Real-Time Location System (RTLS) Based on the Bluetooth Technology for Internal Logistics

Augustyn Lorenc (), Jakub Szarata and Michał Czuba
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Augustyn Lorenc: Department of Rail Vehicles and Transport, Cracow University of Technology Poland, al. Jana Pawla II 37, 31-864 Cracow, Poland
Jakub Szarata: SKK S.A., R&D, ul. Gromadzka 54A, 30-719 Cracow, Poland
Michał Czuba: SKK S.A., R&D, ul. Gromadzka 54A, 30-719 Cracow, Poland

Sustainability, 2023, vol. 15, issue 6, 1-22

Abstract: The problem of object localization in indoor environments is very important in order to make a company effective and to detect disruption in the logistics system in real-time. Present research investigates how the IoT (Internet of Things) location system based on Bluetooth can be implemented for this solution. The location based on the Bluetooth is hard to predict. Radio wave interference in this frequency is affected by other devices, steel, vessels containing water, and more. However, proper data processing and signal stabilization can increase the accuracy of the location. To be sure that the location system based on the BT (Bluetooth) can be implemented for real cases, an analysis of signal strength amplitude and disruption was made. The paper presents R&D (Research and Development) works with a practical test in real cases. The signal strength fluctuation for the receiver is between 7 and 10 dBm for ESP32 device and between 13 and 14 dBm for Raspberry. For commercial implementation the number of devices scanned in the time window is also important. For Raspberry, the optimal time window is 5 s; in this time six transmitters can be detected. ESP32 has a problem with detecting devices in a short time, as just two transmitters can be detected in 4–8 s time window. Localisation precision depends on the distance between transmitter and receiver, and the angle from the axis of the directional antenna. For the distance of 10 m the measurement error is 1.2–6.1 m, whilst for the distance of 40 m the measurement error is 4.9 to 24.6 m. Using a Kalman filter can reduce the localization error to 1.5 m.

Keywords: real-time location system; Bluetooth; Bluetooth Low Energy; sensor; internal logistics; disruption; location (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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