Indoor Tracking with Sensor Networks

Passive target tracking in 3D indoor environments using DNNs and wireless sensors — M.Eng. thesis

For my M.Eng. thesis at Kwangwoon University, I studied passive target tracking in three-dimensional indoor environments using deep neural networks together with adaptive wireless sensor networks (ultrasonic, Wi-Fi, RF, beacon).

The work explored how geometric constraints in adaptive sensor networks can be combined with learned representations for robust indoor localization.

Related publications: (Zhou et al., 2018; Ahn et al., 2016)

References

2018

Sensors

A Passive Tracking System Based on Geometric Constraints in Adaptive Wireless Sensor Networks

Biao Zhou, Deokhyun Ahn, J. Lee, C. Sun, S. Ahmed, and Youngok Kim

Sensors, 2018

Bib HTML PDF

@article{zhou2018passive,
  title = {A Passive Tracking System Based on Geometric Constraints in Adaptive Wireless Sensor Networks},
  author = {Zhou, Biao and Ahn, Deokhyun and Lee, J. and Sun, C. and Ahmed, S. and Kim, Youngok},
  journal = {Sensors},
  volume = {18},
  number = {10},
  pages = {3276},
  year = {2018}
}

2016

JKICS

2D Indoor Map Building Scheme Using Ultrasonic Module

Deokhyun Ahn, Nammoon Kim, Ji-Hye Park, and Youngok Kim

Journal of the Korean Institute of Communications and Information Sciences, 2016

Bib HTML

@article{ahn20162d,
  title = {2D Indoor Map Building Scheme Using Ultrasonic Module},
  author = {Ahn, Deokhyun and Kim, Nammoon and Park, Ji-Hye and Kim, Youngok},
  journal = {Journal of the Korean Institute of Communications and Information Sciences},
  volume = {41},
  number = {8},
  pages = {986--994},
  year = {2016}
}