Two-Dimensional Rule Language for Querying Sensor Log Data: A Framework and Use Cases

Proc. of the 26th Int. Symp. on Temporal Representation and Reasoning (TIME 2019). Volume 147 of Leibniz International Proceedings in Informatics (LIPIcs). 2019.

Motivated by two industrial use cases that involve detecting events of interest in (asynchronous) time series from sensors in manufacturing rigs and gas turbines, we design an expressive rule language DslD equipped with interval aggregate functions (such as weighted average over a time interval), Allen's interval relations and various metric constructs. We demonstrate how to model events in the uses cases in terms of DslD programs. We show that answering DslD queries in our use cases can be reduced to evaluating SQL queries. Our experiments with the use cases, carried out on the Apache Spark system, show that such SQL queries scale well on large real-world datasets.

@inproceedings{TIME-2019,
   title = "Two-Dimensional Rule Language for Querying Sensor Log Data:  A
Framework and Use Cases",
   year = "2019",
   author = "Sebastian Brandt and Diego Calvanese and Güzel Kalayci,
Elem and Roman Kontchakov and Benjamin Mörzinger and Vladislav
Ryzhikov and Guohui Xiao and Michael Zakharyaschev",
   booktitle = "Proc. of the 26th Int. Symp. on Temporal Representation and
Reasoning (TIME 2019)",
   pages = "7:1--7:15",
   volume = "147",
   publisher = "Schloss Dagstuhl--Leibniz-Zentrum für Informatik",
   series = "Leibniz International Proceedings in Informatics (LIPIcs)",
   doi = "10.4230/LIPIcs.TIME.2019.7",
}