Exploiting the use of machine learning in two different sensor network architectures for indoor localization

@article{Carvalho2016ExploitingTU,
  title={Exploiting the use of machine learning in two different sensor network architectures for indoor localization},
  author={Eduardo Rodrigues de Carvalho and Bruno S. Faiçal and Geraldo P. R. Filho and Patr{\'i}cia Am{\^a}ncio Vargas and Jo Ueyama and Gustavo Pessin},
  journal={2016 IEEE International Conference on Industrial Technology (ICIT)},
  year={2016},
  pages={652-657}
}
Indoor localization has been an active research area for the last two decades. This emerged in the context of providing a mobile robot the capability to conduct navigation tasks in indoor environments. Although the sensing technologies and techniques proposed for indoor robot localization have proven to be reliable solutions, these cannot be adopted as a solution to people or object localization for indoor environments, particularly, due to their high computational cost and power requirements… CONTINUE READING

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