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 paper presents the implementation of an Apache Spark distributed computing cluster based on Raspberry Pi microcomputers. The solution consists of three Raspberry Pi 4 devices (one master node and two worker nodes), each equipped with 8 GB of RAM and a high-speed network connection. The cluster configuration was optimized by adjusting the SPARK_WORKER_MEMORY and SPARK_WORKER_CORES parameters to maximize the use of available hardware resources. Secure communication between nodes was established through authentication using 4096-bit SSH keys.
This paper presents the analysis and development of a smart noise information collection system utilizing the Spectrum Analyzer SVAN 958A to enhance real-time noise monitoring and data analysis. The study addresses the limitations of traditional noise measurement tools, which often lack real-time processing and comprehensive integration with modern data management platforms.
The paper presents the development of a cyber-physical system based on the HomeAssistant platform for efficient automation and control of Internet of Things (IoT) devices. The architectural features, technical implementation and prospects for the development of the system are considered, with an emphasis on the ability to integrate a wide range of sensors and IoT devices into a single network to create adaptive and intelligent solutions.