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. 2021 Oct 25;23(11):1401.
doi: 10.3390/e23111401.

Ultra-Low-Power, High-Accuracy 434 MHz Indoor Positioning System for Smart Homes Leveraging Machine Learning Models

Haq Nawaz  1 , Ahsen Tahir  1   2 , Nauman Ahmed  1 , Ubaid U Fayyaz  1 , Tayyeb Mahmood  1 , Abdul Jaleel  3 , Mandar Gogate  4 , Kia Dashtipour  4 , Usman Masud  5 , Qammer Abbasi  2
Affiliations

Ultra-Low-Power, High-Accuracy 434 MHz Indoor Positioning System for Smart Homes Leveraging Machine Learning Models

Haq Nawaz et al. Entropy (Basel). .

Abstract

Global navigation satellite systems have been used for reliable location-based services in outdoor environments. However, satellite-based systems are not suitable for indoor positioning due to low signal power inside buildings and low accuracy of 5 m. Future smart homes demand low-cost, high-accuracy and low-power indoor positioning systems that can provide accuracy of less than 5 m and enable battery operation for mobility and long-term use. We propose and implement an intelligent, highly accurate and low-power indoor positioning system for smart homes leveraging Gaussian Process Regression (GPR) model using information-theoretic gain based on reduction in differential entropy. The system is based on Time Difference of Arrival (TDOA) and uses ultra-low-power radio transceivers working at 434 MHz. The system has been deployed and tested using indoor measurements for two-dimensional (2D) positioning. In addition, the proposed system provides dual functionality with the same wireless links used for receiving telemetry data, with configurable data rates of up to 600 Kbauds. The implemented system integrates the time difference pulses obtained from the differential circuitry to determine the radio frequency (RF) transmitter node positions. The implemented system provides a high positioning accuracy of 0.68 m and 1.08 m for outdoor and indoor localization, respectively, when using GPR machine learning models, and provides telemetry data reception of 250 Kbauds. The system enables low-power battery operation with consumption of <200 mW power with ultra-low-power CC1101 radio transceivers and additional circuits with a differential amplifier. The proposed system provides low-cost, low-power and high-accuracy indoor localization and is an essential element of public well-being in future smart homes.

Keywords: indoor positioning system (IPS); telemetry link; time difference of arrival (TDOA); ultra-low power.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Illustration of the Time Difference of Arrival (TDOA)-based localization scheme.
Figure 2
Figure 2
The architecture of the proposed TDOA-based positioning system using three receivers.
Figure 3
Figure 3
The CC1101 circuit schematic for 434 MHz operation and its evaluation board [30].
Figure 4
Figure 4
(a) Circuit Maker schematic for the differential amplifier and the envelop detector. (b) The frequency response of the circuit presented in (a).
Figure 5
Figure 5
The Circuit Maker simulation results for the differential amplifier and envelop detector.
Figure 6
Figure 6
The implemented differential amplifiers with the envelope detector.
Figure 7
Figure 7
The implemented TDOA-based IPS system using three TI CC1101 radio transceivers.
Figure 8
Figure 8
Test and measurement setup: (a) three CC1101 as receivers; (b) one CC1101 as transmitter; (c) placement of the three measuring receivers in 2D space to locate the target Tx.
Figure 9
Figure 9
The CC1101 configured as a 434 MHz transmitter (−10 dBm, 250 Kbaud data rate).
Figure 10
Figure 10
Three CC1101devices configured as 434 MHz measuring receivers.
Figure 11
Figure 11
The oscilloscope screenshots of received waveforms from two receivers and corresponding output of envelope detector along with measurement setup.(a) received waveforms from Rx1 and Rx3; (b) output of the envelope detector; (c) test and measurement setup.
Figure 12
Figure 12
The estimated (measured) location vs. the actual location of the target transmitter in an LOS environment (outdoor scenario).
Figure 13
Figure 13
The estimated (measured) location vs. actual location of target transmitter in NLOS environment (indoor scenario).
See this image and copyright information in PMC

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