Passive Indoor Localization or Device Free Localization (DFL)

Wireless DFL:

DFL can track an “untagged” object and therefore does not require active participation from the target. Traditional research on passive localisation is fractured with siloed approach, concentrating on single sensing modality. Robust, functioning positioning can only be realised if it is treated as a multidisciplinary, multisensory problem. At Smart Lab, we have a unique, holistic perspective on localisation and have developed advanced prototypes that utilize wireless, visible light, Infrared and capacitive floor-based sensing for device free positioning.

Wireless-based localization has the advantage of potentially being able to localize with existing infrastructure by leveraging the ubiquitous presence of wireless network within the built environment. We have implemented one of the most advanced wireless DFL prototype systems based on ZigBee and Wi-Fi technologies and using RSSI and CSI metrics. 

Researchers:

  • Nathaniel Faulkner (PhD researcher)
  • Dr Daniel Konings
  • Prof Edmund Lai
  • A/P Fakhrul Alam (Research lead)

Publications in Device Free Localization:

  1. F. Alam, N. Faulkner, and B. Parr, " Device Free Localization: A Review of Non-RF Techniques for Unobtrusive Indoor Positioning," IEEE Internet of Things Journal, October 2020.

Publications in Wireless Device Free Localization:

  1. D. Konings, F. Alam, F. Noble and E. M.-K. Lai, “Improved Distance Metrics for Histogram-based Device-free Localization," IEEE Sensors Journal, vol. 19, no. 19, pp. 8940-8950, October 2019.
  2. D. Konings, F. Alam, F. Noble and E. M.-K. Lai, "SpringLoc: A Device-free Localization Technique for Indoor Positioning and Tracking using Adaptive RSSI Spring Relaxation," IEEE Access, vol. 7, pp. 56960- 56973, April 2019.
  3. D. Konings, F. Alam, F. Noble and E. M.-K. Lai, "Device-free Localization Systems Utilizing Wireless RSSI: A Comparative Practical Investigation," IEEE Sensors Journal, vol. 19, no. 7, pp. 2747- 2757, April 2019.
  4. D. Konings and F. Alam " LifeCount: A Device-free CSI-based Human Counting Solution for Emergency Building Evacuations," Proceedings - 2020 IEEE Sensors Applications Symposium (SAS2020), 2020.
  5. D. Konings, N. Faulkner, F. Alam, F. Noble, and E. M.-K. Lai, "The effects of interference on the RSSI values of a ZigBee based indoor localization system," in Mechatronics and Machine Vision in Practice (M2VIP), 2017 24th International Conference on, 2017, pp. 1-5: IEEE.
  6. D. Konings, N. Faulkner, F. Alam, F. Noble, and E. M.-K. Lai, "Do RSSI values reliably map to RSS in a localization system?," in Recent Trends in Telecommunications Research (RTTR), Workshop on, 2017, pp. 1-5: IEEE.
  7. D. Konings, A. Budel, F. Alam, and F. Noble, "Entity tracking within a Zigbee based smart home," in Mechatronics and Machine Vision in Practice (M2VIP), 2016 23rd International Conference on, 2016, pp. 1-6: IEEE.

Passive Indoor Localization or Device Free Localization (DFL) using Visible Light

Passive VLP has the potential to be significantly more accurate than passive wireless positioning. Passive VLP can leverage existing lighting infrastructure. There are only a handful existing works dedicated to passive VLP. We have implemented one of the world’s first passive VLP systems utilizing wall mounted light-sensors.

Researchers:

  • Nathaniel Faulkner (PhD researcher)
  • Dr Daniel Konings
  • Dr Mathew Legg
  • Prof Serge Demidenko
  • Prof Edmund Lai
  • A/P Fakhrul Alam (Research lead)

Publications in Passive VLP:

  1. N. Faulkner, F. Alam, M. Legg and S. Demidenko, " Watchers on the Wall: Passive Visible Light-Based Positioning and Tracking with Embedded Light-Sensors on Wall," IEEE Transactions on Instrumentation & Measurement, November 2019.
  2. D. Konings, N. Faulkner, F. Alam, E. M.-K. Lai and S. Demidenko, “FieldLight: Device-free Indoor Human Localization using Passive Visible Light Positioning and Artificial Potential Fields," IEEE Sensors Journal, October 2019.
  3. N. Faulkner, F. Alam, M. Legg and S. Demidenko " Smart Wall: Passive Visible Light Positioning with Ambient Light Only," Proceedings - International Instrumentation and Measurement Technology Conference (I2MTC 2019), IEEE, 2019.

Passive Indoor Localization or Device Free Localization (DFL) using Smart Sensing Floor

When inside a building, humans spend much of their time in contact with the floor. This therefore lends the floor a new potential purpose: becoming a large sensor for both positioning and identifying people indoors. We have recently implemented a protype floor based on capacitive sensing. The floor acts like a large, low resolution touch screen and can potentially identify events like fall detection and identify individuals through gait recognition.

Researchers:

  • Nathaniel Faulkner (PhD researcher)
  • Dr Mathew Legg
  • Prof Serge Demidenko
  • A/P Fakhrul Alam (Research lead)

Publications in Sensing Floor based DFL:

  1. N. Faulkner, B. Parr, F. Alam, M. Legg and S. Demidenko, " CapLoc: Capacitive Sensing Floor for Device-Free Localization and Fall Detection," IEEE Access, vol. 8, pp. 187353 – 187364, October 2020.
  2. N. Faulkner, B. Parr, F. Alam, M. Legg and S. Demidenko" Device Free Localization with Capacitive Sensing Floor," Proceedings - 2020 IEEE Sensors Applications Symposium (SAS2020), 2020.

Passive Indoor Localization with Low Resolution Thermopile

Human subjects produce infrared (IR) radiation, as their body is normally at a higher temperature than the ambient environment. This IR radiation can be detected by employing thermopiles or thermal cameras. In contrast to PIR sensors, thermopiles have the advantage of being able to acquire absolute temperature values and thus can detect both stationary and mobile targets. We have developed bespoke thermopile sensors using privacy preserving low resolution Panasonic GridEye AMG8833. These sensors can be deployed as a distributed network to localize human subjects.

Researchers:

  • Nathaniel Faulkner (PhD researcher)
  • Eric Ma (PhD researcher)
  • Jasmine Wang (Student researcher)
  • Dr Daniel Konings
  • Dr Mathew Legg
  • Prof Serge Demidenko
  • A/P Fakhrul Alam (Research lead)

Publications in Thermopile Sensing:

  1. N. Faulkner, D. Konings, F. Alam, M. Legg, and S. Demidenko, " Machine Learning Techniques for Device-Free Localization Using Low-Resolution Thermopiles," IEEE Internet of Things Journal, March 2022.
  2. N. Faulkner, F. Alam, M. Legg, and S. Demidenko, " Device-Free Localization Using Privacy-Preserving Infrared Signatures Acquired from Thermopiles and Machine Learning," IEEE Access, June 2021