Visible Light Communication (VLC) technology allows wireless data transmission piggybacked by illumination. Highly accurate and reliable systems based on VLC, as Indoor Positioning System (IPS) have been already developed by academics and specialized companies. Underground Positioning System (UPS) addressed here is embedded into the protection equipment, compulsory to be used underground, being therefore important to workers in potential dangerous spaces since fast data communication and real-time data interpretation is therefore possible. This paper presents the VLC technology implemented in mining underground specific environment for an accurate positioning and fast data communication for underground navigation with the main aim of developing a real time warning and alarming system based on Augmented Reality (AR) and Neural Networks (NNs) principles.

The Internet of Things (IoT) has developed tremendously over the past few years and has proven its worth in many areas of activity. With regard to environmental air quality monitoring, there are more and more products and applications that try to gather as much data as possible about all the pollution factors in a given area. This paper aims to present a new method of using devices capable of communicating with each other using the LoRa communication protocol to report to a real-time central server on environmental air quality. The innovation of this paper is the fact that it is implemented using a developed LoRa localization protocol, which connects an air quality sensor network, using only the low power of the LoRa technology by applying a multilayer algorithm to the gateway timestamps from received packages. The so created LoRaWAN tracking system is able to exploit transmitted packets to calculate the current position without using GPS or GSM that are high power consumers.

By using the most rudimentary microcontroller chips, that receive data from sensors, and transmit the data to a computer system, thorough a virtual serial port, motion of many objects, bodies and joints can be captured. Capturing the motion and reproducing it live is not the only destination for the data usage. Recording and studying the motion data, can reduce a lot of work in a wide range of domains. Using the simplest methods to capture the data, also means making it so widely accessible for learning, editing and also developing systems that use very little processing power, granting data access for the less efficient computers. We propose using the MPU-6050 MEMS sensor in a dual instance, and the Arduino UNO microcontroller, connected to a computer for data acquisition, to capture the motion of a human arm, and reproduce it in a projected environment. Other experiments, conducted by other researchers and developers have used a higher number of sensors, and the data acquisition and recording systems were much more complex, but our research reduced the number of sensors to just two. One of the high impact innovations brought by this system, in particular, is that we’ve virtually hooked the end of one sensor to the tip of the other, creating a virtual motion chain.