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.
[1]
Moustafa Youssef,et al.
Analysis of a Device-Free Passive Tracking System in Typical Wireless Environments
,
2009,
2009 3rd International Conference on New Technologies, Mobility and Security.
[2]
Lionel M. Ni,et al.
A Survey on Wireless Indoor Localization from the Device Perspective
,
2016,
ACM Comput. Surv..
[3]
Ning An,et al.
SCPL: indoor device-free multi-subject counting and localization using radio signal strength
,
2013,
IPSN.
[4]
Moustafa Youssef,et al.
Nuzzer: A Large-Scale Device-Free Passive Localization System for Wireless Environments
,
2009,
IEEE Transactions on Mobile Computing.
[5]
L. M. Kamarudin,et al.
Analysis of RSSI-based DFL for human detection in indoor environment using IRIS mote
,
2016,
2016 3rd International Conference on Electronic Design (ICED).
[6]
Ammar Zakaria,et al.
RSSI-based Device Free Localization for Elderly Care Application
,
2017,
IoTBDS.