Trilateration-based Indoor Location using Supervised Learning Algorithms
27th International Conference on Applied Electronics, AE 2022
; 2022-September, 2022.
Article
in English
| Scopus | ID: covidwho-2103138
ABSTRACT
The indoor positioning system (IPS) has a wide range of applications, due to the advantages it has over Global Positioning Systems (GPS) in indoor environments. Due to the biosecurity measures established by the World Health Organization (WHO), where the social distancing is provided, being stricter in indoor environments. This work proposes the design of a positioning system based on trilateration. The main objective is to predict the positioning in both the 'x' and 'y' axis in an area of 8 square meters. For this purpose, 3 Access Points (AP) and a Mobile Device (DM), which works as a raster, have been used. The Received Signal Strength Indication (RSSI) values measured at each AP are the variables used in regression algorithms that predict the x and y position. In this work, 24 regression algorithms have been evaluated, of which the lowest errors obtained are 70.322 [cm] and 30.1508 [cm], for the x and y axes, respectively. © 2022 IEEE.
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Databases of international organizations
Database:
Scopus
Language:
English
Journal:
27th International Conference on Applied Electronics, AE 2022
Year:
2022
Document Type:
Article
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