4.6 Article

A Comparison of Wireless Standards in IoT for Indoor Localization Using LoPy

Journal

IEEE ACCESS
Volume 9, Issue -, Pages 65925-65933

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2021.3076371

Keywords

Location awareness; Wireless communication; Wireless sensor networks; Wireless fidelity; Standards; Hardware; Bluetooth; Indoor localization accuracy; Internet of Things; RSSI; Wi-Fi; Bluetooth low energy; LoRaWAN

Funding

  1. Office of Research Innovation and Commercialization (ORIC) of University of Management and Technology (UMT)
  2. University of Lahore (UOL), Lahore, Pakistan
  3. National Natural Science Foundation of China (NSFC) [51950410583]

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Indoor localization is crucial for various applications in smart cities, requiring the development of a robust and cost-effective real-time system. Recent wireless standards like BLE and LoRa are ideal choices for indoor localization due to their low power consumption. Experimental results show that Wi-Fi is the most accurate, followed by LoRa, with BLE being the least accurate option.
There are surplus applications in modern smart cities where localization of indoor environments is critical ranging from surveillance and trailing in smart structures to the localized wireless distribution of advertising content in shopping malls. These applications are only successful if a robust and cost-effective real-time system is developed for precise localization. Another aspect considered for indoor localization is power consumption. Recent wireless standards such as Bluetooth Low Energy (BLE) and LoRa consume less power which makes them a perfect candidate for indoor localization. This work aims to carry out an experimental evaluation which would help to decide which wireless standard i.e., Wi-Fi, Bluetooth Low Energy (BLE), and LoRa are most suitable for indoor localization. Experiments are carried out using trilateration in three multiple environments. RSSI is used to calculate the coordinates of a sensor node. Results obtained from the experiment show that Wi-Fi is most accurate with an average error of 0.54 m. LoRa is second most accurate with an average error of 0.62 m and BLE is the least accurate with an average error of 0.82 m. These results can be used to decide which wireless standard is best suited for indoor localization.

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