Dominic T. J. O'Sullivan

TL;DR: The main contributions of this research are a set of data and system requirements for implementing equipment maintenance applications in industrial environments, and an information system model that provides a scalable and fault tolerant big data pipeline for integrating, processing and analysing industrial equipment data.

TL;DR: The formal research methodology of systematic mapping is used to provide a breadth-first review of big data technologies in manufacturing to provide an obvious lack of secondary research undertaken in the area.

TL;DR: This research presents an industrial cyber-physical system based on the emerging fog computing paradigm, which can embed production-ready PMML-encoded machine learning models in factory operations, and adhere to Industry 4.0 design concerns pertaining to decentralisation, security, privacy and reliability.

TL;DR: In this article, an industry foundation class based building product model of University College Cork's Environmental Research Institute was developed and combined with a building management system and other tools and technologies to create a framework for monitoring, analysing and controlling a building throughout its building lifecycle.

TL;DR: In this article, the authors presented a degree-days simulation technique coupled with a genetic algorithm optimization procedure to propose an optimal retrofit solution for a recently retrofitted case-study building, which demonstrated the necessity to carry out analysis of a project before retrofit works commence to ensure an optimal approach is taken in accordance with the project specific criteria.