Increasing accuracy RFID Dock Door Discrimination with Naive Bayes Classifier

Master thesis (2023)

Authors

B.W. Berenschot Mechanical Engineering

Contributors

M.B. Duinkerken Transport Engineering and Logistics - Mechanical, Maritime and Materials Engineering (mentor)
R.R. Negenborn Transport Engineering and Logistics - Mechanical, Maritime and Materials Engineering (graduation committee member)
Walter Romijn (mentor)
Faculty
Mechanical Engineering, Mechanical Engineering
Copyright: © 2023 Bastijn Berenschot
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Published Date

17-01-2023

Language

English

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Faculty

Mechanical Engineering

Abstract

Errors during truck loading at dock doors lead to unwanted wrong deliveries in logistics. Due to the falling price of RFID tags, RFID dock door discrimination is now being used for product registration. The problems that arise with the current system for RFID Dock Door Discrimination are cross-reads and miss-reads. The purpose of this research is to increase the accuracy of product registration by the proposed Dock Door Discrimination method with Naive Bayes Classifier (NBC). A hardware design, including 4 RFID antennas at three adjacent dock doors and 1 added antenna at the staging area, and software design, including the implementation of the NBC, are proposed to improve the RFID Dock Door Discrimination. The Experimental Setup and Plan were used to gather data to compare the current RFID transition system with the new proposed NBC system in six scenarios, three with and without noise at other gates. For each individual scenario, the accuracy improved most with NBC with one input feature. The accuracy for all scenarios combined for the collected data improved from 82.1$ (current) to 93.6(NBC).These results mean that there is a solid improvement in implementing the Naive Bayes Classifier over the current RFID transition system for Dock Door Discrimination.