CHUQUR O‘RGANISHGA ASOSLANGAN HOLDA AQLLI SHAHAR UCHUN AQLLI MUHITNI LOYIHALASH VA REJALASHTIRISH
Ключевые слова:
Aqlli shahar, aqlli muhit, chuqur o‘rganish, sun’iy intellekt, IoT, loyihalash, qaror qabul qilish, rejalashtirish, ma’lumotlarni tahlil qilish, avtomatlashtirilgan boshqaruv.Аннотация
Ushbu maqolada chuqur o‘rganish (deep learning)
texnologiyalariga asoslangan holda aqlli shaharlar uchun aqlli muhitni samarali
loyihalash va rejalashtirish masalalari yoritiladi. Aqlli shahar infratuzilmasida real
vaqtli monitoring, bashoratlash, resurslarni optimal boshqarish hamda fuqarolar
xavfsizligi va qulayligi asosiy ustuvor yo‘nalishlardan biri sifatida qaraladi. Shu
nuqtai nazardan, maqolada chuqur o‘rganish modellari yordamida katta hajmdagi
ma’lumotlarni tahlil qilish, kontekstga mos qarorlar qabul qilish va tizimning
adaptivligi kabi jihatlar keng muhokama qilinadi. Loyihalash jarayonida atrof-muhit
holatini o‘lchash, harakatni aniqlash, transport oqimini boshqarish va energiya
samaradorligini ta’minlash kabi komponentlar chuqur o‘rganish algoritmlari bilan
uyg‘unlashtirilgan holda tavsiflanadi. Maqola yakunida aqlli muhitni barpo etishda
chuqur o‘rganish texnologiyalarining ustunliklari va ularni amaliyotga tatbiq
qilishdagi dolzarb masalalar xulosa tarzida bayon etiladi.
Библиографические ссылки
1.
Jabareen, Y. (2013). Planning the resilient city: Concepts and strategies for
coping with climate change and environmental risk. Cities, 31, 220–229.
2.
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.
3.
Jegadeesan, S., Azees, M., Kumar, P. M., Manogaran, G., Chilamkurti, N.,
Varatharajan, R., et al. (2019). An efficient anonymous mutual authentication
technique for providing secure communication in mobile cloud computing for smart
city applications. Sustainable Cities and Society, 49, 101522.4.
Ambituuni, A., Amezaga, J., & Emeseh, E. (2014). Analysis of safety and
environmental regulations for downstream petroleum industry operations in Nigeria:
Problems and prospects. Environmental Development, 9, 43–60.
5.
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.
6.
Gomathi, P., Baskar, S., & Shakeel, P. M. (2020). Concurrent service access and
management framework for user-centric future internet of things in smart cities.
Complex & Intelligent Systems. https://doi.org/10.1007/s40747-020-00160-5
7.
Sajjad, M., Nasir, M., Muhammad, K., Khan, S., Jan, Z., Sangaiah, A. K., et al.
(2020). Raspberry Pi assisted face recognition framework for enhanced law
enforcement services in smart cities. Future Generation Computer Systems, 108, 995
1007.
8.
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.
9.
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.
10.
Schaffers, H., Komninos, N., Pallot, M., Trousse, B., Nilsson, M., Oliveira, A.,
et al. (2011). Berlin, Heidelberg: Springer, pp. 431–446.
11.
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.
12.
Kumar, P. M., Gandhi, U., Varatharajan, R., Manogaran, G., Jidhesh, R., &
Vadivel, T. (2019). Intelligent face recognition and navigation system using neural
learning for smart security in Internet of Things. Cluster Computing, 22(4), 7733
7744.13.
Dieleman, H. (2013). Organizational learning for resilient cities, through
realizing eco-cultural innovations. Journal of Cleaner Production, 50, 171–180.
14.
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.
15.
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.
16.
Lorek, S., & Spangenberg, J. H. (2014). Sustainable consumption within a
sustainable economy–beyond green growth and green economies. Journal of Cleaner
Production, 63, 33–44.
17.
Hanjra, M. A., Blackwell, J., Carr, G., Zhang, F., & Jackson, T. M. (2012).
Wastewater irrigation and environmental health: Implications for water governance
and public policy. International Journal of Hygiene and Environmental Health, 215(3),
255–269.
18.
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.
19.
Wang, S. P., Lin, L. C., Lee, C. M., & Wu, S. C. (2011). Effectiveness of a self
care program in improving symptom distress and quality of life in congestive heart
failure patients: A preliminary study. Journal of Nursing Research, 19(4), 257–266.
