Development of real-time monitoring BLE-LoRa positioning system based on RSSI for non-line-of-sight condition

Abstract

Indoor positioning has become popular in this decade and is used to locate users or objects in indoor environments. This is because global positioning system (GPS) is not efficient for indoor use due to the multipath fading effect. This research is about development bluetooth low energy (BLE) indoor positioning system with the aid of long range (LoRa) network and guideline on selection of the BLE beacons. Next, positioning systems are developed consisting of BLE beacons, a transceiver of hybrid BLE-LoRa module, a LoRa receiver and Raspberry Pi as real-time monitoring. The received signal strength indicator (RSSI) and BLE Mac address from BLE beacons received via LoRa network are analyzed using the positioning algorithm designed in MATLAB. The positioning algorithm incorporates distance estimation, filter implementation and trilateration technique. The estimated location is analyzed with the root mean square error (RMSE) and cumulative distribution function (CDF). According to the results, implementing the filter reduces the positioning accuracy error, achieving 90% accuracy of positioning error less than 1.20 meters for the whole testbed. Finally, the algorithm is embedded into Raspberry Pi to view the location via desktop.

Description and analysis of Sigfox received signal strength indicator dataset by using statistical techniques

“…Currently there is a large amount of research related to geopositioning measures for received signal strength indicator (RSSI) data analysis with different applications [1], [2], one of them is the internet of things (IoT), which has become the concept of the internet of the future. This occurred since it defines a system where things in the physical world and sensors within or near them are connected to the internet via a wireless network or a fixed internet connection [3], [4].…”

Long range based effective field monitoring system

“…In terms of distance and minimal power usage, LoRa holds its position. Nearly all products, such as mobile devices, headphones, and speakers, include blue tooth low energy (BLE) [29]. Similarly, Wi-Fi exists but LoRa prevails.…”

A device identification method from BLE advertising packets with randomized MAC addresses based on regression of received signal strength

“…Many BLE devices such as mobile devices enabling Find My [1], lost prevention or tracking tags [2], smartphone applications [3], broadcast BLE advertising packets periodically. By observing MAC addresses of BLE advertising packets, device tracking can be accomplished [4,5]. For example, by installing multiple monitoring devices within a facility and observing BLE advertising packets, it is possible to know how mobile devices move within the facility.…”