Semantic-driven Configuration of Internet of Things Middleware
This addresses the challenge for non-IT experts like plant scientists or city planners to use IoT middleware more efficiently, though it appears incremental as it builds on existing middleware platforms.
The paper tackles the problem of configuring IoT middleware, which is complex and typically requires IT experts, by proposing a semantics-driven model called CASCoM that enables non-IT experts to configure components easier and faster, with evaluation in agriculture showing performance in usability and computational complexity.
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.