SRE: Semantic Rules Engine For the Industrial Internet-Of-Things Gateways

TL;DR

This paper introduces a Semantic Rules Engine (SRE) for industrial IoT gateways that enables dynamic, flexible, and semantic rule-based control strategies, supporting on-the-fly updates without service interruption.

Contribution

It presents a novel SRE that manages rules dynamically, supports semantic queries, and infers knowledge, validated across hardware platforms and commercial products.

Findings

SRE allows real-time rule updates without service disruption.

It effectively handles semantic queries and knowledge inference.

Performance evaluations confirm conformance to customer requirements.

Abstract

The Advent of the Internet-of-Things (IoT) paradigm has brought opportunities to solve many real-world problems. Energy management, for example, has attracted huge interest from academia, industries, governments and regulatory bodies. It involves collecting energy usage data, analyzing it, and optimizing the energy consumption by applying control strategies. However, in industrial environments, performing such optimization is not trivial. The changes in business rules, process control, and customer requirements make it much more challenging. In this paper, a Semantic Rules Engine (SRE) for industrial gateways is presented that allows implementing dynamic and flexible rule-based control strategies. It is simple, expressive, and allows managing rules on-the-fly without causing any service interruption. Additionally, it can handle semantic queries and provide results by inferring additional knowledge from previously defined concepts in ontologies. SRE has been validated and tested on different hardware platforms and in commercial products. Performance evaluations are also presented to validate its conformance to the customer requirements.