Secure connection of multiple retrofitted smart building monitoring systems across a group of buildings
This project is part of the Queen’s Doctoral Training Programme in Secure Connected Intelligent Design and Manufacturing. Many of today’s industrial approaches require transformative changes to ensure long term societal, economic and environmental resilience and sustainability. PhD projects in this programme explore the potential of emerging digital technologies, such as artificial intelligence, robotics, and the Internet of Things, to transform the way we design, manufacture and operate products and services. It is an interdisciplinary PhD, co supervised by Prof Roger Woods, EEECS https://pure.qub.ac.uk/en/persons/roger-woods.
Smart technology is fast becoming the norm in new build construction, with widespread use of digital twins and integration of temperature, room occupancy, energy and light sensors enabling building energy management systems to track, predict and manage energy use. However, there exists a large stock of existing buildings which are, by comparison, largely ‘dumb’; very little information is gathered on their efficiency, occupancy, and energy use, and their management often uses legacy, analogue systems. Fitting sensors to monitor existing buildings presents a number of challenges: the integration of the technology with the existing building envelope; older mechanical and electrical systems which may use a mixture of heat and energy generation and distribution networks; and the security and reliability of information gathered. This project responds to the UK construction 2025 strategy through the development and use of innovative techniques to record the existing built environment including connecting room and building wide information.
Aims and Objectives: The project aims to generate a resilient network of secure, smart building models as an online digital building information system, with real time sensor data combined with user feedback / participation. This will aid energy use tracking, gathering real time data for analysis and prediction of energy use.
To develop a network of non-invasive building sensors which can be retrofitted without unduly disturbing an existing building’s fabric.
To develop a number of digital twins for existing buildings based on a laser scan / point cloud model.
To securely connect these digital twins to each other, to the building sensors, and to an interface for building user feedback. The information needs to be accessible and secure – the right person is able to access the right level of secure, reliable data from the system.
The successful candidate will be funded through an EPSRC 3.5 year doctoral training partnership, including stipend and Home/EU fees. Candidates must have been ordinarily resident in the UK for 3 years (with no restrictions). EU residents may be eligible for a fees-only studentship. Further details: https://epsrc.ukri.org/skills/students/guidance-on-epsrc-studentships/
• Apply for Degree of Doctor of Philosophy in the School of Natural and Built Environment (subject: Architecture)
• State name of the lead supervisor as ‘Tara Brooks’ on application
• State ‘EPSRC funded 3.5 years DTP’ as Intended Source of Funding
• To apply, select the ’Visit Website’ link below
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FTE Category A staff submitted: 30.60
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