2020•Unpublished venueRequires access

Indoor Tracking with Bluetooth Low Energy Devices Using K-Nearest Neighbour Algorithm

Koon Kee Lie, Kwok Shien Yeo, Alvin Kee Ngoh Ting, David Heng Tze Chieng

Abstract

In this paper we discuss the design of an indoor positioning system (IPS) using Bluetooth Low Energy (BLE) scanners and beacons. We deployed the prototype system in a laboratory where its dimension is measured at 990 × 770 cm2, Range test has been carried out to study the relationship between distance and Received Signal Strength (RSSI) of the BLE devices. Using the highest RSSI values received from 3 of the scanners, we use K-Nearest Neighbour algorithm to predict the region where the beacon is possibly located. We further demonstate that our system is able to estimate the location region of the target beacon with good accuracy.

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Available abstract

Key concepts: Beacon, Bluetooth Low Energy, Bluetooth, Received signal strength indication, Computer science, Energy (signal processing), Algorithm, Tracking (education)