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%%This file is Copyright (C) 2018 Megha Gaur. This repository contains the implementation details/code for anomaly detection in building's energy consumption. The reader is suggested to read through the paper to know about the approaches in detail. For short-term data, Dataset: Dataport Dataset (2 months data from 10 houses) This meter-level data is grouped into weekdays and weekends. Pecan_weekday_house_mat and Pecan_weekend_house_mat are the matlab files containing weekday and weekend data across all houses. Code: Gen_labels.m is used to generate anomaly scores and labels depending on the user defined threshold. For long-term data, Dataset: HUE Dataset (3years data from 5 houses) Code: weatherNormalisedData.m is used to annotate the year long observations. To evaluate the performance metrics, Dataset: Peccan street data Code: MetricEval.m is used to compare all the performance metrics discussed in the paper. Another contribution of this paper is in publishing the annotated anomalies obtained from short-range and long-range datasets. The csv files named as Hue_House_anomalies and Dataport_House_anomalies are in the AnnotatedAnomalies folder of this repository. Please cite our paper if you use our data or annotated anomalies as a benchmark for your research. If you have any query feel free to contact email@example.com or firstname.lastname@example.org