Periodic pattern mining is a topic for mining periodic event patterns with sufficient confidence. The resulted patterns are often used to predict future events because they have established confidence that their periodicity will be maintained ...

Industrial information models are standardised ways of representing industrial devices, equipment, and processes together with the data collected from associated sensors and control systems. Companies invest in such models to enable ...

• Novel approach to SPARQL for querying contextualised time series data.
• Proof of correctness for approach.
• Open source implementation using state of the art technologies.
• Large performance increase over incumbent open source ...

We present a record-breaking result and lessons learned in practicing TPCx-IoT benchmarking for a real-world use case. We find that more system characteristics need to be benchmarked for its application to real-world use cases. We introduce an ...

The rapid growth in edge computing devices as part of Internet of Things (IoT) allows real-time access to time-series data from 1000’s of sensors. Such observations are often queried to optimize the health of the infrastructure. Recently, edge ...

Edge computing is unlocking the potential of Industrial Internet of Things (IIoT) to deliver business value and impact. Reliable data processing and guarantee of services within the IIoT sphere mandates the use of local storage within the device. The ...

Today, many applications produce and use time series data. The data of this type may contain sensitive information. So they should be protected against unauthorized accesses. In this paper, security issues of time series data are ...

• An access and inference control model for time series data to satisfy identified security requirements.

In this paper, we propose an efficient algorithm, called CFP, for mining closed flexible patterns in time-series databases, where flexible gaps are allowed in a pattern. Our proposed algorithm involves three stages: transforming a time-series database ...

In this paper, we propose an efficient algorithm, called CMP-Miner, to mine closed patterns in a time-series database where each record in the database, also called a transaction, contains multiple time-series sequences. Our proposed algorithm consists ...