Abstract
A radio frequency (RF) based device-free indoor localization (DFL) has attracted a lot of research effort due to its simplicity, less costly and compatibility with the existing hardware equipped with RF interface compared to the existing positioning system. An advanced monitoring system, known as Ambient Assisted Living (AAL) has been developed using DFL and Internet of Things (IoT) technologies. In this paper, we present a probabilistic DFL system using passive radio map method based on a non-parametric histogram-based approach to locate and map the passive target position in an indoor area. The proposed technique is based on a radio map concept in locating human position using received signal strength indicator (RSSI). The Bayesian inversion was introduced in the proposed approach for estimating the density function and the Probability of Error metric (PoE) was used to evaluate the tracking accuracy of the system. We firstly performed system analysis on the deterministic approach for comparison with the proposed probability approach. The results show that the probabilistic approach can accurately locate a passive target with an error probability of 0.0782 compared to the deterministic approach that gives high PoE of 0.2463.
Original language | English |
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Title of host publication | 2019 IEEE International Conference on Sensors and Nanotechnology |
Place of Publication | Penang, Malaysia |
Publisher | IEEE |
Number of pages | 4 |
ISBN (Electronic) | 9781538656198 |
ISBN (Print) | 9781538662182 |
DOIs | |
Publication status | Published - 24 Jul 2019 |
Event | IEEE International Conference on Sensors and Nanotechnology - Bayview Beach Resort , Pulau Pinang, Malaysia Duration: 24 Jul 2019 → 25 Jul 2019 https://sensorsandnano2019.ieeemy.org/ |
Conference
Conference | IEEE International Conference on Sensors and Nanotechnology |
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Abbreviated title | SN |
Country/Territory | Malaysia |
City | Pulau Pinang |
Period | 24/07/19 → 25/07/19 |
Internet address |
Keywords
- Device-free Localization
- deterministic localization
- probabilistic localization
- passive radio map
- Ambient Assisted Living
- Internet of Things