At present, computer networks are no longer used to connect just personal computers. Smaller devices can connect to them even at the level of individual sensors and actuators. This trend is due to the development of modern microcontrollers and singleboard computers which can be easily connected to the global Internet. The result is a new paradigm—the Internet of Things (IoT) as an integral part of the Industry 4.0; without it, the vision of the fourth industrial revolution would not be possible. In the field of digital factories it is a natural successor of the machine-to-machine (M2M) communication. Presently, mechatronic systems in IoT networks are controlled and monitored via industrial HMI (human-machine interface) panels, console, web or mobile applications. Using these conventional control and monitoring methods of mechatronic systems within IoT networks, this method may be fully satisfactory for smaller rooms. Since the list of devices fits on one screen, we can monitor the status and control these devices almost immediately. However, in the case of several rooms or buildings, which is the case of digital factories, ordinary ways of interacting with mechatronic systems become cumbersome. In such case, there is the possibility to apply advanced digital technologies such as extended (computer-generated) reality. Using these technologies, digital (computer-generated) objects can be inserted into the real world. The aim of this article is to describe design and implementation of a new method for control and monitoring of mechatronic systems connected to the IoT network using a selected segment of extended reality to create an innovative form of HMI.
This paper is focused on the possibilities of data collection via photogrammetry methods, using smartphone cameras and post-processing. The aim of this paper is to refer to progressive technologies that are part of smartphone devices, which bring more performance and variability of usage year by year. The theoretical part starts with looking to the past, describing problems of measurements and solutions invented by famous mathematicians, which we use nowadays. The following section deals with the background of measuring the human body and photogrammetry. The next section is about measuring and using calibration methods. The results section presents the architecture design of the system and a visual representation of how the application works. The result of processing a 3D person is a data object with measurements in real world metric units with minimum deviation. The conclusion is that we created our own low-cost method for 3D body measurement which partially or completely removes the shortcomings that were identified during the review of similar solutions. Our method is based on the use of open-source libraries, the use of a single smartphone mobile device and the creation of a true 3D human body model.
Abstract-The paper deals with the development of a system for automatic weld recognition using new information technologies based on cloud computing and single-board computer in the context of Industry 4.0. The proposed system is based on a visual system for weld recognition, and a neural network based on cloud computing for real-time weld evaluation, both implemented on a single-board low-cost computer. The proposed system was successfully verified on welding samples which correspond to a real welding process in the car production process. The system considerably contributes to the welds diagnostics in industrial processes of small-and medium-sized enterprises.
Abstract-The paper demonstrates remote control of test experiment in the virtual laboratory. This is a common problem, but another way can always be used to solve it. The paper compares several existing virtual laboratories and their possible issues at present. To develop such a new solution JavaScript technology was used on both client and server side using Node.js runtime. The modern approach is a visualization of received data in mixed reality using Microsoft HoloLens or another compatible device with Windows Mixed Reality platform.
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