With the rapid advances in sensor data collection and communication, heterogeneous and real-time IOT data is increasing rapidly. To make full use of the information, lots of web technologies are introduced to integrate the IOT world and Web world into an unified Web of Things(WOT). While most of the existing efforts are mainly focused on the modeling, annotation, and representation of WOT data, there has been little work focusing on the background processing of large-scale streaming WOT data. In the paper, we present a general semantic processing framework and implement an elastic streaming engine for WOT applications. The proposed engine efficiently capture and model different scenarios for all kinds of WOT applications based on popular large-scale distributed computing platform SPARK. Based on the engine, a typical use case on home environment monitoring is given to illustrate the efficiency of our engine. The results show that our system can scale for large number of sensor streams with different types of WOT applications.
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