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 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Number of pages | 4 |
ISBN (Electronic) | 9781538656198 |
ISBN (Print) | 9781538662182 |
DOIs | |
Publication status | Published - 24 Jul 2019 |
Event | 2019 IEEE International Conference on Sensors and Nanotechnology, SENSORS and NANO 2019 - Penang, Malaysia Duration: 24 Jul 2019 → 25 Jul 2019 |
Conference
Conference | 2019 IEEE International Conference on Sensors and Nanotechnology, SENSORS and NANO 2019 |
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Country/Territory | Malaysia |
City | Penang |
Period | 24/07/19 → 25/07/19 |
Keywords
- ambient assisted living
- deterministic localization
- device-free localization
- internet of things
- passive radio map
- probabilistic localization