This paper presents the development of an advanced non-invasive inspection system utilizing beamforming technology, specifically designed for detecting and characterizing defects across various materials. The device employs sophisticated algorithms to enhance both the precision and resolution of non-invasive examinations. Additionally, the system incorporates 3D reconstruction capabilities, providing improved visualization of detected anomalies. A comparative analysis with current market solutions further validates the superior diagnostic performance and potential applications of this innovative technology in sectors such as aerospace engineering, construction, and manufacturing, where accurate defect detection is paramount.

The article discusses research on a wearable medical diagnostic system using electrical impedance tomography. This system aims to diagnose long-term respiratory diseases, particularly COPD, ARDS, pneumothorax, pneumonia, bron-chospasm, and pulmonary hypertension. It seeks to reduce the number of tests needed for accurate diagnoses, thus saving time. The article compares two classification models for distinguishing between diseased and healthy individuals. This approach helps streamline the diagnostic process.

This paper presents novel diagnostic system for medicine, based on electrical impedance tomography (EIT). One of the primary functional features of this system is its ability to detect respiratory diseases with high accuracy, particularly focusing on conditions such as Chronic Obstructive Pulmonary Disease (COPD), Acute Respiratory Distress Syndrome (ARDS), Pneumothorax (PTX), Pulmonary Hypertension (PHTN), Pneumonia (PNA), and bronchospasm. A comparison of several classification models is presented, with the best-performing model achieving an accuracy rate of 98.22% in distinguishing between healthy and diseased patients.