IoTDQ: An Industrial IoT Data Analysis Library for Apache IoTDB

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Abstract

There is a growing demand for time series data analysis in industry areas. Apache IoTDB is a time series database designed for the Internet of Things (IoT) with enhanced storage and I/O performance. With User-Defined Functions (UDF) provided, computation for time series can be executed on Apache IoTDB directly. To satisfy most of the common requirements in industrial time series analysis, we create a UDF library, IoTDQ, on Apache IoTDB. This library integrates stream computation functions on data quality analysis, data profiling, anomaly detection, data repairing, etc. IoTDQ enables users to conduct a wide range of analyses, such as monitoring, error diagnosis, equipment reliability analysis. It provides a framework for users to examine IoT time series with data quality problems. Experiments show that IoTDQ keeps the same level of performance compared to mainstream alternatives, and shortens I/O consumption for Apache IoTDB users.

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Chen, P., He, W., Ma, W., Huang, X., & Wang, C. (2024). IoTDQ: An Industrial IoT Data Analysis Library for Apache IoTDB. Big Data Mining and Analytics, 7(1), 29–41. https://doi.org/10.26599/BDMA.2023.9020010

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