Using DIALux and Regression-based Machine Learning Algorithm for Designing Indoor Visible Light Positioning (VLP) and Reducing Training Data Collection

Abstract

We propose and demonstrate using DIALux software with regression-machine-learning for designing visible-light-positioning (VLP) systems. Besides, the proposed scheme can also reduce the burden of training data collection in VLP systems.

Utilizing Lighting Design Software for Simulation and Planning of Machine Learning Based Angle-of-Arrival (AOA) Visible Light Positioning (VLP) Systems

“…Then, the precise position inside a particular unit cell can be obtained by using AOA VLP scheme. Using DIALux® for the VLP systems have already been reported [27][28][29][30]; however, they are applied for the RSS based VLP system. Here, our contribution is to show the feasibility of using DIALux® for the AOA based VLP system.…”

“…Here, we evaluate the applicability of the proposed scheme to several popular ML models, including second order linear regression (LR), artificial neural-network (ANN), and convolutional neural-network (CNN). Previously, DIALux® has been applied in the RSS based VLP systems without [27,28] and with obstacle [29], as well as in 3D environment [30]. Here, we evaluate the applicability of DIALux® for the AOA based VLP system.…”