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Computers, Materials & Continua 2022年第6期71卷 4659-4676页

作者： Radek Martinek Jan Baros Rene Jaros lukas danys Jan Nedoma VSB-Technical University of Ostrava Faculty of Electrical Engineering and Computer ScienceDepartment of Cybernetics and Biomedical Engineering70800Ostrava-PorubaCzechia VSB Technical University of Ostrava Faculty of Electrical Engineering and Computer ScienceDepartment of Telecommunications70800Ostrava-PorubaCzechia

This pilot study focuses on employment of hybrid LMS-ICA system for in-vehicle background noise *** vehicles are nowadays increasingly supporting voice commands,which are one of the pillars of autonomous and SMART *** speaker recognition for context-aware in-vehicle applications is limited to a certain extent by in-vehicle back-ground *** article presents the new concept of a hybrid system which is implemented as a virtual *** highly modular concept of the virtual car used in combination with real recordings of various driving scenarios enables effective testing of the investigated methods of in-vehicle background noise *** study also presents a unique concept of an adaptive system using intelligent clusters of distributed next generation 5G data networks,which allows the exchange of interference information and/or optimal hybrid algorithm settings between individual *** average,the unfiltered voice commands were successfully recognized in 29.34%of all scenarios,while the LMS reached up to 71.81%,and LMS-ICA hybrid improved the performance further to 73.03%.

关键词： 5G noise reduction hybrid algorithms speech recognition 5G data networks in-vehicle background noise

Enhancements of SDR-Based FPGA System for V2X-VLC Communications

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Computers, Materials & Continua 2021年第9期68卷 3629-3652页

作者： lukas danys Radek Martinek Rene Jaros Jan Baros Petr Simonik Vaclav Snasel Department of Cybernetics and Biomedical Engineering Faculty of Electrical Engineering and Computer ScienceVSB–Technical University of OstravaOstrava-Poruba70800Czechia Department of Electronics Faculty of Electrical Engineering and Computer ScienceVSB–Technical University of OstravaOstrava-Poruba70800Czechia Department of Computer Science Faculty of Electrical Engineering and Computer ScienceVSB–Technical University of OstravaOstrava-Poruba70800Czechia

This pilot study focuses on a real measurements and enhancements of a software defined radio-based system for vehicle-to everything visible light communication(SDR-V2X-VLC).The presented system is based on a novel adaptive optimization of the feed-forward software defined equalization(FFSDE)methods of the least mean squares(LMS),normalized LMS(NLMS)and QR decomposition-based recursive least squares(QR-RLS)*** parameters of adaptive equalizations are adjusted in real-time to reach the best possible *** were carried out on a conventional LED Octavia III taillight drafted directly from production line and universal software radio peripherals(USRP)from National *** transmitting/receiving elements used multistate quadrature amplitude modulation(M-QAM)implemented in LabVIEW programming *** results were verified based on bit error ratio(BER),error vector magnitude(EVM)and modulation error ratio(MER).Experimental results of the pilot study unambiguously confirmed the effectiveness of the proposed solution(longer effective communication range,higher immunity to interference,deployment of higher state QAM modulation formats,higher transmission speeds etc.),as the adaptive equalization significantly improved BER,MER and EVM *** best results were achieved using the QR-RLS *** results measured on deployed QR-RLS algorithm had significantly better Eb/N0(improved by approx.20 dB)and BER values(difference by up to two orders of magnitude).

关键词： 5G feed-forward software defined equalization multistate quadrature amplitude modulation software defined radio visible light communication

Noise Reduction in Industry Based on Virtual Instrumentation

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Computers, Materials & Continua 2021年第10期69卷 1073-1096页

作者： Radek Martinek Rene Jaros Jan Baros lukas danys Aleksandra Kawala-Sterniuk Jan Nedoma Zdenek Machacek Jiri Koziorek Faculty of Electrical Engineering and Computer Science Department of Cybernetics and Biomedical EngineeringVSB–Technical University of Ostrava70800Ostrava-PorubaCzechia Faculty of Electrical Engineering Automatic Control and InformaticsOpole University of TechnologyOpolePoland Faculty of Electrical Engineering and Computer Science Department of TelecommunicationsVSB–Technical University of Ostrava70800Ostrava-PorubaCzechia

This paper discusses the reduction of background noise in an industrial environment to extend *** the Industry 4.0 era,the mass development of voice control(speech recognition)in various industrial applications is possible,especially as related to augmented reality(such as hands-free control via voice commands).As Industry 4.0 relies heavily on radiofrequency technologies,some brief insight into this problem is provided,including the Internet of things(IoT)and 5G *** study was carried out in cooperation with the industrial partner Brose CZ spol.s.r.o.,where sound recordings were made to produce a *** experimental environment comprised three workplaces with background noise above 100 dB,consisting of a laser/magnetic welder and a press.A virtual device was developed from a given dataset in order to test selected commands from a commercial speech recognizer from *** tested a hybrid algorithm for noise reduction and its impact on voice command recognition *** virtual devices,the study was carried out on large speakers with 20 participants(10 men and 10 women).The experiments included a large number of repetitions(100 times for each command under different noise conditions).Statistical results confirmed the efficiency of the tested *** welding environment efficiency was 27%before applied filtering,76%using the least mean square(LMS)algorithm,and 79%using LMS+independent component analysis(ICA).Magnetic welding environment efficiency was 24%before applied filtering,70%with LMS,and 75%with LMS+*** workplace environment efficiency showed no success before applied filtering,was 52%with LMS,and was 54%with LMS+ICA.

关键词： 5G hybrid algorithms signal processing speech recognition

New Hybrid IoT LoRaWAN/IRC Sensors:SMARTWater Metering System

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Computers, Materials & Continua 2022年第6期71卷 5201-5217页

作者： Vlastimil Slany Petr Koudelka Eva Krcalova Jan Jobbagy lukas danys Rene Jaros Zdenek Slanina Michal Prauzek Radek Martinek Mendel University in Brno Faculty of AgrisciencesDepartment of AgriculturalFood and Environmental Engineering61300BrnoCzechia Slovak University of Agriculture in Nitra Faculty of EngineeringDepartment of Machines and Production Biosystems94976NitraSlovakia VSB-Technical University of Ostrava Faculty of Electrical Engineering and Computer ScienceDepartment of Cybernetics and Biomedical Engineering70800Ostrava-PorubaCzechia

The massive development of internet of things(IoT)technologies is gaining momentum across all areas of their possible deployment—spanning from Industry 4.0 to eHealth,smart city,agriculture or waste *** ongoing development is further pushed forward by the gradual deployment of 5G *** 5G capable smart devices,it will be possible to transfer more data with shorter latency thereby resulting in exciting new use cases such as Massive ***-IoT(low-power wide area network-LPWAN)enables improved network coverage,long device operational lifetime and a high density of *** all the advantages of massive-IoT technology,there are certain cases where the original concept cannot be *** them are dangerous explosive environments or issues caused by subsurface deployment(operation during winter months or dense greenery).This article presents the concept of a hybrid solution of IoT LoRaWAN(long range wide area network)/IRC-VLC(infrared communication,visible light communication)technology,which combines advantages of both technologies according to the deployment scenario.

关键词： IRC/VLC LoRaWAN LPWAN massive IoT smart metering