Abstract: With the rapid development of IoT technology, everything in the world is going to interconnect via IoT, which has become a popular technology that permits users to connect anywhere, anytime, anyplace, anyone and any device, involving many domains such as smart home, intelligent transportation and so on. However, most of IoT heterogeneous data are isolated, which holds back the progress of IoT interconnection. Schema matching techniques are widely used in the scenario of data interconnection to solve the problem above. Because of the characteristics of IoT heterogeneous data such as heterogeneity and increasing growth, the existing schema matching approaches can’t solve the problems caused by schema auto-matching under new IoT environment. In this paper, we attempt to solve this problem by introducing a new algorithm based on hierarchical method that could fulfill automatic schema matching for IoT heterogeneous data. Our algorithm has three parts: classifi-cation matching, clustering matching and mixed element matching. By each step, we keep narrowing down matching space and improving matching quality. We demonstrate the utility and efficiency of our algorithm with a set of comprehensive experiments on real datasets from the scenario of IoT industrial household appliances testing. The result shows that our algorithm has good performance.

Key words: Internet of things(IoT), data interconnection, schema matching, heterogeneous data, time series