Energy harvesting (EH) is a rapidly evolving domain that is primarily focused on capturing and converting ambient energy sources into more convenient and usable forms. These sources, which range from traditional renewable sources such as solar or wind power to thermal gradients and vibrations, present an alternative to typical power generation. The temptation to use energy harvesting systems is in their potential to power low-power devices, such as environment monitoring devices, without relying on conventional power grids or standard battery implementations. This improves the sustainability and self-sufficiency of IoT devices and reduces the environmental impact of conventional power systems. Applications of EH include wearable health monitors, wireless sensor networks, and remote structural sensors, where frequent battery replacement is impractical. However, these systems also face challenges such as intermittent energy availability, limited storage capacity, and low power density, which require innovative design approaches and efficient energy management. The paper provides a general overview of the subsystems present in the energy harvesting systems and a comprehensive overview of the energy transducer technologies used in energy harvesting systems.

The Over-the-air update mechanism is really important for managing and maintaining the firmware of Internet of Things devices deployed in the field. This paper explores the implementation of over-the-air updates for ESP32 microcontrollers using the Espressif library, focusing on three distinct wireless communication protocols: Wi-Fi via HTTPS, Bluetooth Low Energy, and Zigbee. The study presents an approach to understand these protocols for firmware updates. We discuss the architecture and steps involved in configuring and executing over-the-air updates over Wi-Fi, which is the most commonly used protocol for such operations. Additionally, we explore the implementation of over-the-air updates via Bluetooth Low Energy, highlighting the constraints and advantages of this low-power communication method. Furthermore, the paper addresses over-the-air update strategies using Zigbee, a protocol tailored for low-power, mesh network environments, with concept of fully automated update system and fault detection algorithms for improving versioning system.

In this paper, we present BioLab, an educational and research application designed for real-time streaming and analysis of biomedical signals using the Lab Streaming Layer (LSL). BioLab facilitates the streaming, visualization, and storage of signals such as electrocardiography (ECG), electroencephalography (EEG) and electromyography (EMG), among others, from various biomedical devices, which can then be analyzed in real-time or post-acquisition. We have developed specific scripts for ECG and EMG data acquisition, along with MATLAB scripts to plot, visualize, and filter the received signals. The system's configuration is easily adjustable through JSON configuration files, allowing flexibility in the stream settings. While our current focus is on real-time visualization and basic noise filtering, we discuss the potential for future classification of cardiovascular diseases based on the spectrograms generated from the streamed ECG data. This platform aims to serve as an essential tool for researchers and educators in the field of biomedical engineering, providing a flexible environment for the analysis of both raw and processed biosignal data.

Myoelectric signals are physiological indicators in various biomedical applications. These signals brings information about muscle contractions, providing motor control, muscle function, and user intent. In most of applications is myoelectric signal analysis provided on single-channel devices or commercial expensive armbands. In case of myoelectric signals research without owning device, we experience lack of useful datasets, in most of cases poorly defined measurement conditions. In this paper we present the development of cheaper 6-channel wearable band for monitoring myoelectric signals, useful for research and education purpose. Band provides real-time stream to the collecting device using Bluetooth Low Energy protocol for advanced analysis and interconnection with brain-computer interface.

This paper examines the development and integration of a 3D printing course into the educational curriculum. The increasing accessibility, affordability, and user-friendliness of 3D printing technology have made it widely available. In 2019, a 3D printing course was introduced at the Faculty of Management Science and Informatics, designed to be open to students from all academic disciplines. The course allows students to transform an idea into a tangible object through CAD software and modeling completing the process in a single session. The course's popularity has led to increased student engagement and attendance. The paper discusses the selection of appropriate technical equipment for the laboratory, focusing on student safety and printer reliability. It also outlines key aspects of the course syllabus, highlighting the choice of FFF (Fused Filament Fabrication) technology. Additionally, various student projects are mentioned to illustrate the practical application of the course content. The paper advocates for incorporating 3D printing into educational programs across schools.

Article focus on the course Development of embedded systems handled by the the Department of Technical Cybernetics at Faculty of Management Science and Informatics, University of Zilina. Course introduces students to embeddedˇ systems programming with a focus on interfacing with hardware peripherals and preparing for wider overview for final thesis in Computer Engineering degree. Using platforms like the ESP32, students gain experience in implementation of IoT applications, including use of various sensors and actuators. The course emphasizes practical skills in integrating hardware components, while also introducing the concept of wireless communication and embedded systems.