A new arsenal of artificial intelligence and data science tools will unlock massive energy savings and help UK business in their goal of achieving net zero.


These cutting-edge algorithms will automatically and continuously sift through a deluge of data and find new insights and recommend ways to slash energy consumption.


Crucially, these new tools will be designed and developed to be transferred across a wide range of business sectors and organisations, and across different buildings and infrastructure. This will pave the way for the ‘digital replication’ of energy efficiency savings, and a viral spread of the knowledge and techniques across sectors.


This multi-disciplinary programme, called Net0Insights, which is led by researchers at Lancaster University working alongside major industry partners, draws on Lancaster University’s Data Science Institute, bringing together researchers from School of Computing and Communications, Mathematics and Statistics, and Lancaster Environment Centre.



1. Develop automated techniques for supporting analysis, identifying and recommending energy savings strategies, based on the application of statistical and machine learning techniques to fine-grained energy data;

2. Derive knowledge of how, where, and when energy is used, to identify opportunities to reduce and shift demand by comparing differences in energy use over time within and between premises;

3. Support regular and repeated analysis, towards a continual improvement in energy reduction over time.

4. Provide open source, permissively licensed implementations for enabling uptake, even beyond our project partners and their partner networks.

Our publication and publicity strategies will maximise exposure of our project results to various stakeholder groups including academia, practitioners, and key industry stakeholders.



Adrian Friday, Oliver Bates, Christian Remy, Adam Tyler, and Christina Bremer
School of Computing and Communications, Lancaster University

Idris Eckley, Paul Smith, Guillermo Cuauhtemoctzin Granados Garcia, Alex Gibberd, and Tak-Shing Chan
Mathematics and Statistics, Lancaster University

Ally Gormally-Sutton
Lancaster Environment Centre (LEC), Lancaster University


In collaboration with commercial partners Tesco, BTBEST, and Lancaster University Facilities




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