Abstract

This study discusses the estimated position of objects in buildings with the value of Recieved Signal Strength Indicator (RSSI) on IEEE 802.11 used as the research parameter. The algorithm used in estimating the location of the RSS Fingerprint measurement is the naive bayes classifier. Position Estimation is done on the 1st floor of building B majoring in computer system, university sriwijaya with an area 305,28 m 2 with length 31.8 meters and width 9.6 meters. The result of the position estimation that has been done by comparing training dataset with data testing shows that the estimation is successful with the prediction of room 2 with the coordinate point (11.3).

Keywords:
Naive Bayes classifier RSS Classifier (UML) Artificial intelligence Computer science Signal strength Bayes' theorem Position (finance) Bayes error rate Pattern recognition (psychology) Data mining Computer vision Machine learning Bayes classifier Support vector machine Bayesian probability Wireless Telecommunications

Metrics

1
Cited By
0.12
FWCI (Field Weighted Citation Impact)
9
Refs
0.52
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Indoor and Outdoor Localization Technologies
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
IoT and GPS-based Vehicle Safety Systems
Physical Sciences →  Engineering →  Mechanical Engineering
IoT-based Smart Home Systems
Physical Sciences →  Engineering →  Electrical and Electronic Engineering

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