Visible light positioning

Citation Author(s):
Huiying
Zhang
Submitted by:
Huiying Zhang
Last updated:
Mon, 05/22/2023 - 03:31
DOI:
10.21227/a8nt-m060
License:
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Abstract 

At present, various technologies have been developed for indoor positioning, such as Bluetooth, infrared, wireless local area network, radio frequency identification (RFID), and ultra-wide band (UWB) , but most of these technologies require hardware, are costly, and are susceptible to electromagnetic interference. Visible light positioning technology has become a research hotspot in the field of indoor positioning because of its unique advantages, such as no complex equipment, high security, and high positioning accuracy .At present, indoor visible light positioning technology based on machine learning is widely used.This article proposes an indoor visible light localization algorithm based on fingerprint library and neural network. We establish an indoor visible light positioning model, collect received signal strength values using receivers, establish a fingerprint database, use machine learning algorithms to classify fingerprint points, input them into an optimized neural network for training, and establish a positioning model.

Instructions: 

This dataset contains the positioning errors when using neural networks and optimized neural networks to locate rooms

Comments

dfg

Submitted by Arif Ullah on Mon, 07/03/2023 - 01:24

Dear Arif Ullah
I want this dataset, can you share it with me. I would greatly appreciate it if you could agree.

Submitted by Hongji Cao on Wed, 08/30/2023 - 04:58

Dataset Files

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