Artificial Neural Network for LiDAL Systems

Aubida A Al-Hameed,Mohammed Thamer Alresheedi,Jaafar M H Elmirghani,Safwan Hafeedh Younus,Ahmed Taha Hussein

doi:10.1109/access.2019.2933470

Aubida A Al-Hameed, Mohammed Thamer Alresheedi + Show 3 more

Open Access

https://doi.org/10.1109/access.2019.2933470

Copy DOI

Abstract

In this paper, we introduce an intelligent light detection and localization (LiDAL) system that uses artificial neural networks (ANN). The LiDAL systems of interest are MIMO LiDAL and MISO IMG LiDAL systems. A trained ANN with the LiDAL system of interest is used to distinguish a human (target) from the background obstacles (furniture) in a realistic indoor environment. In the LiDAL systems, the received reflected signals in the time domain have different patterns corresponding to the number of targets and their locations in an indoor environment. The indoor environment with background obstacles (furniture) appears as a set of patterns in the time domain when the transmitted optical signals are reflected from objects in LiDAL systems. Hence, a trained neural network that has the ability to classify and recognize the received signal patterns can distinguish the targets from the background obstacles in a realistic environment, especially given the mobility of targets (humans) which distinguishes them from static obstacles (furniture). The LiDAL systems with ANN are evaluated in a realistic indoor environment through computer simulation.

Highlights

Visible light communication (VLC) is part of optical wireless communication (OWC) that uses light as a carrier to modulate the information signal in the visible spectrum (380nm to 780nm) [14]
This paper presented new localization systems that employ artificial neural networks with MIMO light detection and localization (LiDAL) and MISO IMG LiDAL systems for people detection, counting and localization
The results of intelligent LiDAL systems with the trained neural network show that significant improvement in the counting and localization are achieved compared with traditional LiDAL systems with distinguishing methods namely; Background subtraction method (BSM) and Cross Correlation method (CCM)

Summary

Introduction

Visible light communication (VLC) is part of optical wireless communication (OWC) that uses light as a carrier to modulate the information signal in the visible spectrum (380nm to 780nm) [14]. VLC systems are becoming more popular everyday due to their inherent advantages over radio frequency (RF) systems. The advantages include a large unregulated spectrum, low complexity of transceiver units, freedom from fading, confidentiality and immunity against interference from electrical devices [5]-[8]. In [14], a light sensing system using VLC (LiSense) was proposed to track the human gesture and reconstruct human skeleton. The LiSense system makes use of 324 photodetector array placed on the floor to sense the beacon signals sent from the light sources (VLC transmitters) to recover the human shadow pattern created by individual VLC transmitters. A laser radar in conjunction with VLC system was introduced in [15] to provide vehicle to vehicle ranging and VLC communication

Methods

Results

Conclusion