A new study finds that mobile phone data could enable urban buildings to become more energy-efficient.
Energy use in buildings accounts for more than 40% of total primary energy use in Europe and the United States, with most of them located in urban areas that are growing rapidly.
According to Dr Edward Barbour, of the School of Mechanical, Electrical and Manufacturing Engineering, his latest study shows mobile phones can provide valuable data on the occupancy of buildings and this can be used to better plan for collective energy use.
Dr Barbour has helped develop a model that shows mobile phone data could be used to improve urban scale building occupancy and mobility estimates.
In contrast to surveys, mobile phones can be used to ‘passively’ track users – meaning the phone user does not need to actively report their movements.
The research, which has been published in a paper in Nature Communications, builds on work by Carlos Cerezo Davila and Siddharth Gupta, of the Massachusetts Institute of Technology (MIT), and was conducted in collaboration with academics from Berkeley Engineering, where Dr Barbour worked before joining Loughborough.
Like traffic apps tell us the current state of road congestion, the research team envision the future for creating sustainable buildings involves a model that can tell users what the energy demands are in different places and then identify bespoke efficiency measures.
They say this tool could potentially connect to smart devices that automatically adjust to the energy demand.
The team’s paper is a ‘proof-of-concept’ and the study involved analysing the call records of nearly two million anonymous mobile phone users in Boston, US, to explore their idea.
They found the data from mobile phones to be more accurate than current methods for estimating occupancy, with energy consumption differing as much as 15% for residential buildings and 20% for commercial buildings.
Dr Barbour hopes to build on the research at Loughborough University and use the methodology to better understand other climate-related issues, such as the potential for heat demand reduction.
He said: “Heat demand in buildings is one of the biggest sources of carbon emissions. I would like to exploit the methodology – in particular, to examine how smart heating strategies can be used to reduce heat demands in unused (unpopulated) spaces.
“I’m also considering using the mobile phone data to try and infer EV (Electric Vehicles) trip distance distributions, which would allow us to get a good estimates of the grid impacts of widespread EV adoption, and whether the electricity required to charge a mass adoption of EVs can be generated by large amounts of wind.”