This project aims to build a software tool (Retail Energy Management System or REMS) which uses novel pattern matching tools on sub-metered energy data collected at 30 minute intervals from a portfolio of supermarket stores. The project team want to link the energy data to other external data (weather data and building data) so that normalisation models can be used to compare performance between stores. We will build AURAmonitor, a pattern matching tool which will detect and alert on anomalies over time and use shape-based pattern tools to detect known events (e.g. asset failure, human behaviours). The consortium will use data from ASDA's current energy monitoring system and use other data from their Building Management Software. The software will be developed by Cybula, an SME specialising in analysis of time series data using the expertise of the Leeds Sustainability Institute in building energy management. The Centre for Low Carbon Futures will use their links with UKTI and overseas embassies to construct a plan for exploitation of REMS.