@inbook{b382b98df076442b856e59d96550854e,
title = "Generation of a Partitioned Dataset with Single, Interleave and Multioccupancy Daily Living Activities",
abstract = "The advances in electronic devices have entailed the development of smart environments which have the aim to help and make easy the life of their inhabitants. In this kind of environments, an important task is the process of activity recognition of an inhabitant in the environment in order to anticipate the occupant necessities and to adapt such smart environment. Due to the cost to checking activity recognition approaches in real environments, usually, they use datasets generated from smart environments. Although there are many datasets for activity recognition in smart environments, it is difficult to find single, interleaved or multioccupancy activity datasets, or combinations of these classes of activities according to the researchers{\textquoteright} needs. In this work, the design and development of a complete dataset with 14 sensors and 9 different activities daily living is described, being this dataset divided into partitions with different classes of activities.",
author = "Quesada, {Francisco J.} and Francisco Moya and Javier Medina and Luis Mart{\'i}nez and Chris Nugent and Macarena Espinilla",
year = "2015",
doi = "10.1007/978-3-319-26401-1_6",
language = "English",
isbn = "978-3-319-26400-4",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "60--71",
editor = "Garc{\'i}a-Chamizo, {M. Juan} and Giancarlo Fortino and Ochoa, {F. Sergio}",
booktitle = "Ubiquitous Computing and Ambient Intelligence. Sensing, Processing, and Using Environmental Information",
address = "United Kingdom",
}