Research Article

Hybrid Indoor-Based WLAN-WSN Localization Scheme for Improving Accuracy Based on Artificial Neural Network

Table 2

Comparison between the proposed hybrid indoor positioning system and previous hybrid indoor positioning studies.

ReferenceHybrid position systemsType of studyTest areaTotal number of anchor pointsAccuracyImplementation

[12]WSN + RFIDExperimental5 30 m148
(approx.)
1.6 mFingerprinting + extended Kalman filter approach
[29]WiFi + bluetoothExperimental & simulation50 m241.75 mFingerprinting approach
[30]WiFi + RFIDExperimental25 12 m80
(approx.)
1.6 mFingerprinting + particle filter approach
Our WiFi data (alone)WiFiExperimental25 282281.22Fingerprinting + artificial neural network
Our WSN
data (alone)
WSNExperimental10 28961.36Fingerprinting + artificial neural network
Proposed hybrid indoor systemWiFi + WSNExperimental10 28 m961.05 mFingerprinting + artificial neural network