Home Comfort Dataset: Acquired from SGH

Author:

Santos Mariana1ORCID,Antunes Mário12ORCID,Gomes Diogo12ORCID,Aguiar Rui L.12ORCID

Affiliation:

1. Departamento de Electrónica, Telecomunicações e Informática, Universidade de Aveiro, 3810-193 Aveiro, Portugal

2. Instituto de Telecomunicações, Departamento de Electrónica, Telecomunicações e Informática, Universidade de Aveiro, 3810-193 Aveiro, Portugal

Abstract

In this work, we share the dataset collected during the Smart Green Homes (SGH) project. The project’s goal was to develop integrated products and technology solutions for households, as well as to improve the standards of comfort and user satisfaction. This was to be achieved while improving household energy efficiency and reducing the usage of gaseous pollutants, in response to the planet’s sustainability issues. One of the tasks executed within the project was the collection of data from volunteers’ homes, including environmental information and the level of comfort as perceived by the volunteers themselves. While used in the original project, the resulting dataset contains valuable information that could not be explored at the time. We now share this dataset with the community, which can be used for various scenarios. These may include heating appliance optimisation, presence detection and environmental prediction.

Publisher

MDPI AG

Subject

Information Systems and Management,Computer Science Applications,Information Systems

Reference19 articles.

1. APA (2022, September 21). State of the Environment Portal (Portugal). Available online: https://rea.apambiente.pt/?language=en.

2. A global review of energy consumption, CO2 emissions and policy in the residential sector (with an overview of the top ten CO2 emitting countries);Nejat;Renew. Sustain. Energy Rev.,2015

3. Heating behaviour in English homes: An assessment of indirect calculation methods;Kane;Energy Build.,2017

4. Universidade de Aveiro (2022, September 21). Smart Green Homes. Available online: https://www.ua.pt/pt/smartgreenhomes/.

5. Misalignment problem in matrix decomposition with missing values;Fernandes;Mach. Learn.,2021

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