Automated Guided Vehicles (AGVs) are a key component of many modern industrial systems. AGVs are supposed to communicate with each other in real time using wireless networks. In this article, the advantages and disadvantages of the ZigBee wireless network related to the control of AGVs are considered. We analyze the performance of the ZigBee network programmed with both C# and Python libraries to control ZigBee devices. The throughput and signal strength are presented and discussed depending on the transmission speed of the serial port, the payload size, and the presence and distance from the obstacles. The results of the experiments show the effective values of these parameters, the methods of using C# and Python, and the reliability of the throughput up to a certain point in network devices.

The rapid but uneven education development worldwide is creating many challenges. Changing conditions and rules in engineering fields such as programming, automation, and electronics are not always followed by changes in education. Employers expect potential candidates to be current with the latest domain competencies and soft skills. The idea is to hire candidates with both knowledge (theoretical and practical) and experience in reflection and collaboration skills. Universities can not always keep up with the development of technology and the adaptation of curricula because change happens so quickly. Therefore, upgrades are needed in engineering education. Focusing education solely on measurable knowledge and results is a simple but often insufficient approach to presenting the entire curriculum within the time frame of a course. Our study of about 150 engineering students in Poland and Norway included the role of students' experiences in hands-on activities, especially labs. The research aimed to determine what students expect, what influences their results, and what complications may arise. The study results show that students often struggle with time management, prioritizing, and understanding practical tasks. In addition, there is a difference between students with and without practical work experience. Our research showed that both groups of students did not achieve all their intended educational goals for various reasons. Therefore, adapting the current teaching system to the student's needs and requirements is important.

Introduction: Miniaturisation and development of mobile devices led to accelerometers being literally everywhere. The way we are moving seems intuitively very personal, resulting in increased interest in the possibility of accelerometer-based authorisation. We present results of an experiment based on data from the "Wearables in Arthritis" project. Aims: The main aim of this work was to assess if it is possible to identify participants based on data from a single accelerometer. Methods: Participants' accelerometer data were collected during clapping and walking. We trained models using k-nearest neighbours (KNN), naïve Bayes (NB), random forest (RF), extreme gradient boosting (xgboost – XGB), and single-hidden-layer neural network (NNET) algorithms. We analysed data separately from clapping and walking, and both together. The most effective algorithm was RF on clapping data, with an accuracy of 0.992. We examined the effect av "imposter" data from participants not used in training. The performance was lower but still acceptable, with an accuracy between 0.860-0.929, depending on the probability threshold. Conclusions: The results show the potential of accelerometer data for biometric authorisation but also raise concerns about data privacy.

Integration of management information systems is crucial to optimizing internal and external processes in enterprises' environments. One of the technologies sup-porting this integration is OPC UA. An embedded automation device OPC UA server can transmit either dead-band tested analog attributes or all changes of ana-log attributes to OPC UA clients. Typically OPC UA server to OPC UA client data transmission is based on subscriptions. Subscription interval, sampling interval, and dead-band are usually controlled by OPC UA clients [1]. It is, however, desirable that OPC UA data traffic is controlled by automation de-vice control programs and the embedded OPC UA servers and not by OPC UA clients as specified in the norm. This is because the OPC UA server is the limiting component in the client sever communication scheme. Floating-point attributes in an automation device have small changes all the time, but in real-world plants, analog attributes do not necessarily have to be frequently communicated to OPC UA clients on small changes. In addition to an attribute dead-band test, changes in some attributes can safely be blocked a minimum time since the last attribute update before a new value is transmitted to the UA clients. Analog attributes can also be cyclically transmitted to OPC UA clients with a low frequency to ensure that they receive the exact attribute value after a set maximum time. This paper demonstrates an implementation of this communication scheme by using a device function block to control traffic between an OPC UA server and OPC UA clients for analog attributes.

Medical internet of things leads to revolutionary improvements in medical services, also known as smart healthcare. With the big healthcare data, data mining and machine learning can assist wellness management and intelligent diagnosis, and achieve the P4-medicine. However, healthcare data has high sparsity and heterogeneity. In this paper, we propose a Heterogeneous Transferring Prediction System (HTPS). Feature engineering mechanism transforms the dataset into sparse and dense feature matrices, and autoencoders in the embedding networks not only embed features but also transfer knowledge from heterogeneous datasets. Experimental results show that the proposed HTPS outperforms the benchmark systems on various prediction tasks and datasets, and ablation studies present the effectiveness of each designed mechanism. Experimental results demonstrate the negative impact of heterogeneous data on benchmark systems and the high transferability of the proposed HTPS.

Modern industrial systems require more and more flexibility and mobility; furthermore the quantity of data generated by them is great. In some cases, classical wired networks are not feasible due to the type of device itself (e.g., AGV) or its location. In such cases wireless communication is the only solution. The then, the choice of appropriate communication protocol, especially in an industrial system, is crucial. The paper presents an approach of using a wireless connection in EtherCAT network, which in principle is a wired solution. Therefore, for wireless communication upper layer protocol has to be implemented. Here, Software Defined Networks SDN technology is used. SDN allows for dynamic and programmable infrastructure management and monitoring of network traffic. The proposed solution was compared in terms of performance to a standard wired connection. To do this research and confirm the theoretical assumptions industrial devices like PLC controllers, remote IO stations and servo drives were used. The paper shows limitations resulting from this type of communication and the possibility to reduce their significance.

In this research, we proposed a practical shelf space allocation model with the vertical and horizontal categorization of products. Five groups of constraints, such as shelf, product, multi-shelves, orientation and band constraints, are implemented in the model. We proposed two heuristics to solve the retailer's profit maximization problem. The experiments were performed on small instances, and the solution was compared to the optimal solution found by the CPLEX solver. The experiments proved that heuristics could find the optimal solution in most cases (14/20 for heuristics H1 and 16/20 for heuristics H2) without checking the whole solutions space. The lowest solution quality is 97.68% which shows that the heuristics allow finding high-quality near-optimal solutions. Therefore the steps implemented in the proposed heuristics should be used in more complicated shelf space allocation problems for which it is impossible to find a solution by the solvers.

The new manufacturing paradigm, which is organized under Industry 4.0, has strict requirements for supporting technologies. Wireless communication technology should be available to support movable nodes and to make a production site flexible and able to adapt to the various requirements of the manufacturing operations and the production management systems. Depending on the application and processes being serviced, communication is subject to a broad range of strict requirements, from reliability and predictable delays to low cost and reduced energy consumption. In this paper, we present a real scenario in which Autonomous Guided Vehicles (AGVs) equipped with Collaborative robots (Cobots) are used as transportation and production units, and therefore, a set of communication services must be implemented. The challenges associated with moving AGVs are discussed, and the associated requirements that apply to wireless communication are presented. The results allow to formulate a definition of a three-level hierarchy for communication services (onboard, shopfloor, and system) that are required to implement the Industry 4.0 paradigm. In addition, a review of the relevant wireless network protocols that can be used for the implementation of communication services is presented.

Ongoing changes in manufacturing, and in particular the growing importance of internal logistics based on Autonomous Guided Vehicles (AGV), makes the use of wireless communication in the industry no longer an option but a necessity. Wireless communication offers including lower installation costs than wired networks, less mechanical wear and tear, and the ability to provide crucial information even with moving AGVs. Robust and reliable wireless communication solutions must accommodate the demanding and changing conditions of the existing industrial environment, such as a variable number of communication elements, possible interference, a large area for which to provide communication, and an organic amount of available battery power. Several types of such communications are available and in use in manufacturing systems. For this reason, AGVs operating in a heterogeneous manufacturing environment must support a different kind of wireless communication and use them in an optimal way for the tasks performed. The aim of this paper is to analyze the different types of sensor networks and the requirements for communication with autonomous vehicles that they fulfill.

This work-in-progress paper describes our experience in introduction of a Project-Based Learning environment in teaching of undergraduate students in the field of electrical engineering at Sogn og Fjordane University College in Norway. In the scope of this work, a robot capable of playing the tic-tac-toe game with a human and an additional laboratory exercise in robotic manipulation with computer vision has been developed. In this lab, the students integrated the robotic manipulator with computer vision in order to prepare a fully autonomous robot navigation using a prepared library that provides the functions for robot control and image processing. The project can be an interesting tool for learning some advanced topics such as robot vision, robot mechanics and autonomous robot navigation. The results show that students with strong motivation start to carry out an advanced project without any theoretical background in robotics and image processing. Another advantage is that the students can test in practice the influence of all stages of image processing on final robot navigation and understand that we may control robotic manipulators by using the vision information.