Repository for the Dissertation of Machine Learning For Visible Light Positioning with Non-Imaging Sensors for the degree of MSc in Electrical and Telecomunications Engineering of the University of Aveiro.
- This repository contains the code for the dissertation of Machine Learning For Visible Light Positioning with Non-Imaging Sensors
- Version 1.0
- Enter the 'MATLAB' folder and then enter the 'VLP_HTM' folder
- Open the 'demo_Renato.mlx' file
- Setup the parameters of the simulation
- Make sure that the paths for the .xlsx files are correct
- Run the simulation
PS: The simulation can take up a long time to run, depending on the amount of data we want to simulate, for example, 2.880.000 samples can take up to 15 minutes to run.
- Open the 'demo3.ipynb' file
- Install the required libraries (numpy, pandas, matplotlib, sklearn, seaborn, tensorflow, keras, ...)
- If you want to run the model with GPU support, make sure that you have the correct drivers installed and that you have a CUDA compatible GPU
- Setup the parameters of the simulation
- Make sure that the paths for the .xlsx files are correct
- Run the code