COOLL: Controlled On/Off Loads Library, a Public Dataset of High-Sampled Electrical Signals for Appliance Identification

TL;DR

This paper introduces COOLL, a high-sampled electrical signals dataset for appliance identification, featuring controlled on/off measurements of 42 appliances across 12 types, useful for advancing non-intrusive load monitoring research.

Contribution

The paper presents a publicly available, high-frequency dataset of controlled appliance electrical signals, enabling improved appliance identification methods.

Findings

Dataset includes 42 appliances across 12 types.

High sampling rate of 100 kHz captures detailed electrical signals.

Provides controlled on/off measurements for precise appliance analysis.

Abstract

This paper gives a brief description of the Controlled On/Off Loads Library (COOLL) dataset. This latter is a dataset of high-sampled electrical current and voltage measurements representing individual appliances consumption. The measurements were taken in June 2016 in the PRISME laboratory of the University of Orl\'eans, France. The appliances are mainly controllable appliances (i.e. we can precisely control their turn-on/off time instants). 42 appliances of 12 types were measured at a 100 kHz sampling frequency.