Incorporating Spatial Queries into Semantic Sensor Streams on the Internet of Things

Abstract

In the Internet of Things (IoT) environment, the use of sensors and sensor readings is significant in research and industry. The number of sensors is increasing exponentially, adding a tremendous amount of data to the Web. Therefore, the efficient management of sensors and observation data is becoming important. Especially, the location and time of observations are expected to play a vital role in IoT. However, existing researches mainly focus on the temporal properties of data stream. It is necessary to consider the spatial features in addition to the temporal ones. In this article, the authors propose a spatiotemporal query language which integrates spatial and temporal features. Also, they propose an efficient method of building a spatiotemporal index and processing the proposed query language. To evaluate the proposed method, the authors conduct experiments through implementation. The experimental results show that the proposed method deals with spatiotemporal queries within a reasonable time.