Перегляд за Автор "Mogylevych, Dmytro"

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    Innovative methods of automotive crash detection through audio recognition using neural networks algorithms
    (Institute of Special Communication and Information Protection of National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, 2024) Mogylevych, Dmytro; Khmil, Roman
    The automatic e-Call system has become mandatory in the European Union since 2018. This requirement means that all new passenger vehicles released on the European market after this date must be equipped with a digital emergency response service, which automatically notifies emergency services in case of an accident through the Automatic Crash Notification (ACN) system. Since the response of emergency services (police, ambulance, etc.) to such calls is extremely expensive, the task arises of improving the accuracy of such reports by verifying the fact that the accident actually occurred. Nowadays, most car manufacturers determine an emergency by analyzing the information coming from the built-in accelerometer sensors. As a result, quite often sudden braking, which avoids an accident, is mistakenly identified as an emergency and leads to a false call to emergency services. Some car manufacturers equip their high-end vehicles with an automatic collision notification, which mainly monitors the airbag deployment in order to detect a severe collision, and call assistance with the embedded cellular radios. In order to reduce costs some third-party solutions offer the installation of boxes under the hood, wind-screen boxes and/or OBDII dongles with an embedded acceleration sensor, a third-party simcard as well as a proprietary algorithm to detect bumps. Nevertheless, relying on acceleration data may lead to false predictions: street bumps, holes and bad street conditions trigger false positives, whereas collisions coming from the back while standing still may be classified as normal acceleration. Also acceleration data is not suitable to identify vehicle side impacts. In many cases emergency braking helps to avoid collision, while acceleration data would be very similar to the data observed in case of an accident, resulting in a conclusion that the crash actually occurred. As a result, the average accuracy of those car crash detection algorithms nowadays does not exceed 85% , which is acceptable, yet offers a lot of room for further improvement, since each additional percept of accuracy would provide substantial cost savings. That is why the task of increasing accuracy of collision detection stays urgent. In this article, we will describe an innovative approach to the recognition of car accidents based on the use of convolutional neural networks to classify soundtracks recorded inside the car when road accidents occur, assuming that every crash produces a sound. Recording of the soundtrack inside the car can be implemented both with the help of built-in microphones as well as using the driver's smartphone, hands-free car kits, dash cameras, which would drastically reduce cost of hardware required to solve this task. Also, modern smartphones are equipped with accelerometers, which can serve as a trigger for starting the analysis of the soundtrack using a neural network, which will save the computing resources of the smartphone. Accuracy of the crash detection can be further improved by using multiple sound sources. Modern automobiles may be equipped with various devices capable of recording the audio inside the car, namely: built-in microphone of the hands-free speaking system, mobile phones of the driver and/or passengers, dash-cam recording devices, smart back-view mirrors etc.
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    Soft frequency reuse for miligation of intercelluler intereference
    (National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", 2022) Papushoi, Olha; Mogylevych, Dmytro
    Background. The appearance of femtocells in LTE networks has provided indoor coverage and overcome large data flows for operators. However, strong interference occurs in neighbouring femtocell users due to the limited available spectrum in cellular networks that transmit data in the same radio range. In densely deployed environments, interference issues in single channel femtocells cause significant performance degradation. In this study, we mitigate inter-cell interference in femtocell networks by combining femtocells as a result of common interference and soft frequency reuse in downlink and uplink by moving and exchanging interfering physical blocks. Objective. The purpose of the paper is to improve the efficiency of ensuring the quality of services in wireless networks by reducing any interference due to the distribution of traffic, which is able to provide uninterrupted connection to the user. Methods. Enabling conditions for inter-cell interference mitigation in LTE-based femtocell networks with soft frequency reuse. Results. Interference is a key issue in the deployment of LTE femtocells. Closely located femtocells interfere with each other if they transmit on the same frequency. Therefore, crossing femtocells and enabling them to allocate resources and reuse soft frequencies effectively reduces interference and prevents the loss of network resources. The scheme is triggered whenever the user's femto equipment experiences strong interference from neighbouring femtocells. By assigning a separate set of physical resource blocks to users at the edge of the cell, our scheme significantly reduces interference, which automatically increases cell throughput. The simulation results show the advantages of applying our scheme, in particular, the interference of the user's femto-equipment is reduced by 14% and the throughput is improved by 25%. That is, we observe a significant improvement in the performance of femtocells. Conclusions. A femtocell crossing scheme with soft frequency reuse is presented to reduce interference between femtocells of LTE networks, which allows effectively ensuring the quality of service transmission in wireless networks by reducing interference and increasing performance through traffic distribution.
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    Оценка показателей качества технического обслуживания систем непрерывного использования с временным резервом при известных начальных моментах распределения наработки до отказа
    (НТУУ "КПІ", 2012) Могилевич, Дмитрий; Креденцер, Борис; Вишневский, Виктор; Могилевич, Дмитро; Креденцер, Борис; Вишнівський, Віктор; Mogylevych, Dmytro; Kredentser, Borys; Vyshnivsky, Vyctor