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Neural network-based indoor tag-less localization using capacitive sensors

Published: 09 September 2019 Publication History

Abstract

Many applications aim to make smarter the indoor environments where most people spend much of their time (home, office, transportation, public spaces), but they need long-term low-cost human sensing and monitoring capabilities. Small capacitive sensors match well most requirements, like privacy, power, cost, and unobtrusiveness, and, importantly, they do not rely on wearables or specific human interactions. However, long-range capacitive sensors often need advanced data processing to increase their performance. Our ongoing research experimental results show that four 16 cm X 16 cm capacitive sensors deployed in a 3 m X 3 m room can taglessly track the movement of a person with a root mean square error as low as 26 cm. Our system uses a median and low-pass filter for sensor signal conditioning before an autoregressive neural network that we trained to infer the location of the person in the room.

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Cited By

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  • (2022)Research on Indoor Spatial Behavior Perception IoT Smart System for Solitary Elderly at HomeDesigns10.3390/designs60500756:5(75)Online publication date: 28-Aug-2022
  • (2021)Neural Networks for Indoor Person Tracking With Infrared SensorsIEEE Sensors Letters10.1109/LSENS.2021.30497065:1(1-4)Online publication date: Jan-2021
  • (2020)Neural Networks for Indoor Human Activity ReconstructionsIEEE Sensors Journal10.1109/JSEN.2020.300600920:22(13571-13584)Online publication date: 15-Nov-2020

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cover image ACM Conferences
UbiComp/ISWC '19 Adjunct: Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers
September 2019
1234 pages
ISBN:9781450368698
DOI:10.1145/3341162
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Published: 09 September 2019

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Author Tags

  1. capacitive sensing
  2. indoor localization
  3. neural networks
  4. tagless indoor localization

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UbiComp '19

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Overall Acceptance Rate 764 of 2,912 submissions, 26%

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Cited By

View all
  • (2022)Research on Indoor Spatial Behavior Perception IoT Smart System for Solitary Elderly at HomeDesigns10.3390/designs60500756:5(75)Online publication date: 28-Aug-2022
  • (2021)Neural Networks for Indoor Person Tracking With Infrared SensorsIEEE Sensors Letters10.1109/LSENS.2021.30497065:1(1-4)Online publication date: Jan-2021
  • (2020)Neural Networks for Indoor Human Activity ReconstructionsIEEE Sensors Journal10.1109/JSEN.2020.300600920:22(13571-13584)Online publication date: 15-Nov-2020

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