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.
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