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Optimising the processing of smart-house data across edge and central devices

   School of Computing and Engineering

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  Prof Phil Lane, Prof Richard Hill  No more applications being accepted  Competition Funded PhD Project (Students Worldwide)

Huddersfield United Kingdom Data Analysis Electrical Engineering Computer Science Software Engineering

About the Project

The Huddersfield Smart House Research Facility is a well-instrumented, 2-storey dwelling that is intended to showcase how technology can make a positive contribution to living spaces encompassing health, the environment, enjoyment and entertainment, and security. A challenge that arises whenever a large number of sensors are integrated is how to best process the high volumes of data that are generated. The processing requirements can be onerous as in order to extract most value from the data sophisticated machine learning and artificial intelligence algorithms will have to be used. One approach would be to use the domestic communications infrastructure to convey all sensor data to a central compute server where the required algorithms run. This approach has drawbacks though in that the conveyance of the data could place a disruptive load on the communications infrastructure to the detriment of other applications such as entertainment.  The use of edge processing where data is processed at, or near to, the sensor can enable the transformation of the raw sensor data into knowledge that is then communicated to a central server where decisions are taken that impact the whole house.

Edge devices usually have very limited processing power as they will be based on technology similar to e.g., Arduino microcontrollers as the cost of edge devices has to be low. There is also the possibility of using low-cost edge devices based on FPGAs that could provide quick but inflexible processing. The challenge addressed by this project is how to best partition tasks across an estate of processing devices of varying capabilities (i.e. what the nodes can do) and capacities (i.e. how much of what they do they can do). There are very interesting trade-offs here that involve network traffic – moving data around the house to centralised processing capability and moving capability around in terms of software/firmware updates delivered to edge devices, performance – how quickly a particular task is done, and cost – the complexity of the solution required to deliver the required behaviour. 

The project will involve the development of detailed simulations of alternative approaches and the building and characterisation of test-beds located in the smart house. Both of these will contribute to a deeper understanding of optimal approaches to the provision of the required computational capacity and capability to enable smart living in future residential properties. The test-beds will comprise of a number of sensors and associated edge processing devices distributed throughout the smart house, and will be installed very early on in the project so that the practical data gathering and the simulation work will both support each other. The sensors and edge devices are already available within CindA.

The Huddersfield Smart House Research Facility is being developed as a collaborative hub for industry, academia and government organisations. It is being developed to accelerate research and development for smart products and services to be used in the building environment with an aim to bring transformational improvements in key performance indicators corresponding to 21st century houses and living conditions. For this purpose, a well instrumented two storey dwelling is being constructed that will provide facilities for a range of novel and innovative investigations to be carried out.

Smart technologies can help us in reducing carbon footprints as well as having positive energy balance through improved energy performance of homes and buildings. We can achieve greater energy efficiency, cut carbon emissions and support more intelligent and flexible management of energy supply and demand. By incorporating use of smart technologies, the health and wellbeing can be significantly improved through better management of internal environments, safety and security. Smart technologies have potential to offer significant improvements in wellbeing of the occupants by allowing control through voice and mobile apps as well as using automation and artificial intelligence to support and predict our changing needs.

HSHRF aims to bring researchers, practitioners, industries and government organisations together to design, develop and implement holistic solutions to current and future societal challenges associated with building environment and its use.


Applications must be made through the University of Huddersfield Online Application portal:

Funding Notes

The Huddersfield Smart House Research Facility is looking to award four Smart House Scholarships to exceptional applicants. Each Smart House Scholarship will provide a full fee waiver to the successful candidate. The Scholarships do not include a bursary or stipend. The Interviews will take place on Thursday 1st and Friday 2nd July 2021.
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