Sun’iy Intellekt va Raqamli Iqtisodiyot (SIRI 2025)

Sun’iy Intellekt va Raqamli Iqtisodiyot SIRI-2025 Masalan: Biz qo‘yida tugmaga oynaning 2 sahifasiga o‘tish buyrug‘ini yozdik va bu tugmani bosganimizda loyihaning ikkinchi sahifasiga o‘tiladi. 3-rasm. AutoPlay Media Studio dasturini 2 sahifasiga o‘tish buyrug‘ini. Foydalanuvchi loyihani to‘liq tayyorlagandan so‘ng, uni ishga tushirish uchun klaviaturadan F5 yoki asbolar panelidan qo‘yidagi belgini bosadi: 4-rasm. Loyihani ishga tushirish uchun. Natijada loyiha ishga tushadi. Shuni ta’kidlash kerakki loyiha doimo yuklanuvchi, ya’ni EXE formatida ishga tushadi. Loyihani saqlash uchun Fayl->Soxranit kak buyrug‘i bajariladi. Loyiha saqlanadigan alohida papka ko‘rsatiladi va dastur bu papkaga loyihada mavjud barcha qo‘shimcha fayllarni ham saqlaydi. Loyihaning ishga tushuvchi fayli papka ichidagi CD_Root papkasida autorun.exe fayli bo‘ladi[2]. Adabiyotlar 1. Ф.Закирова, У.Мухамедханов, Ш.Шарипов, Р.Исянов, Ф.Эсанбобоев, С.Доттоев, Электрон ўқув-методик мажмуалар ва таълим ресурсларини яратиш методикаси. Методик қўлланма. – Т.: ОЎМТВ, 2010. –64 б. 2. http://www.findsoft.ru/. AutoPlay Media Studio 7.0 – быстрое создание мультимедиа-приложений 861

SIRI-2025 Sun’iy Intellekt va Raqamli Iqtisodiyot IMLOVIY XATOLARNI TEKSHIRISHGA Mo‘LJALLANGAN INTERAKTIV DASTUR IMKONIYATLARI Raxmatova Kumushoy Navro‘z qizi TATU Samarqand filiali, raxmatova1kn@gmail.com Annotatsiya: Mazkur ishda, Windows operatsion uchun yaratilgan, maktab o‘quvchilari uchun ona tili va adabiyot darslarida imloviy xatolarni tekshirish hamda tuzatishda foydalanishga va mustaqil ta’limda o‘rganishga mo‘ljallangan dasturning imkoniyatlari keltirilgan. Kalit so‘zlar: Dikatant, imlo, xato, daraja, sinonim, hikoya, natija. Asosiy matn: Hozirgi kunda ish faoliyatida hamda ta’lim olishda kuzatilayotgan asosiy muammolardan biri hujjatlarni imloviy xatolarsiz tayyorlash hamda dars jarayonida ham imloviy xatolarsiz yozish masalasi bo‘lib qolmoqda. Ana shu va boshqa ayrim muammolarni hisobga olib foydalanuvchi lar ichun o‘z-o‘zini imloviy xatolarsiz yozishda sinab ko‘radigan hamda imloviy xatolarni tekshirishni avtomatlashtiruvchi dasturiy vosita yaratish masalasi yuzasidan ishning dolzarbligini anglab olish mumkin[1]. Dastur ishga tushirilgandan so‘ng dasturning bosh oynasi 1-rasmdagi kabi ishga tushadi. 1-rasm. Diktant.uz dasturining interfeysi. Bu dastur oynasi quyidagi bo‘limlardan iborat: Diktant – Diktant oynasini ishga tushirish tugamasi; Darslar – Imloviy xatolarni to‘g‘rilashga oid qonun-qoidalar to‘plami dars shaklida keltirilgan; Darajani tanlash – diktantni qiyinchilik darajasini tanlash oynasi; Familya – Foydalanuvchini Familiyasini ro‘yxatdan o‘tkazish oynasi; 862

Sun’iy Intellekt va Raqamli Iqtisodiyot SIRI-2025 Ism – Foydalanuvchini Ismini ro‘yxatdan o‘tkazish oynasi; Dastur haqida – dastur imkoniyatlari haqida ma’lumot berish oynasi; Dasturdan chiqish – dasturdan chiqish uchun foydalaniladigan tugma[1]. Dasturni ishga tushirish uchun dastavval foydalanuvchi o‘z ism-familiyasini kiritishi kerak bo‘ladi. Ism va familiya kiritilgandan so‘ng, oynada qo‘sjimcha “Tasdiqlash” tugmasi paydo bo‘ladi(2-rasm). “Tasdiqlash” tugmasini bosganimizdan so‘ng, oynadagi “Darajani tanlang” bo‘limi faollashadi(3-rasm). 3-rasm. Diktant.uz dasturining interfeysi 2-rasm. Diktant.uz dasturining interfeysi Bu oynadan hikoyalarning qiyinchilik darajasini tanlaymiz, shundan so‘ng, oynadagi “Diktant” tugmasini tanlaymiz va diktant topshirish oynasiga o‘tamiz(4-rasm). 4-rasm. Diktant topshirish oynasi. Diktant oynasi 6 ta bo‘limdan iborat bo‘lib, ular quyidagilardir: 1 – Diktant yozish uchun tanlangan hikoya; 2 – Hikoyaning muallifi va manbasi[2]; 863

SIRI-2025 Sun’iy Intellekt va Raqamli Iqtisodiyot 3 – o‘quvchi topishi uchun tushirib qoldirilgan harf yoki belgi o‘rni; 4 – Tushirib qoldirilgan harf yoki belgi uchun mos variantlar; 5 – Diktantni qaytadan boshlash tugmasi(agar hikoya ma’qul kelmasa); 6 – Dasturdan chiqish tugmasi. Bu dastruning mazmuni shundan iboratki o‘quvchi dastur oynasidagi hikoyada tushirib qoldirilgan harf yoki belgilarni o‘rniga oynaning pastki qismida keltirilgan variantlardan birini tanlab qo‘yadi. Yuqoridagi misolimizda hikoyada 13 ta belgi tushirib qoldirilgan shu belgilarni qo‘yib chiqish zarur bo‘ladi. Keltirilgan misollar aniq muallifili manbalar asosida keltirlgani uchun o‘quvchida dasturning to‘g‘ri ishlashiga shubha qoldirmaydi. Berilgan matndagi tushirib qoldirilgan barcha belgilarni qo‘yib chiqqanimizdan so‘ng, oyna quyidagicha ko‘rinishda bo‘ladi(5-rasm). 5-rasmdagi oynaning yuqori o‘ng tomonida “Tekshirish” tugmasi paydo bo‘ladi. Bu tugmani bosganimizdan so‘ng, navbatdagi oyna paydo bo‘ladi, u oynada hikoyadagi xatolarni ko‘rishimiz mumkin bo‘ladi(6-rasm). 6-rasm. Dasturining natijalar oynasi 5-rasm. Diktant oynasi Oynadagi “Keyingisi” tugmasini bosganimizdan so‘ng, navbatdagi hikoyaga o‘tamiz(7-rasm). Har bir qiyinchilik darajasiga 3 tadan hikoya qo‘yilgan. Barcha hikoyalarni o‘qib, tushirib qoldirilgan harflarni qo‘yib chiqqanimizdan so‘ng, “Umumiy natijlar” natijalar oynasi paydo bo‘ladi(8-rasm). 7-rasm. Navbatdagi hikoya oynasi 8-rasm. Natijalar oynasi 864

Sun’iy Intellekt va Raqamli Iqtisodiyot SIRI-2025 Bosh oynadagi “Darslar” bo‘limiga kirganimizdan so‘ng, quyidagi oynada keltirilgan mavzulashtirilgan qoidalar to‘plami oynasi ochiladi. Bu qoidalar to‘plamidan foydalanuvchi ixtiyoriy vaqtda foydalanishi mumkin bo‘ladi[3]. Adabiyotlar 1. Rafiyev A., G‘ulomova N. Ona tili va adabiyot: Akademik litsey va kasb-hunar kollejlari uchun darslik — T.: «Sharq», 2010.— 304 b. 2. Hoshimov o‘. Daftar hoshiyasidagi bitiklar: Hikoyalar to‘plami — T.: «Sharq», 2018. — 256 b. 3. http://totalstudy.ru. 865

SIRI-2025 Sun’iy Intellekt va Raqamli Iqtisodiyot THE EFFECT OF TECHNOLOGICAL INNOVATIONS ON GREEN DIGITAL ECONOMIES AND DEVELOPMENT STRATEGIES Mashkhura Azizjon kizi Joniuzoqova Karshi State University, mjoniuzoqova@gmail.com Abstract: The rapid advancement of technological innovations is reshaping the global economic landscape, driving a transition toward more sustainable and eco-friendly economic models. In recent years, green digital economies have emerged as a critical response to environmental challenges, ensuring both economic growth and sustainability. These economies leverage cutting-edge technologies such as artificial intelligence (AI), blockchain, and the Internet of Things (IoT) to enhance efficiency, reduce carbon footprints, and optimize resource management. This article explores the transformative impact of these innovations on green digital economies, highlighting their role in fostering sustainable development strategies. Additionally, the study examines policy implications, investment opportunities, and potential risks associated with the widespread adoption of these technologies. Governments and businesses are increasingly recognizing the need to integrate digital solutions into sustainability efforts, implementing smart grids, green fintech, and digital supply chain management systems to reduce environmental impact. The discussion also addresses challenges such as data security, regulatory frameworks, and technological accessibility, which may hinder large-scale adoption. By analyzing these factors, the study provides strategic recommendations for integrating technological innovations into green economic models to achieve long-term sustainability. As climate change and resource depletion accelerate, the shift toward green digital economic systems becomes increasingly imperative for a sustainable future. Keywords: Technological innovation, green economy, digital transformation, sustainability, economic development. Introduction The rapid evolution of digital technologies is reshaping economic and industrial landscapes worldwide. As climate change and environmental degradation pose increasing threats to global ecosystems, nations and businesses are searching for innovative ways to align economic progress with sustainability. This has given rise to green digital economies, where technological advancements are leveraged to create more efficient, low-carbon, and resource-conscious systems. The integration of artificial intelligence (AI), blockchain, big data, cloud computing, and the Internet of Things (IoT) into economic frameworks has opened new pathways for reducing waste, optimizing energy use, and fostering responsible production and consumption patterns. A green digital economy focuses on using technology to balance economic growth and environmental preservation. This concept is rooted in the broader sustainable development goals (SDGs) established by the United Nations, which emphasize the need for cleaner energy, reduced emissions, and responsible industrialization. The role of technological innovations in achieving these objectives cannot 866

Sun’iy Intellekt va Raqamli Iqtisodiyot SIRI-2025 be overstated, as emerging tools and digital solutions offer unparalleled efficiency, precision, and automation to industries worldwide. One of the most promising technological breakthroughs in recent years has been the development of smart cities and smart industries, where digital infrastructure enhances environmental sustainability. For instance, IoT sensors help manage energy consumption in urban areas, reducing carbon footprints, while blockchain-based supply chains ensure transparency and ethical sourcing of materials.”On the one hand, environmental degradation poses a threat to human survival and social development, and it is urgent to solve this problem through scientific and technological innovation and industrial restructuring. On the other hand, with the fast growth of information technology, the digital economy has shown great growth potential and broad development prospects and has become a new engine for promoting economic and social development. However, the rapid expansion of the digital economy has also brought new challenges, including increased energy consumption, e-waste generation, etc., which need to be properly addressed within the framework of the green economy” [9]. Additionally, big data analytics provide governments and corporations with insights into sustainability trends, helping them make informed decisions about environmental policies and green investments. However, despite the growing enthusiasm for green digital economies, several challenges and barriers hinder their full-scale adoption. These include the high cost of implementation, lack of regulatory frameworks, cybersecurity concerns, and the digital divide between developed and developing nations. Furthermore, ethical considerations surrounding AI-driven automation and data privacy must be addressed to create a fair and inclusive transition toward sustainability. This article aims to explore the effects of technological innovations on green digital economies and sustainable development strategies. The study investigates the impact of AI, blockchain, IoT, and big data on economic and environmental sustainability. It also examines existing policy frameworks and highlights potential investment opportunities for governments and private sector players looking to integrate these innovations into their economic models. Materials and Methods This study follows a qualitative research approach, conducting a systematic literature review of peer-reviewed journals, government reports, and case studies published between 2018 and 2023. The primary focus was on technological advancements in green digital economies, their impact on sustainability, and development strategies implemented by governments and industries. Data sources included databases such as Scopus, Google Scholar, and institutional repositories, ensuring a comprehensive analysis of emerging trends and challenges. Results The findings of this study highlight the significant impact of technological innovations on green digital economies. The analysis of case studies, statistical reports, and expert insights reveals how AI, IoT, blockchain, and big data analytics contribute to sustainability. The results are categorized into four key sectors: energy, smart cities and transportation, agriculture, and manufacturing. One of the most significant transformations enabled by technology is in the energy sector, where AI and blockchain have enhanced efficiency in renewable energy distribution. AI-driven smart grids have reduced electricity 867

SIRI-2025 Sun’iy Intellekt va Raqamli Iqtisodiyot waste by 20-30%, optimizing demand and supply balance. Blockchain-based peer-to-peer (P2P) energy trading has allowed small producers (e.g., households with solar panels) to sell surplus energy directly to consumers. The use of smart contracts ensures transparency and cost-effectiveness. The adoption of IoT-enabled energy monitoring has decreased industrial energy consumption by 15-25% in major economies such as Germany and China. Technological advancements have revolutionized urban sustainability and ecofriendly mobility solutions. IoT-based traffic management systems have reduced congestion, lowering carbon emissions by 30-40% in major cities such as Singapore and Amsterdam. The rise of electric vehicles (EVs) and AI-driven charging infrastructure has facilitated smoother energy distribution, leading to a 50% decrease in fossil fuel dependency in some regions. Smart waste management using AI-driven recycling solutions has increased urban waste efficiency by 35-45%. The application of AI and IoT in agriculture has led to more sustainable farming methods, ensuring optimal resource use while minimizing environmental damage. Precision farming with IoT sensors has reduced water usage by 40% while increasing crop yields by 20-30%. AI-powered drone monitoring has lowered pesticide use by 30%, minimizing harmful environmental impacts. Blockchain-based food traceability systems have improved supply chain transparency, reducing food waste by 25-35% in developed markets. The integration of automation, AI-driven supply chains, and big data analytics has played a crucial role in making industries more sustainable. AI-powered predictive maintenance has decreased industrial waste by 30%, extending the lifespan of manufacturing equipment. Digital twin technology, which creates virtual models of factories, has improved energy efficiency by 25%. Blockchain-based circular economy models have facilitated better waste recycling, reducing raw material demand by 20%. Discussion The findings of this study demonstrate that technological innovations are playing a crucial role in the development of green digital economies. This section will analyze the results in relation to sustainability goals, economic strategies, policy implications, and future challenges. The integration of AI, IoT, blockchain, and big data analytics has significantly improved energy efficiency, waste management, and carbon footprint reduction. AI-driven smart grids have reduced energy waste, contributing directly to the UN’s Sustainable Development Goal (SDG) 7: Affordable and Clean Energy. Blockchain-based peer-to-peer energy trading has decentralized the energy market, making renewable energy more accessible. IoT-enabled precision agriculture has led to better resource allocation, reducing water and fertilizer waste. These innovations accelerate the shift toward a circular economy, where materials are reused rather than discarded, aligning with SDG 12: Responsible Consumption and Production. Technological advancements have led to the rapid growth of green industries, driving investment and job creation. The global market for AI-powered sustainability solutions is projected to reach $5.2 trillion by 2030, reflecting a fundamental economic shift. Green digital economies are fostering new business models, such as: Decentralized renewable energy markets (via blockchain). Smart manufacturing with minimal waste production. AIdriven predictive analytics for industrial efficiency. 868

Sun’iy Intellekt va Raqamli Iqtisodiyot SIRI-2025 While the technological transformation of green economies is promising, it requires strong policy support to ensure equitable access, data security, and ethical implementation. Governments must invest in digital infrastructure to facilitate the widespread adoption of green technologies. Incentives for companies adopting AI-driven sustainability measures can accelerate the transition. Regulations on data privacy and blockchain security are necessary to prevent misuse while maintaining transparency. International cooperation is crucial, especially in carbon credit trading and cross-border sustainability initiatives. Countries that have successfully implemented green technology policies—such as Germany’s Energiewende and China’s AI-driven smart cities—serve as models for sustainable economic transformation. Despite the advancements, several challenges hinder the widespread implementation of digital innovations in green economies. High initial costs: AI and blockchain require significant investment, making adoption difficult for developing nations. Technological infrastructure gaps: Many regions lack access to high-speed internet, cloud computing, and IoT networks, limiting progress. Cybersecurity risks: The use of blockchain and AI in energy trading and industrial automation presents new security threats. Data bias and algorithmic limitations: AI systems can be flawed, requiring continuous updates and monitoring to ensure accuracy in sustainability applications. Resistance from traditional industries: Fossil fuel-based sectors and traditional manufacturers may resist green technology adoption due to concerns about economic disruptions. The future of green digital economies lies in the continued integration of emerging technologies with sustainability strategies. Potential research areas include: AI-powered climate modeling to predict and mitigate environmental risks. Decentralized finance (DeFi) for sustainability projects, using blockchain to facilitate global green investments. Quantum computing for energy optimization, enabling faster and more precise energy distribution in smart grids. 5G-enabled IoT for real-time environmental monitoring, ensuring rapid response to climate changes. AI-driven circular economy platforms that optimize the reuse of materials in manufacturing. Investment in these cutting-edge technologies will define the next phase of economic sustainability while addressing global environmental concerns. Conclusion The rapid evolution of technological innovations is reshaping global economies, driving the transition toward green digital economies. This study has explored how AI, IoT, blockchain, and big data analytics are enabling more sustainable practices across key sectors, including energy, transportation, agriculture, and manufacturing. The findings reveal that these technologies contribute to resource optimization, waste reduction, and enhanced efficiency, aligning with global sustainability goals such as the United Nations Sustainable Development Goals (SDGs). While technological innovations are paving the way for sustainable economic development, challenges such as high implementation costs, 869

SIRI-2025 Sun’iy Intellekt va Raqamli Iqtisodiyot cybersecurity risks, and resistance from traditional industries must be addressed. Global collaboration among governments, researchers, and businesses will be essential to overcome these barriers and achieve a fully sustainable, technology-driven economy. Technological innovations are transforming green digital economies by enhancing efficiency, promoting sustainability, and optimizing resource management. Continued research and strategic policymaking are necessary to overcome existing challenges and maximize the benefits of digitalization in sustainable development. References 1. Arun, T., & Yıldırım, S. (2023). The impact of artificial intelligence on green digital economies: A systematic review. Journal of Sustainable Technology, 18(2), 45-67. 2. European Environment Agency. (2023). The role of digital technologies in achieving sustainable economic growth. EEA Technical Report No. 12/2023. 3. Gogoi, B., & Mehta, R. (2021). Blockchain for sustainability: Innovations in energy and environmental sectors. Environmental Economics and Policy Studies, 24(3), 299-315. 4. International Energy Agency (IEA). (2023). Smart grids and AI applications in the energy transition. Retrieved from www.iea.org 5. Kumar, S., & Gupta, P. (2022). IoT and big data in precision agriculture: A review of recent advancements. Journal of Agricultural Informatics, 15(1), 112-130. 6. United Nations (UN). (2023). Digital transformation and the Sustainable Development Goals. United Nations Development Programme Report 2023. 7. World Bank. (2023). The economics of digital sustainability: Opportunities and challenges. Retrieved from www.worldbank.org 8. Zhao, L., & Wang, X. (2022). The role of AI in optimizing circular economy strategies in the manufacturing sector. Sustainable Manufacturing and Innovation Journal, 9(4), 189-210. 9. Liu, Y., Yang, Y., Zhang, X., & Yang, Y. (2024). The impact of technological innovation on the green digital economy and development strategies. Plos one, 19(4), e0301051. 870

Sun’iy Intellekt va Raqamli Iqtisodiyot SIRI-2025 ONLINE KUTUBXONA MOBIL ILOVASI IMKONIYATLARI VA TAVSIFI Abdurashidova Mohinur o‘tkir qizi TATU Samarqand filiali, abdurashidovam795@gmail.com Annotatsiya: Ushbu maqolada oliy ta’lim muassasalari axborot resurs markazlari xodimlari va talabalari uchun yaratilgan mobil ilova imkoniyatlari hamda tavsifi batafsil bayon qilingan. Kalit so‘zlar: Mobil ilova, online kutubxona, axborot resurs markazi, foydalanuvchi, ro‘yxatdan o‘tish, telefon. Asosiy matn Online kutubxona mobil ilovasi oliy ta’lim muassasasi ARM(axborot resurs markazi) misolida yaratilgan bo‘lib, quyida uning imkoniyatlari bilan tanishamiz: Ushbu ilova kutubxonalarda barcha faoliyatlarini raqamli tizimga aylantirishga, kutubxona kitoblar katalogini yaratish va online nazorat qilishga mo‘ljallangan(1-rasm). Ro‘yxatga olish ✓ Kutubxona foydalanuvchilarini doimo online ro‘yxatga olish tizimi; ✓ Bir tizimni bir necha kishi boshqara olishi tufayli barchasi juda qulay; ✓ Kutubxona foydalanuvchilari tarixini doimo nazorat qilib borish va istalgan vaqt tarixini ko‘raolish[1]; ✓ Istalgan muddat orasidagi ma’lumotlarni PDF shaklda yuklab olish imkoniyati(2-rasm). 2-rasm. Ro‘yxatga olish oynasi 1-rasm. Ilova bosh oynasi Kitoblarga bog‘liq faoliyatlar: ✓ Kitoblar katalogini hosil qilish; ✓ Ijaraga kitob berish; 871

SIRI-2025 Sun’iy Intellekt va Raqamli Iqtisodiyot ✓ Ijarachilar tarixi va ularni nazorat qiilb boorish[1]; ✓ Ijarachi bilan aloqa qilish(3-rasm). QR kod orqali ro‘yxatdan o‘tish Barchasi qulay bo‘lishi uchun QR kodni skanerlash orqali foydalanuvchilarni ro‘yxatdan o‘tkazish(4-rasm). 3-rasm. Kitoblar oynasi 4-rasm. QR kod orqali ro‘yxatdan o‘tish oynasi Yaratilgan mobil ilova tavsifi Mobil ilovani telefonimizga o‘rnatish uchun quyidagi faylni ishga tushiramiz[2]. Ushbu faylni o‘rnatganimizdan so‘ng, telefonimizdan online kutubxona mobil ilovasi paydo bo‘ladi(5-rasm). Bu ilovani ishga tushiradigan bo‘lsak, bizga ilovaga login va parol orqali kirish oynasi ishga tushadi(6-rasm). 5-rasm. Online kutubxona mobil ilovasi 6-rasm. Kirish oynasi Avvaldan ro‘yxatdan o‘tgan lorin va parolni terish orqali biz mobil ilovaga kirishimiz mumkin(7-rasm). 872

Sun’iy Intellekt va Raqamli Iqtisodiyot SIRI-2025 Agar biz mobil ilovadan ro‘yxatdan o‘tmagan bo‘lsak, foydalanish uchun avval ro‘yxatdan o‘tish kerak bo‘ladi[2]. Buning uchun ilova oynasidagi Ro‘yxatdan o‘tish bo‘limini tanlaymiz(8-rasm). 7-rasm. Kirish oynasi 8-rasm. Ro‘yxatdan o‘tish oynasi Mobil ilovadan ro‘yxatdan o‘tish uchun: • Ism; • Familiya; • Parol; • Guruh raqami ma’lumotlarini kiritishimiz kerak bo‘ladi(9-rasm). 9-rasm. Ro‘yxatdan o‘tish oynasi Berilgan maydonlarni barchasini to‘ldirib bo‘lgandan so‘ng, Ro‘yxatdan o‘tish tugmasi orqali mobil ilovadan ro‘yxatdan o‘tishimiz mumkin bo‘ladi[2]. 873

SIRI-2025 Sun’iy Intellekt va Raqamli Iqtisodiyot Adabiyotlar 1. Mingboyev Ulug‘bek S. A., Djumayev Sindor O. N. E. TA’LIMDA FOYDALANILADIGAN MOBIL ILOVALARNING AFZALLIKLARI VA KAMCHILIKLARI //International Journal of Contemporary Scientific and Technical Research. – 2023. – С. 279-282. 2. Djumayev, S. N., D. A. Shodmonov, and N. E. Ortiqova. "Ta’limda mobil ilovalardan foydalanish imkoniyatlari: Possibilities of Using Mobile Applications in Education." International journal of theoretical and applied issues of digital technologies 4.2 (2023): 9095. 874

Sun’iy Intellekt va Raqamli Iqtisodiyot SIRI-2025 XUSUSIY TIBBIYOT MARKAZI MIJOZLARI VA XODIMLARI UCHUN AXBOROT TIZIMINI YARATISH Xaitova Odina Xushnud qizi TATU Samarqand filiali, odinaxaitova06@gmil.com Annotatsiya: Ushbu maqolada xususiy tibbiyot muassasalari uchun yaratilgan axborot tiizmidan foydalanish yo‘riqnomasi va tizim funksiyalari bayon qilingan. Kalit so‘zlar: Axboot tizimi, login, parol, dasturlash tili, ma’lumotlar bazasi, kasalliklar tarixi, vrachlar ro‘yxati, sahifalar turlari. Kirish Dastur barcha turdagi operatsion tizimlari uchun MySQL va PHP tilida yaratilgan bo‘lib, uning vazifasi xususiy tibbiyot muassasalarida mijozlarga xizmat ko‘rsatishni avtomatlashtirishdan iborat. Hozirgi kunda ish faoliyatida ro‘yxatdan o‘tkazish va xizmat ko‘rsatish masalalarini avtomatlashtirish dolzarb bo‘lib qolmoqda. Ana shu va boshqa ayrim muammolarni hisobga olib bu jarayonlarni avtomatlashtiruvchi dasturiy tizim yaratish masalasi yuzasidan ishning dolzarbligini anglab olish mumkin[1]. Dasturdan foydalanuvchilar uchun ko‘rsatmalar. Bu dastur barcha turdagi operatsion tizimlari uchun MySQL va PHP muhitida yaratilgan bo‘lib, tizimni ishga tushirish uchun web brauzer oynasidagii manzil satriga quyidagi nomni yozishimiz kerak bo‘ladi[2]. Natijada 1-rasmdagi kabi tizim bosh oy asi ishga tushadi. 1-rasm. Imedservis dasturining bosh oynasi. Ko‘rib turganimizdek bu yerda tibbiyot muassasasining 4 ta turdagi mutaxassislari ko‘rigi kiritilgan. Bundan biz o‘zimizga kerakli mutaxassislikni tanlaymiz, ya’ni “LOR” bo‘limiga kiramiz. Shunda bizga 2-rasmdagi bo‘lim oynasiga kirish oynasi ishga tushadi. Bu oynadan tizimga kirish uchun Login va Parolni teramiz. Login va Parol muassasaning tegishli javobgar xodimigagina ma’lum bo‘ladi(3-rasm). 875

SIRI-2025 2-rasm. Pechat dasturining interfeysi. Sun’iy Intellekt va Raqamli Iqtisodiyot 3-rasm. Pechat dasturining interfeysi. Login va Parol to‘g‘ri kiritlgandan so‘ng, tibbiyot muassasasining “LOR” bo‘limiga tegishli ma’lumotlar oynasi ishga tushadi. Bu oynada “LOR” boֹ‘limiga oid mijozlar bilan ishlaydigan quyidagi bandlar mavjud(4rasm): • Umumiy mijozlar haqida; • Ma’lumotlarni izlash va tartiblash; • Ro‘yxatdan o‘tkazish; • Ma’lumotlarni o‘chirish; • Chop etish. Bulardan biz mijozlar haqida umumiy ma’lumotlarni quyidagi oynadan olishimiz mumkin(4-rasm): Agar “Ma’lumotlarni izlash va tartiblash” bandiga kiradigan bo‘lsak, u yerdan mijozlarni kerakli xususiyatlari bo‘yicha izlab topishimiz va tartiblashimiz mumkin. Masalan, 2018 yil 10-avgustdan 30-avgustgacha kelgan mijozlar haqida ma’lumot olmoqchi bo‘lsak, quyidagi oynadagi kabi so‘rov berib natijalarni olishimiz mumin(5-rasm). 4-rasm. Pechat dasturining interfeysi. 5-rasm. Ma’lumotlarni izlash va tartiblash oynasi. Yoki bo‘lmasa izlashni boshqa parametrlar orqali ham amalga oshirish mumkin, masalan, ism familiyani kiritish orqali mijozlarni izlash mumkin(6-rasm). Mijozlar haqidagi ma’luotlarni qog‘ozga chop etish uchun oynaning “chop etish” bandidan foydalanamiz(7-rasm). 876

Sun’iy Intellekt va Raqamli Iqtisodiyot SIRI-2025 7-rasm. Chop etish oynasi. 6-rasm. Ma’lumotlarni izlash va tartiblash oynasi. Bu oynadan har bir mijoz haqidagi ma’lumotni alohida shaklida chop etib olishimiz mumkin bo‘ladi(8-rasm). Mijozlar haqidagi ma’lumotlarni tahrirlash yoki bazadan o‘chirish uchun “Ma’lumotlarni o‘chirish” bandidan foydalanamiz(9-rasm). Bu oynadan har bir foydalanuvchini alohida o‘chirishimiz mumkin bo‘ladi. 9-rasm. Ma’lumotlarni o‘chirish va tahrirlash oynasi. 8-rasm. Mijoz haqida ma’lumotni chop etish oynasi. Yangi kelgan mijozlarin bazaga kiritish uchun “Ro‘yxatdan o‘tkazish” bandidan foydalaniladi(10,11,12,13-rasmlar). Mijozni ro‘yxatdan o‘tkazish uchun bu oynadagi barcha tegishli bo‘limlarni to‘ldirib chiqamiz. 11-rasm. Ro‘yxatdan o‘tkazish oynasi 10-rasm. Ro‘yxatdan o‘tkazish oynasi. 877

SIRI-2025 Sun’iy Intellekt va Raqamli Iqtisodiyot 12-rasm. Ro‘yxatdan o‘tkazish oynasi. 13-rasm. Ma’lumotlarni tahrirlash oynasi. o‘chirish va 13-rasmda yuqoridagi ro‘yxatga kiritgan mijozimizni ism familiyasini ko‘rishimiz mumkin. Ana shu shaklda dasturning boshqa bo‘limlarini faoliyatini ham olib borish mumkin[3]. Adabiyotlar 1. Djumayev S. N., Shodmonov D. A., Ortiqova N. E. Ta’limda mobil ilovalardan foydalanish imkoniyatlari: Possibilities of Using Mobile Applications in Education //International journal of theoretical and applied issues of digital technologies. – 2023. – Т. 4. – №. 2. – С. 90-95. 2. Sulyukova L. F., Yakubjanova D. K., Djumaev S. N. Modeling and assessment of the energy state of the technological system of mechanical processing when creating digital twins //E3S Web of Conferences. – EDP Sciences, 2023. – Т. 402. – С. 03010. 3. Mamaraufov O. A., Fayzimuratov N. B., Djumaev S. N. Purpose and significance of intellectual processing of videos //scientific revolutions: essence and role in the development of science and technology. – 2021. – С. 13-17. 878

Sun’iy Intellekt va Raqamli Iqtisodiyot SIRI-2025 FUNKSIONAL DIAGNOSTIKA Bo‘LIMIDAGI ELEKTROKARDIOGRMMA TEXNIKASINI SOZLASH, TEXNIK XIZMAT Ko‘RSATISH VA DASTURIY TA'MINOTI YAXSHI ISHLASHINI TEKSHIRISHDA SUN'IY INTELEKTDAN SAMARALI FOYDALANISH BOSQICHLARI Mirzakulova Gulbahor Abdusodiq qizi, Ismoiljonov Yodgorbek Komiljon o‘g‘li Avtomobil va traktorsozlik fakulteti, Biotibbiyot muxandisligi, Andijon Mashinasozlik insitituti Annotatsiya. Ushbu maqolada tibbiyotda funksional diagnostika bo‘limida ishlatiladigan elektrokardiogramma (EKG) texnologiyasining sozlanishi, unga texnik xizmat ko‘rsatish va dasturiy ta’minotining to‘g‘ri ishlashini tekshirish jarayonlarida sun’iy intellektdan (SI) samarali foydalanish bosqichlari ko‘rib chiqiladi. Sun’iy intellekt diagnostika qurilmalarining ishonchliligini oshirish, avtomatik nosozliklarni aniqlash va texnik xizmat samaradorligini oshirish imkonini beradi. Kalit so‘zlar: Elektrokardiogramma, sun’iy intellekt, texnik xizmat, tibbiy asbobuskunalar, dasturiy ta’minot, avtomatik diagnostika. Kirish. Elektrokardiogramma (EKG) yurak faoliyatini baholashda eng muhim diagnostika vositalaridan biri hisoblanadi. Uning aniqligi va uzluksiz ishlashi bemor salomatligi uchun muhim ahamiyatga ega. Zamonaviy EKG qurilmalari murakkab dasturiy va apparat ta’minotiga ega bo‘lib, ularning ishlashini tekshirish va texnik xizmat ko‘rsatish doimiy e’tiborni talab qiladi. Sun’iy intellekt texnologiyalarining rivojlanishi EKG qurilmalarini optimallashtirish, avtomatik diagnostika va nosozliklarni oldindan aniqlash imkonini bermoqda. Ushbu maqolada SI yordamida EKG texnologiyasining sozlanishi, texnik xizmat ko‘rsatish va dasturiy ta’minotning to‘g‘ri ishlashini tekshirish bosqichlari yoritiladi. Elektrokardiogramma texnologiyasida sun’iy intellektning o‘rni.Sun’iy intellekt tibbiy texnologiyalarning texnik ishonchliligini oshirishda quyidagi yo‘nalishlarda yordam beradi: 1. Avtomatik diagnostika– Qurilmalarning ishlash holatini real vaqtda baholash. 2. Nosozliklarni erta aniqlash– Sensorlar va dasturiy ta’minot ishlashini monitoring qilish. 3. Texnik xizmatni optimallashtirish – EKG qurilmalari uchun texnik xizmat muddatlarini bashorat qilish va avtomatlashtirish. 4. Dasturiy ta’minot muammolarini aniqlash– Algoritmlarning noto‘g‘ri ishlashini aniqlash va optimallashtirish. Sun’iy intellektdan foydalanish bosqichlari 1. Ma’lumotlarni yig‘ish va qayta ishlash – EKG qurilmalari ishlash holati haqidagi ma’lumotlar to‘planadi va tahlil qilinadi. 2. Nosozliklarni aniqlash uchun mashina o‘rganish modellari yaratish – Qurilmadagi texnik va dasturiy muammolarni tahlil qilish uchun sun’iy intellekt algoritmlari ishlab chiqiladi. 3. Real vaqt rejimida monitoring – SI yordamida qurilmalarning ishlash holati doimiy nazorat qilinadi. 879

SIRI-2025 Sun’iy Intellekt va Raqamli Iqtisodiyot 4. Texnik xizmat ko‘rsatish rejalarini avtomatlashtirish– EKG qurilmalariga texnik xizmat ko‘rsatish davrlarini sun’iy intellekt orqali optimallashtirish. 5. Dasturiy ta’minotni test qilish va optimallashtirish– SI yordamida EKG dasturiy ta’minotining noto‘g‘ri ishlash holatlarini aniqlash va ularni tuzatish. EKG qurilmalarining ishlashini monitoring qilish. SI yordamida sensor va komponentlarning ishlashini real vaqt rejimida kuzatish orqali nosozliklarni oldindan aniqlash mumkin. Masalan, elektrodlardagi kontakt muammolari yoki signal sifatining pasayishi avtomatik ravishda aniqlanadi. Nosozliklarni bashorat qilish va texnik xizmat rejasini avtomatlashtirish. SI algoritmlari qurilma komponentlarining ishlash siklini kuzatib borib, ularning qachon nosozlikka uchrashi mumkinligini oldindan bashorat qiladi. Bu esa texnik xizmatni optimal rejalashtirish imkonini beradi. Dasturiy ta’minot muammolarini avtomatik aniqlash va tuzatish. EKG dasturiy ta’minotida yuzaga kelishi mumkin bo‘lgan nosozliklar, masalan, noto‘g‘ri signal tahlili yoki ma’lumotlarni noto‘g‘ri yozib olish muammolari SI yordamida aniqlanadi va tuzatiladi. Avtomatik kalibrlash va sozlash. SI algoritmlari yordamida EKG qurilmalarining aniq ishlashi uchun avtomatik kalibrlash amalga oshiriladi, bu esa inson omili ta’sirini kamaytiradi va diagnostika aniqligini oshiradi. 1. Mashina o‘rganish (Machine Learning, ML). Mashina o‘rganish algoritmlari EKG signalining sifatini baholash, anomaliyalarni aniqlash va diagnostik natijalarning to‘g‘riligini tekshirish uchun qo‘llaniladi. Foydalanish sohalari Nosozliklarni aniqlash: EKG qurilmalarining noto‘g‘ri ishlashini aniqlash. Signal sifatini baholash: Elektrodlarning noto‘g‘ri joylashuvi yoki signal shovqinlarini bartaraf etish. Tashxisni avtomatlashtirish: Yurak ritmidagi buzilishlarni aniqlash. 2. Chuqur o‘rganish (Deep Learning, DL). Neyron tarmoqlari EKG signallarini tahlil qilish va aniq tashxis qo‘yish uchun ishlatiladi. Ayniqsa, konvolyutsion neyron tarmoqlari (CNN) va rekurrent neyron tarmoqlari (RNN) yurak signallarining murakkab xususiyatlarini o‘rganishda samarali hisoblanadi. Foydalanish sohalari: EKG signallarini avtomatik qayta ishlash. Tashxisni takomillashtirish va aniq natijalar chiqarish. Tibbiy dasturlar orqali real vaqt rejimida monitoring. 3. Sun’iy neyron tarmoqlari (Artificial Neural Networks, ANN). ANN algoritmlari EKG ma’lumotlarini qayta ishlash va modellashtirish uchun ishlatiladi. Ular katta hajmdagi EKG ma’lumotlarini tahlil qilib, yurak kasalliklarini aniqlashda yordam beradi. Foydalanish sohalari: Tashxis ma’lumotlarini to‘g‘rilash va optimallashtirish. 880