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calendar23 октябр 2025
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YO‘L-TRANSPORT HODISALARINING OLDINI OLISH UCHUN REAL VAQT REJIMIDA ALKOGOLNI ANIQLASH VA DVIGATELNI BLOKLASH TIZIMI

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MAQOLA ANNOTATSIYASI

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Mazkur loyiha bitiruv ishi sifatida amalga oshirilib, alkogol ta’siriostida transport vositasini boshqarishdan kelib chiqadigan yo‘l-transport hodisalari va zararni kamaytirishga qaratilgan. Tizim Arduino Uno3 mikrokontrolleri asosida ishlab chiqilgan bo‘lib, u haydovchi nafasidan namunani tahlil qiluvchi alkogol sensori bilan bog‘langan. Agar alkogol aniqlansa, avtomobil dvigateli avtomatik ravishda o‘chiriladi hamda atrofdagilarni ogohlantirish va xavfning oldini olish maqsadida favqulodda signal beriladi. Alkogol sensori rulga joylashtirilgan bo‘lib, belgilangan me’yordan yuqori darajada aniqlanganda, yondirish (зажигание) tizimi bloklanadi. Arduino sensor ma’lumotlarini uzluksiz nazorat qiladi va dvigatelni ishga tushirishga yo‘l qo‘ymaydigan blokirovka mexanizmini faollashtiradi. Bu esa avariya, jarohatlar va moddiy zararlar xavfini kamaytirishga xizmat qiladi.

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Teglar

# Arduino Uno# alcohol detection# MQ3 Sensor# Engine Locking# Vehicle safety system# Microcontroller-based control.# alkogolni aniqlash# MQ3 sensori# dvigatelni bloklash# transport xavfsizligi tizimi# mikrokontroller asosida boshqari# определение алкоголя# датчик MQ3# блокировка двигателя# система безопасности транспортно# управление на основе микроконтро

Maqolani baholang

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Maqola idintifikatorlari

Foydalanilgan adabiyotlar

Babor, T. F. (1992). AUDIT: The alcohol use disorders identification test: Guidelines for use in primary health care. World Health Organization.

Dhivya, M., & Kathiravan, S. (2015). Driver authentication and accident-avoidance system for vehicles. Smart Computing Review, 5(1), 201–206.

Karne, R., & Sreeja, T. K. (2021a). COINV—Chances and obstacles interpretation to carry new approaches in the VANET communications. Design Engineering, 2021, 10346–10361.

Karne, R., & Sreeja, T. K. (2021b). Review on VANET architecture and applications. Turkish Journal of Computer and Mathematics Education, 12(4), 1745–1749.

Karne, R., & Sreeja, T. K. (2022). Routing protocols in vehicular ad hoc networks (VANETs). International Journal of Early Childhood, 14(3), 255–263.

Karne, R., et al. (2021a). Genetic algorithm for wireless sensor networks. International Journal of Computer Science and Network Security, 21(5), 91–97.

Karne, R., et al. (2021b). Optimization of WSN using honey bee algorithm. Unpublished manuscript.

Karne, R., et al. (2021c). Simulation of ACO for shortest path finding using NS2. International Journal of Advanced Computer Science and Applications, 12(6), 12866–12873.

Navarro, L. A., Dino, M. A., Jason, E., Anacan, R., & Cruz, R. D. (2016). Design of alcohol detection system for car users through iris recognition pattern using wavelet transform. In 2016 7th International Conference on Intelligent Systems, Modelling and Simulation (ISMS) (pp. 15–19). IEEE. https://doi.org/10.1109/ISMS.2016.11

Sujith, A. V. L. N., Swathi, R., Venkatasubramanian, R., Venu, N., Hemalatha, S., George, T., Hemlathadhevi, A., Madhu, P., Karthick, A., Muhibbullah, M., & Osman, S. M. (2022). Integrating nanomaterial and high-performance fuzzy-based machine learning approach for green energy conversion. Journal of Nanomaterials, 2022, 1–11.

Vaigandla, K. K., & Venu, N. (2021a). Survey on massive MIMO: Technology, challenges, opportunities and benefits. YMER, 20(11), 271–282.

Vaigandla, K. K., & Venu, N. (2021b). A survey on future generation wireless communications— 5G: Multiple access techniques, physical layer security, beamforming approach. Journal of Information and Computational Science, 11(9), 449–474.

Vaigandla, K. K., & Venu, N. (2021c). BER, SNR and PAPR analysis of OFDMA and SC-FDMA. GIS Science Journal, 8(9), 970–977.

Venu, N. (2015). Analysis of Xtrinsic sense MEMS sensors. International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, 4(8), 7228–7234.

Venu, N., & Arun Kumar, A. (2021). Comparison of traditional method with watershed threshold segmentation technique. International Journal of Analytical and Experimental Analysis, 13(1), 181–187.

Venu, N., & Sulthana, A. (2018a). Local mesh patterns for medical image segmentation. Asian Pacific Journal of Health Sciences, 5(1), 123–127.

Venu, N., & Sulthana, A. (2018b). Local maximum edge binary patterns for medical image segmentation. International Journal of Engineering and Techniques, 4(1), 504–509.

Venu, N., ArunKumar, A., & Vaigandla, K. K. (2022a). Review of Internet of Things (IoT) for future generation wireless communications. International Journal for Modern Trends in Science and Technology, 8(3), 1–8.

Venu, N., Swathi, R., Sarangi, S. K., Subashini, V., Arulkumar, D., Ralhan, S., & Debtera, B. (2022c). Optimization of hello message broadcasting prediction model for stability analysis. Wireless Communications and Mobile Computing, 2022, 1–9.

Venu, N., Vaigandla, K. K., & ArunKumar, A. (2022d). Investigations of Internet of Things (IoT): Technologies, challenges and applications in healthcare. International Journal of Research, 11(2), 143–153.

Venu, N., Yuvaraj, D., Glady, J. B. P., Pattnaik, O., Singh, G., Singh, M., & Adigo, A. G. (2022b). Execution of multitarget node selection scheme for target position alteration monitoring in MANET. Wireless Communications and Mobile Computing, 2022, 1–9.

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