Low Resolution Spectroscopy Applications to Smart Home Systems: An Exploratory Study

A common challenge in smart environments is tracking individuals throughout different environments. Reliable solutions to this problem often involve cameras, which pose significant privacy issues, or trackable tags such as RFID which require that individuals be ‘prepared’ for the environment. In this paper an exploratory study is presented that investigates the utility of portable visible range spectroscopy hardware for the purposes identifying individuals based on the spectral pattern of their clothing. This is done by assessing the accuracy of a data-driven machine learning models when differentiating clothing. These sensors have the potential to achieve similar success to using the colour histogram from camera tracking without the privacy issues, and without the need to pre-tag individuals as with RFID’.

Content

Author and article information

Contributors

Jordan Vincent

Bronagh Quigley

Conference

Publication date: July 2018

Publication date (Print): July 2018

Pages: 1-4

Affiliations

[0001]University of Ulster

Shore Rd, BT370QB

School of Computing

Vincent-j1@ulster.ac.uk

[0002]University of Ulster

Shore Rd, BT370QB

School of Computing

Article

DOI: 10.14236/ewic/HCI2018.174

SO-VID: 00a7f7d0-134e-455a-b2b0-753fa10b1cf4

License:

This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

Conference name: Proceedings of the 32nd International BCS Human Computer Interaction Conference

Conference acronym: HCI

Conference number: 32

Conference location: Belfast, UK

Conference date: 4 - 6 July 2018

Conference sponsor: Electronic Workshops in Computing (eWiC)

Conference theme: Human Computer Interaction Conference

History

Product

1477-9358 BCS Learning & Development

Self URI (article page): https://www.scienceopen.com/hosted-document?doi=10.14236/ewic/HCI2018.174

Self URI (journal page): https://ewic.bcs.org/

REFERENCES

B. Alsinglawi 2017 RFID Localisation For Internet Of Things Smart Homes: A Survey. CoRR, abs/1702.02311
M. N. K. Boulos 2007 CAALYX: a new generation of location-based services in healthcare. International Journal of Health Geographics, 6 9
L. Chen 2012 Sensor-based Activity Recognition. IEEE Transactions on Systems, Man and Cybernetics, 790 808
J. Krumm 2000 Multi-camera multi-person tracking for EasyLiving. Dublin s.n 3 10
V. MichalisN. ChristophorosI. A. Kakadiaris 2015 A Review of Human Activity Recognition Methods. Frontiers in Robotics and AI, 28
d. Santos M, L.P. RNL. JA 2013 A review on the applications of portable near-infrared spectrometers in the agro-food industry.. Applied Spectroscopy, 67 11 1215 1233
M. Vega-BarbasI. PauL. M. Martin-RuizF. Seoane 2015 Adaptive Software Architecture Based on Confident HCI for the Deployment of Sensitive Services in Smart Homes. Sensors, 15 4 7294 7322
H. Wang 2016 A Real-Time and Contactless Fall Detection System with Commodity WiFi Devices. IEEE Transactions on Mobile Computing, 511 526
S. WoldM. SjostromL. Eriksson 2001 PLS-regression: a basic tool of chemometrics. Chemometrics and Intelligent Laboratory Systems, 58 2 109 130
N. ZoubaF. BremondM. ThonnatV. T. Vu 2007 Multi-sensors Analysis for Everyday Elderly Activity. Tunis s.n

Comments

Comment on this article

[1] B. Alsinglawi 2017 RFID Localisation For Internet Of Things Smart Homes: A Survey. CoRR, abs/1702.02311

[2] M. N. K. Boulos 2007 CAALYX: a new generation of location-based services in healthcare. International Journal of Health Geographics, 6 9

[3] L. Chen 2012 Sensor-based Activity Recognition. IEEE Transactions on Systems, Man and Cybernetics, 790 808

[4] J. Krumm 2000 Multi-camera multi-person tracking for EasyLiving. Dublin s.n 3 10

[5] V. MichalisN. ChristophorosI. A. Kakadiaris 2015 A Review of Human Activity Recognition Methods. Frontiers in Robotics and AI, 28

[6] d. Santos M, L.P. RNL. JA 2013 A review on the applications of portable near-infrared spectrometers in the agro-food industry.. Applied Spectroscopy, 67 11 1215 1233

[7] M. Vega-BarbasI. PauL. M. Martin-RuizF. Seoane 2015 Adaptive Software Architecture Based on Confident HCI for the Deployment of Sensitive Services in Smart Homes. Sensors, 15 4 7294 7322

[8] H. Wang 2016 A Real-Time and Contactless Fall Detection System with Commodity WiFi Devices. IEEE Transactions on Mobile Computing, 511 526

[9] S. WoldM. SjostromL. Eriksson 2001 PLS-regression: a basic tool of chemometrics. Chemometrics and Intelligent Laboratory Systems, 58 2 109 130

[10] N. ZoubaF. BremondM. ThonnatV. T. Vu 2007 Multi-sensors Analysis for Everyday Elderly Activity. Tunis s.n

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