieval in Surface Dryness and Evapotranspiration Estimations. Remote Sensing. 2020; 12 (3):498.

Chicago/Turabian Style

Tri Wandi Januar; Tang-Huang Lin; Chih-Yuan Huang; Kuo-En Chang. 2020. "Modifying an Image Fusion Approach for High Spatiotemporal LST Retrieval in Surface Dryness and Evapotranspiration Estimations." Remote Sensing 12, no. 3: 498.

Journal article
Published: 20 September 2019 in Sensors
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Time-domain reflectometry (TDR) is considered as a passive monitoring technique which reveals multi-functions, such as water level, bridge scour, landslide, and suspended sediment concentration (SSC), based on a single TDR device via multiplexing and related algorithms. The current platform for revealing TDR analysis and interpreted observations, however, is complex to access, thus a coherent data model and format for TDR heterogeneous data exchange is useful and necessary. To enhance the interoperability of TDR information, this research aims at standardizing the TDR data based on the Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) standards. To be specific, this study proposes a TDR sensor description model and an observation model based on the Sensor Model Language (SensorML) and Observation and Measurement (O&M) standards. In addition, a middleware was developed to translate existing TDR information to a Sensor Observation Service (SOS) web service. Overall, by standardizing TDR data with the OGC SWE open standards, relevant information for disaster management can be effectively and efficiently integrated in an interoperable manner.

ACS Style

Chih-Chung Chung; Chih-Yuan Huang; Chih-Ray Guan; Ji-Hao Jian; Guan; Jian. Applying OGC Sensor Web Enablement Standards to Develop a TDR Multi-Functional Measurement Model. Sensors 2019, 19, 4070 .

AMA Style

Chih-Chung Chung, Chih-Yuan Huang, Chih-Ray Guan, Ji-Hao Jian, Guan, Jian. Applying OGC Sensor Web Enablement Standards to Develop a TDR Multi-Functional Measurement Model. Sensors. 2019; 19 (19):4070.

Chicago/Turabian Style

Chih-Chung Chung; Chih-Yuan Huang; Chih-Ray Guan; Ji-Hao Jian; Guan; Jian. 2019. "Applying OGC Sensor Web Enablement Standards to Develop a TDR Multi-Functional Measurement Model." Sensors 19, no. 19: 4070.

Journal article
Published: 25 January 2019 in Sensors
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Sensor Web and Internet of Things (IoT) (SW-IoT) have been attracting attention from various fields. Both of them deploy networks of embedded devices to monitor physical properties (i.e., sensing capability) or to be controlled (i.e., tasking capability). One of the most important tasks to realize the SW-IoT vision is to establish an open and interoperable architecture, across the device layer, gateway layer, service layer, and application layer. To achieve this objective, many organizations and alliances propose standards for different layers. Among the standards, Open Geospatial Consortium (OGC) SensorThings API is arguably one of the most complete and flexible service standards. However, the SensorThings API only address heterogeneity issues in the service layer. Embedded devices following proprietary protocols need to join closed ecosystems and then link to the SensorThings API ecosystem via customized connectors. To address this issue, one could first follow another device layer and gateway layer open standards and then perform data model mapping with the SensorThings API. However, the data model mapping is not always straightforward as the standards were designed independently. Therefore, this research tries to propose a more direct solution to unify the entire SW-IoT architecture by extending the SensorThings API ecosystem to the gateway layer and the device layer. To be specific, this research proposes SW-IoT Plug and Play (IoT-PNP) to achieve an automatic registration procedure for embedded devices. The IoT-PNP contains three main components: (1) A description file describing device metadata and capabilities, (2) a communication protocol between the gateway layer and the device layer for establishing connections, and (3) an automatic registration procedure for both sensing and tasking capabilities. Overall, we believe the proposed solution could help achieve an open and interoperable SW-IoT end-to-end architecture based on the OGC SensorThings API.

ACS Style

Chih-Yuan Huang; Hsin-Hsien Chen. An Automatic Embedded Device Registration Procedure Based on the OGC SensorThings API. Sensors 2019, 19, 495 .

AMA Style

Chih-Yuan Huang, Hsin-Hsien Chen. An Automatic Embedded Device Registration Procedure Based on the OGC SensorThings API. Sensors. 2019; 19 (3):495.

Chicago/Turabian Style

Chih-Yuan Huang; Hsin-Hsien Chen. 2019. "An Automatic Embedded Device Registration Procedure Based on the OGC SensorThings API." Sensors 19, no. 3: 495.

Journal article
Published: 20 February 2017 in ISPRS International Journal of Geo-Information
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The Worldwide Sensor Web has been applied for monitoring the physical world with spatial and temporal scales that were impossible in the past. With the development of sensor technologies and interoperable open standards, sensor webs generate tremendous volumes of priceless data, enabling scientists to observe previously unobservable phenomena. With its powerful monitoring capability, the sensor web is able to capture time-critical events and provide up-to-date information to support decision-making. In order to harvest the full potential of the sensor web, efficiently processing sensor web data and providing timely notifications are necessary. Therefore, we aim to design a software component applying the publish/subscribe communication model for the sensor web. However, as sensor web data are geospatial in nature, existing topological operators are inefficient when processing a large number of geometries. This paper presents the Aggregated Hierarchical Spatial Model (AHS model) to efficiently determine topological relationships between sensor data and predefined query objects. By using a predefined hierarchical spatial framework to index geometries, the AHS model can match new sensor data with all subscriptions in a single process to improve the query performance. Based on our evaluation results, the query latency of the AHS model increases 2.5 times more slowly than that of PostGIS. As a result, we believe that the AHS model is able to more efficiently process topological operators in a sensor web publish/subscribe system.

ACS Style

Chih-Yuan Huang; Steve H. L. Liang. AHS Model: Efficient Topological Operators for a Sensor Web Publish/Subscribe System. ISPRS International Journal of Geo-Information 2017, 6, 54 .

AMA Style

Chih-Yuan Huang, Steve H. L. Liang. AHS Model: Efficient Topological Operators for a Sensor Web Publish/Subscribe System. ISPRS International Journal of Geo-Information. 2017; 6 (2):54.

Chicago/Turabian Style

Chih-Yuan Huang; Steve H. L. Liang. 2017. "AHS Model: Efficient Topological Operators for a Sensor Web Publish/Subscribe System." ISPRS International Journal of Geo-Information 6, no. 2: 54.

Journal article
Published: 31 August 2016 in Sensors
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The Internet of Things (IoT) is an infrastructure that interconnects uniquely-identifiable devices using the Internet. By interconnecting everyday appliances, various monitoring, and physical mashup applications can be constructed to improve human’s daily life. In general, IoT devices provide two main capabilities: sensing and tasking capabilities. While the sensing capability is similar to the World-Wide Sensor Web, this research focuses on the tasking capability. However, currently, IoT devices created by different manufacturers follow different proprietary protocols and are locked in many closed ecosystems. This heterogeneity issue impedes the interconnection between IoT devices and damages the potential of the IoT. To address this issue, this research aims at proposing an interoperable solution called tasking capability description that allows users to control different IoT devices using a uniform web service interface. This paper demonstrates the contribution of the proposed solution by interconnecting different IoT devices for different applications. In addition, the proposed solution is integrated with the OGC SensorThings API standard, which is a Web service standard defined for the IoT sensing capability. Consequently, the Extended SensorThings API can realize both IoT sensing and tasking capabilities in an integrated and interoperable manner.

ACS Style

Chih-Yuan Huang; Cheng-Hung Wu. A Web Service Protocol Realizing Interoperable Internet of Things Tasking Capability. Sensors 2016, 16, 1395 .

AMA Style

Chih-Yuan Huang, Cheng-Hung Wu. A Web Service Protocol Realizing Interoperable Internet of Things Tasking Capability. Sensors. 2016; 16 (9):1395.

Chicago/Turabian Style

Chih-Yuan Huang; Cheng-Hung Wu. 2016. "A Web Service Protocol Realizing Interoperable Internet of Things Tasking Capability." Sensors 16, no. 9: 1395.

Journal article
Published: 05 August 2016 in ISPRS International Journal of Geo-Information
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With the advance of the World-Wide Web (WWW) technology, people can easily share content on the Web, including geospatial data and web services. Thus, the “big geospatial data management” issues start attracting attention. Among the big geospatial data issues, this research focuses on discovering distributed geospatial resources. As resources are scattered on the WWW, users cannot find resources of their interests efficiently. While the WWW has Web search engines addressing web resource discovery issues, we envision that the geospatial Web (i.e., GeoWeb) also requires GeoWeb search engines. To realize a GeoWeb search engine, one of the first steps is to proactively discover GeoWeb resources on the WWW. Hence, in this study, we propose the GeoWeb Crawler, an extensible Web crawling framework that can find various types of GeoWeb resources, such as Open Geospatial Consortium (OGC) web services, Keyhole Markup Language (KML) and Environmental Systems Research Institute, Inc (ESRI) Shapefiles. In addition, we apply the distributed computing concept to promote the performance of the GeoWeb Crawler. The result shows that for 10 targeted resources types, the GeoWeb Crawler discovered 7351 geospatial services and 194,003 datasets. As a result, the proposed GeoWeb Crawler framework is proven to be extensible and scalable to provide a comprehensive index of GeoWeb.

ACS Style

Chih-Yuan Huang; Hao Chang. GeoWeb Crawler: An Extensible and Scalable Web Crawling Framework for Discovering Geospatial Web Resources. ISPRS International Journal of Geo-Information 2016, 5, 136 .

AMA Style

Chih-Yuan Huang, Hao Chang. GeoWeb Crawler: An Extensible and Scalable Web Crawling Framework for Discovering Geospatial Web Resources. ISPRS International Journal of Geo-Information. 2016; 5 (8):136.

Chicago/Turabian Style

Chih-Yuan Huang; Hao Chang. 2016. "GeoWeb Crawler: An Extensible and Scalable Web Crawling Framework for Discovering Geospatial Web Resources." ISPRS International Journal of Geo-Information 5, no. 8: 136.

Journal article
Published: 13 June 2016 in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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The Internet of Things (IoT) is an infrastructure that interconnects uniquely-identifiable devices using the Internet. By interconnecting everyday appliances, various monitoring and physical mashup applications can be constructed to improve people’s daily life. However, IoT devices created by different manufacturers follow different proprietary protocols and cannot communicate with each other. This heterogeneity issue causes different products to be locked in multiple closed ecosystems that we call IoT silos. In order to address this issue, a common industrial solution is the hub approach, which implements connectors to communicate with IoT devices following different protocols. However, with the growing number of proprietary protocols proposed by device manufacturers, IoT hubs need to support and maintain a lot of customized connectors. Hence, we believe the ultimate solution to address the heterogeneity issue is to follow open and interoperable standard. Among the existing IoT standards, the Open Geospatial Consortium (OGC) SensorThings API standard supports comprehensive conceptual model and query functionalities. The first version of SensorThings API mainly focuses on connecting to IoT devices and sharing sensor observations online, which is the sensing capability. Besides the sensing capability, IoT devices could also be controlled via the Internet, which is the tasking capability. While the tasking capability was not included in the first version of the SensorThings API standard, this research aims on defining the tasking capability profile and integrates with the SensorThings API standard, which we call the extended-SensorThings API in this paper. In general, this research proposes a lightweight JSON-based web service description, the “Tasking Capability Description”, allowing device owners and manufacturers to describe different IoT device protocols. Through the extended- SensorThings API, users and applications can follow a coherent protocol to control IoT devices that use different communication protocols, which could consequently achieve the interoperable Internet of Things infrastructure.

ACS Style

C. Y. Huang; C. H. Wu. DESIGN AND IMPLEMENT AN INTEROPERABLE INTERNET OF THINGS APPLICATION BASED ON AN EXTENDED OGC SENSORTHINGS API STANDARD. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences 2016, XLI-B4, 263 -266.

AMA Style

C. Y. Huang, C. H. Wu. DESIGN AND IMPLEMENT AN INTEROPERABLE INTERNET OF THINGS APPLICATION BASED ON AN EXTENDED OGC SENSORTHINGS API STANDARD. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 2016; XLI-B4 ():263-266.

Chicago/Turabian Style

C. Y. Huang; C. H. Wu. 2016. "DESIGN AND IMPLEMENT AN INTEROPERABLE INTERNET OF THINGS APPLICATION BASED ON AN EXTENDED OGC SENSORTHINGS API STANDARD." The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B4, no. : 263-266.

Journal article
Published: 22 September 2015 in Sensors
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Recently, researchers are focusing on a new use of the Internet called the Internet of Things (IoT), in which enabled electronic devices can be remotely accessed over the Internet. As the realization of IoT concept is still in its early stages, manufacturers of Internet-connected devices and IoT web service providers are defining their proprietary protocols based on their targeted applications. Consequently, IoT becomes heterogeneous in terms of hardware capabilities and communication protocols. Addressing these heterogeneities by following open standards is a necessary step to communicate with various IoT devices. In this research, we assess the feasibility of applying existing open standards on resource-constrained IoT devices. The standard protocols developed in this research are OGC PUCK over Bluetooth, TinySOS, SOS over CoAP, and OGC SensorThings API. We believe that by hosting open standard protocols on IoT devices, not only do the devices become self-describable, self-contained, and interoperable, but innovative applications can also be easily developed with standardized interfaces. In addition, we use memory consumption, request message size, response message size, and response latency to benchmark the efficiency of the implemented protocols. In all, this research presents and evaluates standard-based solutions to better understand the feasibility of applying existing standards to the IoT vision.

ACS Style

Mohammad Ali Jazayeri; Steve H. L. Liang; Chih-Yuan Huang. Implementation and Evaluation of Four Interoperable Open Standards for the Internet of Things. Sensors 2015, 15, 24343 -24373.

AMA Style

Mohammad Ali Jazayeri, Steve H. L. Liang, Chih-Yuan Huang. Implementation and Evaluation of Four Interoperable Open Standards for the Internet of Things. Sensors. 2015; 15 (9):24343-24373.

Chicago/Turabian Style

Mohammad Ali Jazayeri; Steve H. L. Liang; Chih-Yuan Huang. 2015. "Implementation and Evaluation of Four Interoperable Open Standards for the Internet of Things." Sensors 15, no. 9: 24343-24373.

Journal article
Published: 02 October 2013 in Sensors
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The world-wide sensor web has become a very useful technique for monitoring the physical world at spatial and temporal scales that were previously impossible. Yet we believe that the full potential of sensor web has thus far not been revealed. In order to harvest the world-wide sensor web’s full potential, a geospatial cyberinfrastructure is needed to store, process, and deliver large amount of sensor data collected worldwide. In this paper, we first define the issue of the sensor web long tail followed by our view of the world-wide sensor web architecture. Then, we introduce the Geospatial Cyberinfrastructure for Environmental Sensing (GeoCENS) architecture and explain each of its components. Finally, with demonstration of three real-world powered-by-GeoCENS sensor web applications, we believe that the GeoCENS architecture can successfully address the sensor web long tail issue and consequently realize the world-wide sensor web vision.

ACS Style

Steve H.L. Liang; Chih-Yuan Huang. GeoCENS: A Geospatial Cyberinfrastructure for the World-Wide Sensor Web. Sensors 2013, 13, 13402 -13424.

AMA Style

Steve H.L. Liang, Chih-Yuan Huang. GeoCENS: A Geospatial Cyberinfrastructure for the World-Wide Sensor Web. Sensors. 2013; 13 (10):13402-13424.

Chicago/Turabian Style

Steve H.L. Liang; Chih-Yuan Huang. 2013. "GeoCENS: A Geospatial Cyberinfrastructure for the World-Wide Sensor Web." Sensors 13, no. 10: 13402-13424.

Journal article
Published: 30 January 2013 in ISPRS International Journal of Geo-Information
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The Sensor Web is a growing phenomenon where an increasing number of sensors are collecting data in the physical world, to be made available over the Internet. To help realize the Sensor Web, the Open Geospatial Consortium (OGC) has developed open standards to standardize the communication protocols for sharing sensor data. Spatial Data Infrastructures (SDIs) are systems that have been developed to access, process, and visualize geospatial data from heterogeneous sources, and SDIs can be designed specifically for the Sensor Web. However, there are problems with interoperability associated with a lack of standardized naming, even with data collected using the same open standard. The objective of this research is to automatically group similar sensor data layers. We propose a methodology to automatically group similar sensor data layers based on the phenomenon they measure. Our methodology is based on a unique bottom-up approach that uses text processing, approximate string matching, and semantic string matching of data layers. We use WordNet as a lexical database to compute word pair similarities and derive a set-based dissimilarity function using those scores. Two approaches are taken to group data layers: mapping is defined between all the data layers, and clustering is performed to group similar data layers. We evaluate the results of our methodology.

ACS Style

Ben Knoechel; Chih-Yuan Huang; Steve H.L. Liang. A Bottom-Up Approach for Automatically Grouping Sensor Data Layers by their Observed Property. ISPRS International Journal of Geo-Information 2013, 2, 1 -26.

AMA Style

Ben Knoechel, Chih-Yuan Huang, Steve H.L. Liang. A Bottom-Up Approach for Automatically Grouping Sensor Data Layers by their Observed Property. ISPRS International Journal of Geo-Information. 2013; 2 (1):1-26.

Chicago/Turabian Style

Ben Knoechel; Chih-Yuan Huang; Steve H.L. Liang. 2013. "A Bottom-Up Approach for Automatically Grouping Sensor Data Layers by their Observed Property." ISPRS International Journal of Geo-Information 2, no. 1: 1-26.

Conference paper
Published: 01 January 2013 in Computer Vision
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The World-Wide Sensor Web is generating tremendous amount of real-time sensor data streams, and will enable scientists to observe phenomena that are previously unobservable. As the concept of sensor web is to connect all the sensors and their data to achieve shared goals, improving the openness and accessibility of sensor data is important. Open Geospatial Consortium Sensor Observation Service (SOS) defines standard web service protocols for sharing sensor data online in an interoperable manner. However, the SOS has a relatively weak ecosystem, which makes it difficult to build and consume; and it only supports predefined queries. On the other hand, the OASIS Open Data Protocol (OData) has a strong ecosystem and flexible query functions. But the soft-typing approach of OData requires it to have a commonly agreed data model to be interoperable. As we find that the two standards can benefit from each other, we propose a sensor data mediator solution and define an SOS entity data model for OData (SOS-OData) to bridge these two standards. Our prototype demonstrates that the proposed system can convert between existing SOS services and SOS-OData services. As a result, we can not only consume SOS data with the flexible OData protocol, but can also easily build an SOS-compliant service with the strong OData ecosystem. We argue that the bridge between these two standards would lead us to the vision of open data for sensor web.

ACS Style

Chih-Yuan Huang; Steve H. L. Liang; Yan Xu. A Sensor Data Mediator Bridging the OGC Sensor Observation Service (SOS) and the OASIS Open Data Protocol (OData). Computer Vision 2013, 7820, 129 -146.

AMA Style

Chih-Yuan Huang, Steve H. L. Liang, Yan Xu. A Sensor Data Mediator Bridging the OGC Sensor Observation Service (SOS) and the OASIS Open Data Protocol (OData). Computer Vision. 2013; 7820 ():129-146.

Chicago/Turabian Style

Chih-Yuan Huang; Steve H. L. Liang; Yan Xu. 2013. "A Sensor Data Mediator Bridging the OGC Sensor Observation Service (SOS) and the OASIS Open Data Protocol (OData)." Computer Vision 7820, no. : 129-146.