Preliminary Analysis of RFID Localization System for Moving Precast Concrete Units using Multiple-Tags and Weighted Euclid Distance k-NN algorithm

This paper presents two RFID localization methods based on a k-NN algorithm for multiple moving tracking tags attached to a concrete masonry unit (cinder block). This work uses passive RFID tags for localization and seeks to provide rapid wireless analysis for future smart infrastructure projects where precast concrete modular structures are moved during transport and assembly. The RFID localization system uses four reader antennas, four tracking tags, and 28 reference tags in a realistic indoor assembly environment. Results show average error in the direction of movement as low as 10.5 cm. Increasing the number of nearest neighbors in the k-NN algorithm is shown to reduce error in all coordinate directions. Increasing k from 4 to 6 is shown to reduce error by 4 cm or 10%. The localization environment is analyzed, and reference tags 22, 9, 5, and 8 around the moving cinder block are seen most commonly as nearest neighbors. A modified k -NN algorithm, described here as a weighted Euclidian distance k -NN algorithm is presented that reduces total error from 41.1 cm to 32.5 cm.

I. Introduction

Radiofrequency identification (RFID) has uses in object identification, object tracking, inventory management, and is a key technology for enabling Internet of Things (IoT) and smart infrastructure [1]. Passive, ultra-high frequency (UHF) RFID tags are low-cost and can have read range up to several meters. Due to indoor limitations of GPS, indoor RFID localization offers an alternative for tracking the movement modular infrastructure components during movement and assembly. Modular infrastructure components may include small or large precast concrete sections for bridges, buildings, wind turbine components, and small-scale next-generation nuclear reactors [2].