LOCI: Privacy-aware, device-free, low-power localization of multiple persons using IR sensors

S. Narayana, V. Rao, R.V. Prasad, A.K. Kanthila, K. Managundi, L. Mottola, T. V. Prabhakar

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

Abstract

High accuracy and device-free indoor localization is still a holy grail to enable smart environments. With the growing privacy concerns and regulations, it is necessary to develop methods and systems that can be low-power, device-free as well as privacy-aware. While IR-based solutions fit the bill, they require many modules to be installed in the area of interest for higher accuracy, or proper planning during installation, or they may not work if the background has multiple heat-emitting objects, etc. In this paper, we propose a custom-built miniature device called LOCI that uses IR sensing. One unit of LOCI can provide three-dimensional localization at best. LOCI uses only a thermopile and a PIR sensor built within a 5x5x2 cm3 module. Since IR-based sensing is used, LOCI consumes around 80 mW. LOCI uses analog waveform from the PIR sensor with the gain of the PIR sensor dynamically controlled through software in real-time to simulate spatial diversity. LOCI proposes low-complexity techniques with sensor fusion to eliminate the noise in the background, which has not been handled in previous works even with sophisticated signal processing techniques. Since LOCI uses raw data from the thermopile, the computations are power-efficient. We present the complete design of LOCI and the proposed methodology to estimate height and location. LOCI achieves accuracies of sub-22 cm with a confidence of 0.5 and sub-35 cm with a confidence of 0.8. The best-case location accuracy is 12.5 cm. The accuracy of height estimation is within 8 cm in majority cases. LOCI can easily be extended to recognize activities.

Original languageEnglish
Title of host publication2020 19th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN)
EditorsL. O'Conner
Place of PublicationPiscataway
PublisherIEEE
Pages121-132
Number of pages12
ISBN (Electronic)978-1-7281-5497-8
ISBN (Print)978-1-7281-5498-5
DOIs
Publication statusPublished - 2020
Event19th ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN 2020 - Sydney, Australia
Duration: 21 Apr 202024 Apr 2020

Conference

Conference19th ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN 2020
CountryAustralia
CitySydney
Period21/04/2024/04/20

Keywords

  • device-free
  • infrared
  • localization
  • passive
  • PIR
  • privacy-aware
  • thermopile

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