This paper presents the development and inves- tigation of a speech-to-text conversion and speaker identi- fication system based on a Raspberry Pi microcomputer, designed for local audio data processing in environments with limited network connectivity. The system integrates Silero and WebRTC models for voice activity detection, SpeechBrain for speaker identification, and the Whisper family of models for speech recognition.
The article focuses on innovative measurement and control methods in electrical power engineering, specifically addressing challenges of power quality, signal diagnostics, and automation within smart grids. Emphasis is placed on wavelet analysis, smart metering, IoT integration, and automated control systems. These technologies are examined in the context of enhancing the adaptability and efficiency of modern electrical systems in line with Industry 4.0 requirements.
The rapid expansion of the Internet of Things (IoT) has resulted in a substantial increase of diverse data from distributed devices. This extensive data stream makes it increasingly important to implement robust and efficient real-time anomaly detection techniques that can promptly alert about issues before they could escalate into critical system failures.
The article is devoted to the development of an automated care system for indoor plants based on the use of an Arduino microcontroller and IoT technologies. The system contains soil moisture, temperature, and light sensors that monitor the main environmental parameters for effective plant care. The structural and schematic diagrams and algorithm of the system were developed. A prototype of the system was implemented. The prototype of the system was tested in real conditions, which confirmed the correctness of the decisions made, as well as the efficiency and usability of the system.
This paper presents the development of a web-based application for controlling smart curtains using IoT technology. The system is designed to provide a secure and efficient method for managing curtain movements remotely via a web interface.
In the food and beverage industry, maintaining optimal temperature conditions is crucial for ensuring product quality and safety. The advent of the Internet of Things (IoT) has enabled real-time temperature monitoring through sensor networks, providing a wealth of data that can be harnessed for predictive analytics. This study presents a robust method for analyzing and forecasting IoT temperature data, specifically tailored to the operational dynamics of the food and beverage sector.
The article presents a method for optimizing the algorithm flow graph of a deep neural network to reduce the number of processor elements (PE) required for executing the algorithm on single-board computers. The proposed approach is based on the use of a structural matrix to optimize the neural network architecture without loss of performance. The research demonstrated that by reducing the width of the graph, the number of processor elements was reduced from 3 to 2, while maintaining network performance at 75% efficiency.
This study provides a comprehensive overview of the various means and methods employed in gathering data, emphasizing the need for advanced technologies in the face of increasing energy demands and evolving regulatory environments. A thorough comparative analysis focuses on several key aspects, including technology comparison, data accuracy and reliability, real-time data collection capabilities, cost effectiveness, scalability, and flexibility, consumer interaction, and feedback mecha- nisms.
Timely detection and prevention of agriculture vehicles malfunctions are key approaches to reducing maintenance costs, as well as updating and replacing equipment, and reducing the cost of growing agricultural crops. In this article an approach for Remaining Useful Life (RUL) prediction that utilizes a combination of telemetry, maintenance, and geospatial data (such as weather and terrain information) as input to a Long Short- Term Memory (LSTM) algorithm has been considered.
The object of the research is the security of the file system of a single-board platform. As part of the research reported in this paper, a method has been proposed to protect the file system using encryption. Implementing a Linux Unified Key Setup paired with a password or Universal Serial Bus key has been demonstrated. The advantages of Linux Unified Key Setup for this task and the possibilities for system configuration and encryption method depending on the use case and hardware configuration has been outlined.