Semantic-driven Configuration of Internet of Things Middleware

TL;DR

This paper introduces CASCoM, a semantics-driven model that simplifies IoT middleware configuration for non-IT experts by enabling automated, context-aware setup of sensors and data processing components, demonstrated through a scalable prototype.

Contribution

The paper presents a novel semantics-based model for automated IoT middleware configuration, making it accessible to non-IT users and adaptable across platforms.

Findings

CASCoM improves configuration speed for non-IT users.

The approach is scalable and applicable to various IoT middleware.

Prototype evaluation shows enhanced usability and manageable computational complexity.

Abstract

We are currently observing emerging solutions to enable the Internet of Things (IoT). Efficient and feature rich IoT middeware platforms are key enablers for IoT. However, due to complexity, most of these middleware platforms are designed to be used by IT experts. In this paper, we propose a semantics-driven model that allows non-IT experts (e.g. plant scientist, city planner) to configure IoT middleware components easier and faster. Such tools allow them to retrieve the data they want without knowing the underlying technical details of the sensors and the data processing components. We propose a Context Aware Sensor Configuration Model (CASCoM) to address the challenge of automated context-aware configuration of filtering, fusion, and reasoning mechanisms in IoT middleware according to the problems at hand. We incorporate semantic technologies in solving the above challenges. We demonstrate the feasibility and the scalability of our approach through a prototype implementation based on an IoT middleware called Global Sensor Networks (GSN), though our model can be generalized into any other middleware platform. We evaluate CASCoM in agriculture domain and measure both performance in terms of usability and computational complexity.