Indoor Navigation with Visible Light Communication using Genetic Algorithm

Abstract

Today, people prefer supermarkets where they can meet all their needs today for their daily needs. People prefer large markets where they can meet all their needs today for their daily needs. These markets, which have a lot of product capacity, mean more waste of time for the consumer. In such indoor and large areas, it is necessary to plan a route to prevent loss of time. In this study, location determination process was made with visible light communication (VLC) in closed areas and the most suitable route was determined by using Genetic Algorithm (GA) with these locations. It is thought that wireless communication resources will not be sufficient in the future due to the density. VLC systems, developed to solve this problem, are a communication system that uses the light source for data transmission. It has been seen in related studies that this system is quite successful in terms of speed, reliability and energy efficiency. VLC systems basically use a transmitter, receiver and microcontroller for their control. In this study, LED light source, TEMP6000 phototransistor-light sensor and ATMEGA328P (Arduino) are used. Due to its very fast on and off feature, the data sent from the LED light source, is detected by the light sensor TEMP6000. After that, it was modulated using On-Off Keying (OOK). In addition to data transmission, VLC systems, which can be used to determine location especially in indoor areas, can also be used for indoor navigation. Also in this study, indoor positioning is designed on the basis of a market application with VLC. The location data was obtained according to the signal strength, which was transferred from the receiver to Matlab. The operation of the system has been tested on the basis of light sources, products under these sources and the shortest path to the products selected by the user. The shortest distance between the stops selected for this navigation process was found by the Floyd-Warshall algorithm. The shortest path was determined by using a GA for the stops with known distance between them, as in the Traveling Salesman Problem (TSP). In this way, the customer will be able to minimize the time and energy consumed in the market.