Enhanced sensor web services by incorporating IoT interface protocols and spatio-temporal data streams for edge computing-based sensing
The Geospatial Sensor Web (GSW) integrates heterogeneous aerial and ground sensors via cloud-edge linkages and GIS-based approaches, forming a multi-dimensional observation network. However, existing systems struggle to support edge-side collaborative observation due to fragmented physical standards...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-01-01
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| Series: | Geo-spatial Information Science |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/10095020.2025.2450510 |
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| _version_ | 1832591151276752896 |
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| author | Dong Chen Shaoju Wang Chao Wang Xiang Zhang Nengcheng Chen |
| author_facet | Dong Chen Shaoju Wang Chao Wang Xiang Zhang Nengcheng Chen |
| author_sort | Dong Chen |
| collection | DOAJ |
| description | The Geospatial Sensor Web (GSW) integrates heterogeneous aerial and ground sensors via cloud-edge linkages and GIS-based approaches, forming a multi-dimensional observation network. However, existing systems struggle to support edge-side collaborative observation due to fragmented physical standards, incompatible protocols, and limited self-configuration. This study proposes an enhanced Sensor Web, integrating IoT protocols and spatio-temporal models for unified access, collaborative management, and dynamic planning. Validated through the City Sensing Base Station (CSBS), a pilot experiment demonstrated the framework integrates diverse sensing resources across over eight protocols, achieving autonomous alignment of more than five platforms with rapid aerial-ground network formation during emergencies. It also validated autonomous collaboration and coordination of aerial-ground resources, enabling dynamic task allocation and execution across heterogeneous systems. Compared with cloud-based architectures, this approach significantly improves resource accessibility and real-time processing. By extending SensorML and Sensor Observation Service (SOS), the framework bridges the gap between conventional Sensor Webs and edge computing demands. Results confirm its effectiveness in coordinating heterogeneous resources and managing dynamic spatio-temporal data. These findings show how Internet of Things (IoT) protocols advance earth observation, modeling and improve GSW efficiency. |
| format | Article |
| id | doaj-art-1fadcf63ca0144149c8e9afd46d960e5 |
| institution | Kabale University |
| issn | 1009-5020 1993-5153 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Geo-spatial Information Science |
| spelling | doaj-art-1fadcf63ca0144149c8e9afd46d960e52025-01-22T16:22:22ZengTaylor & Francis GroupGeo-spatial Information Science1009-50201993-51532025-01-0111810.1080/10095020.2025.2450510Enhanced sensor web services by incorporating IoT interface protocols and spatio-temporal data streams for edge computing-based sensingDong Chen0Shaoju Wang1Chao Wang2Xiang Zhang3Nengcheng Chen4School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, ChinaSchool of Remote Sensing and Information Engineering, Wuhan University, Wuhan, ChinaState Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, ChinaNational Engineering Research Center of Geographic Information System, School of Geography and Information Engineering, China University of Geosciences, Wuhan, ChinaNational Engineering Research Center of Geographic Information System, School of Geography and Information Engineering, China University of Geosciences, Wuhan, ChinaThe Geospatial Sensor Web (GSW) integrates heterogeneous aerial and ground sensors via cloud-edge linkages and GIS-based approaches, forming a multi-dimensional observation network. However, existing systems struggle to support edge-side collaborative observation due to fragmented physical standards, incompatible protocols, and limited self-configuration. This study proposes an enhanced Sensor Web, integrating IoT protocols and spatio-temporal models for unified access, collaborative management, and dynamic planning. Validated through the City Sensing Base Station (CSBS), a pilot experiment demonstrated the framework integrates diverse sensing resources across over eight protocols, achieving autonomous alignment of more than five platforms with rapid aerial-ground network formation during emergencies. It also validated autonomous collaboration and coordination of aerial-ground resources, enabling dynamic task allocation and execution across heterogeneous systems. Compared with cloud-based architectures, this approach significantly improves resource accessibility and real-time processing. By extending SensorML and Sensor Observation Service (SOS), the framework bridges the gap between conventional Sensor Webs and edge computing demands. Results confirm its effectiveness in coordinating heterogeneous resources and managing dynamic spatio-temporal data. These findings show how Internet of Things (IoT) protocols advance earth observation, modeling and improve GSW efficiency.https://www.tandfonline.com/doi/10.1080/10095020.2025.2450510Sensor webweb geographic information system (WebGIS)earth observationdata modelingsystem integration |
| spellingShingle | Dong Chen Shaoju Wang Chao Wang Xiang Zhang Nengcheng Chen Enhanced sensor web services by incorporating IoT interface protocols and spatio-temporal data streams for edge computing-based sensing Geo-spatial Information Science Sensor web web geographic information system (WebGIS) earth observation data modeling system integration |
| title | Enhanced sensor web services by incorporating IoT interface protocols and spatio-temporal data streams for edge computing-based sensing |
| title_full | Enhanced sensor web services by incorporating IoT interface protocols and spatio-temporal data streams for edge computing-based sensing |
| title_fullStr | Enhanced sensor web services by incorporating IoT interface protocols and spatio-temporal data streams for edge computing-based sensing |
| title_full_unstemmed | Enhanced sensor web services by incorporating IoT interface protocols and spatio-temporal data streams for edge computing-based sensing |
| title_short | Enhanced sensor web services by incorporating IoT interface protocols and spatio-temporal data streams for edge computing-based sensing |
| title_sort | enhanced sensor web services by incorporating iot interface protocols and spatio temporal data streams for edge computing based sensing |
| topic | Sensor web web geographic information system (WebGIS) earth observation data modeling system integration |
| url | https://www.tandfonline.com/doi/10.1080/10095020.2025.2450510 |
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