As unmanned aerial vehicles (UAVs) are increasingly employed across various industries, the demand for robust and accurate detection has become crucial. Light detection and ranging (LiDAR) has developed as a vital sensor technology due to its ability to provide rich 3D spatial information, particularly in applications such as security and airspace monitoring. This review systematically explores recent innovations in LiDAR-based drone detection, deeply focusing on the principles and components of LiDAR sensors, their classifications based on different parameters and scanning mechanisms, and the approaches for processing LiDAR data. The review briefly compares recent research works in LiDAR-based only and its fusion with other sensor modalities, the real-world applications of LiDAR with deep learning, as well as the major challenges in sensor fusion-based UAV detection.

Purpose. The primary objective of this research is to develop a technology for achieving water quality at the level of Maximum Permissible Concentrations (MPC) required by sanitary regulations and norms. Methods. To meet these regulatory requirements, experimental studies were conducted to analyze the chemical and microbiological composition of water, focusing on parameters such as the total microbial count (quantity/ml), coliform bacteria (quantity/ml), coliphages (quantity/100 ml), clostridia (cl/20 ml), and other harmful substances. The research also examined water disinfection processes depending on the autumn and winter seasons of the year. Findings. To assess the device’s effectiveness, the research determined the optimal ozone concentration and contact time in the disinfection chamber. The findings indicate that 0.6 grams per hour (G = 0.6 g/hour) of ozone (O3) per cubic meter of surface water is sufficient for the removal of harmful microbiological substances. Originality. The primary innovation in this research lies in the establishment of parameters for an ozone generator utilizing a novel corona discharge method. The study introduces both theoretical frameworks and practical methodologies for effectively disinfecting surface waters using this innovative technique. Practical implications. This case study offers insights that can be applied and replicated in regions facing similar water quality challenges.

The object of the study is the process of radio signal delay and direction estimation using digital spectral-correlation analysis enhanced by machine learning. This process is essential for high-accuracy direction finding in electromagnetic monitoring systems. The problem addressed is the low adaptability and insufficient accuracy of traditional direction finding methods under variable signal conditions, especially due to manual parameter selection and the computational complexity of correlation processing. The essence of the obtained results is a machine learning-based method for predicting radio signal parameters (delay and angle), which reduced the standard deviation of direction finding estimates to 0.08–0.026° and delay estimation error to 1.5–14.8 μs across a signal-to-noise ratio range of 9 to 37 dB. These results are supported by averaging over 1000 realizations using Monte Carlo simulation, confirming their stability under noise. Due to its distinctive features, the proposed solution addressed the problem by enabling automated selection of processing parameters through a trained neural network that adapts to nonlinear signal characteristics, minimizing the need for manual adjustment or exhaustive search. These results are explained by the model’s ability to identify hidden dependencies between signal parameters and processing outcomes, enabling adaptive behavior and reduced deviations. Although no computational complexity assessment is provided, prediction-based parameter estimation is expected to improve processing speed in future implementations. The results can be applied in real-time electromagnetic monitoring, radio surveillance, and defense applications, especially under limited computing resources or varying noise conditions

The results of applications of various methods for measuring the parameters of high-speed loading using a strain gauge, a fiber Bragg grating located on a metal measuring rod and an interferometer monitoring the movement of the free boundary of the end of the rod are presented. Numerical simulation confirmed the adequacy of the description of the shock-wave process according to experimental data and showed that, with the thickness of the adhesive layer fixing the fiber Bragg grating and the strain gauge on a dimensional rod up to 100 µm, the deformation parameters of the sensors correspond to the parameters of the stress–strain state of the rod. Experimentally, a good correspondence of the results of measuring the magnitude of the relative deformation at a pulse duration of 10–100 µs using sensors of various types is shown, and an estimate of the limit values of the measured values of the deformation wave parameters is given.

In this article, we discuss the scientific research we conducted to ensure information security on concrete structures using the fiber Bragg grating method. As a result, guided by the experiences of other researchers and their results in our studies, the main hazards were identified, and the influence of temperature and deformation sensors in concrete was studied. The work determines the dependence of temperature on the optical cable and its effect on concrete deformation. It also studies the change in the internal structure of the optical fiber when exposed to concrete, and in comparison, with non-concrete optical fiber. In the experimental chapter, conducted on laboratory bench, we consider and study the signal transmission structure of an optical sensor that experiences deformation upon impact with concrete and such fibers. Graphic data was obtained using the OptiSystem program. During the process of determining the optical power of the sensors, we discovered that the higher the vibration during signal transmission, the higher the power of the optical data acquisition system unit. The results presented in this paper show the promise of fiber optics in other environments, as well as new discoveries in the construction industry and the successful use of electrical laser sensors to maintain temperature and stress in a variety of concrete structures, including cooling towers in nuclear and thermal power plants.

In this research work, practical work was carried out to determine the effectiveness of the installation of ETRO-02 ozonizer based on a corona discharge. To conduct experimental work in the research laboratory of the Department of ET and CT of KazNTU named after K. I. Satpayev, models of an ozonizer of various designs based on a small-sized electric discharge were developed. In addition, the physical and chemical properties of coronary electrodes are studied in practice using graphic images.