Visible light positioning

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.