A Knowledge-Based Resource Discovery for Internet of Things

TL;DR

This paper introduces CASCOM, a knowledge-driven model that simplifies IoT resource configuration for non-technical users by using semantic descriptions for automated resource composition, demonstrated via a prototype on GSN middleware.

Contribution

It presents a novel semantic-based approach for automating IoT resource configuration, making it accessible to non-technical users, and demonstrates its feasibility through a prototype implementation.

Findings

Semantic descriptions enable automated resource composition.

The approach improves usability for non-technical users.

Prototype validates the effectiveness of CASCOM.

Abstract

In the sensing as a service paradigm, Internet of Things (IoT) Middleware platforms allow data consumers to retrieve the data they want without knowing the underlying technical details of IoT resources (i.e. sensors and data processing components). However, configuring an IoT middleware platform and retrieving data is a significant challenge for data consumers as it requires both technical knowledge and domain expertise. In this paper, we propose a knowledge driven approach called Context Aware Sensor Configuration Model (CASCOM) to simplify the process of configuring IoT middleware platforms, so the data consumers, specifically non-technical personnel, can easily retrieve the data they required. In this paper, we demonstrate how IoT resources can be described using semantics in such away that they can later be used to compose service work-flows. Such automated semantic-knowledge based IoT resource composition approach advances the current research. We demonstrate the feasibility and the usability of our approach through a prototype implementation based on an IoT middleware called Global Sensor Networks (GSN), though our model can be generalized to any other middleware platform.