AQLLI MUHITDA SUN’IY INTELLEKT TEXNOLOGIYALARINI QO’LLASH SAMARADORLIGI
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aqlli muhit, sun’iy intellekt, optimallashtirish, qaror qabul qilish, aqlli shahar, avtomatlashtirish, IoT, tahlil, texnologiya, samaradorlik.##article.abstract##
Ushbu maqolada aqlli muhitda sun’iy intellekt (SI)
texnologiyalarini qo‘llash samaradorligi tahlil qilinadi. Sun’iy intellekt aqlli
shaharlar, sog‘liqni saqlash, transport, energetika, xavfsizlik va boshqa
infratuzilmaviy tizimlarda qaror qabul qilishni avtomatlashtirish, optimallashtirish va
samaradorligini oshirishda muhim vosita sifatida namoyon bo‘lmoqda. Tadqiqot
davomida SI texnologiyalarining asosiy yo‘nalishlari, amaliy qo‘llanilishi va ularning
funksional afzalliklari chuqur o‘rganilib, ularni amalga oshirish jarayonida yuzaga
keladigan muammolar va ularning yechimlari tahlil qilinadi. Maqola yakunida sun’iy
intellekt asosida boshqariluvchi aqlli tizimlarning samaradorligini baholash
mezonlari keltiriladi va kelajakda bu texnologiyalarning rivojlanish istiqbollari
haqida fikr yuritiladi.
##submission.citations##
1.
Jabareen, Y. (2013). Planning the resilient city: Concepts and strategies for
coping with climate change and environmental risk. Cities, 31, 220–229.
2.
Mohanty, S. P., Choppali, U., & Kougianos, E. (2016). Everything you wanted
to know about smart cities: The Internet of Things is the backbone. IEEE Consumer
Electronics Magazine, 5(3), 60–70.
3.
Bibri, S. E. (2019). The anatomy of the data-driven smart sustainable city:
Instrumentation, datafication, computerization and related applications. Journal of Big
Data, 6(1), 59.
4.
Bhattacharya, S., Somayaji, S. R. K., Gadekallu, T. R., Alazab, M., &
Maddikunta, P. K. R. (2020). A review on deep learning for future smart cities. Internet
Technology Letters, e187.
5.
Kumar, P. M., Gandhi, U., & Varatharajan, R. (2019). Intelligent face
recognition and navigation system using neural learning for smart security in IoT.
Cluster Computing, 22(4), 7733–7744.
6.
Sajjad, M., Nasir, M., Muhammad, K., Khan, S., Jan, Z., & Sangaiah, A. K.
(2020). Raspberry Pi assisted face recognition framework for enhanced law
enforcement services in smart cities. Future Generation Computer Systems, 108, 995
1007.
7.
Jegadeesan, S., Azees, M., Kumar, P. M., Manogaran, G., & Chilamkurti, N.
(2019). An efficient anonymous mutual authentication technique for mobile cloud
computing in smart cities. Sustainable Cities and Society, 49, 101522.8.
Gomathi, P., Baskar, S., & Shakeel, P. M. (2020). Concurrent service access and
management framework for user-centric future IoT in smart cities. Complex &
Intelligent Systems, https://doi.org/10.1007/s40747-020-00160-5
9.
Zhao, L., Wang, J., Liu, J., & Kato, N. (2019). Routing for crowd management
in smart cities: A deep reinforcement learning perspective. IEEE Communications
Magazine, 57(4), 88–93.
10.
Yigitcanlar, T. (2015). Smart cities: An effective urban development and
management model? Australian Planner, 52(1), 27–34.
11.
Jabareen, Y. (2013). Planning the resilient city: Concepts and strategies for
coping with climate change. Cities, 31, 220–229.
12.
Kumar, N., Vasilakos, A. V., & Rodrigues, J. J. (2017). A multi-tenant cloud
based DC nano grid for self-sustained smart buildings in smart cities. IEEE
Communications Magazine, 55(3), 14–21.
13.
Williamson, B. (2017). Computing brains: Learning algorithms and
neurocomputation in the smart city. Information, Communication & Society, 20(1),
81–99.
14.
Aloqaily, M., Otoum, S., Al Ridhawi, I., & Jararweh, Y. (2019). An intrusion
detection system for connected vehicles in smart cities. Ad Hoc Networks, 90, 101842.
15.
Sekaran, K., Meqdad, M. N., Kumar, P., Rajan, S., & Kadry, S. (2020). Smart
agriculture management system using Internet of Things. Telkomnika, 18(3), 1275
1284.
16.
Dieleman, H. (2013). Organizational learning for resilient cities, through
realizing eco-cultural innovations. Journal of Cleaner Production, 50, 171–180.
17.
Macke, J., Casagrande, R. M., Sarate, J. A., & Silva, K. A. (2018). Smart city
and quality of life: Citizens’ perception in a Brazilian case study. Journal of Cleaner
Production, 182, 717–726.
18.
Binz, C., Truffer, B., Li, L., Shi, Y., & Lu, Y. (2012). Conceptualizing
leapfrogging with spatially coupled innovation systems: The case of onsite wastewater
treatment in China. Technological Forecasting and Social Change, 79(1), 155–171. 19.
Cohen, A. J., Brauer, M., Burnett, R., Anderson, H. R., Frostad, J., Estep, K., et
al. (2017). Estimates and 25-year trends of the global burden of disease attributable to
ambient air pollution. The Lancet, 389(10082), 1907–1918.
20.
Van Dalen, A. (2012). The algorithms behind the headlines: How machine
written news redefines the core skills of human journalists. Journalism Practice, 6(5
6), 648–658.
21.
Hanjra, M. A., Blackwell, J., Carr, G., Zhang, F., & Jackson, T. M. (2012).
Wastewater irrigation and environmental health: Implications for water governance.
International Journal of Hygiene and Environmental Health, 215(3), 255–269.
