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Big Data Studies in Combating the Covid-19 Virus Outbreak: The Case of China

Year 2021, , 4 - 14, 21.12.2021
https://doi.org/10.5281/zenodo.4718425

Abstract

The coronavirus epidemic has greatly affected our lives by causing radical changes all over the world. It has caused changes in a variety of areas, from the way we work and education, to our communication and interaction methods, to our shopping behaviour. China has actively used smart technologies such as big data, artificial intelligence, cloud computing, blockchain, 5G to fight the coronavirus. Companies made their algorithms public, researchers shared data. Companies have also increased access to important video streaming tools for educators and remote workers. While its effects are continuing under various restrictions all over the world and the effects of the second wave are heavy in many countries, the epidemic has been brought under control in countries such as South Korea, Singapore, Taiwan and especially China, and life almost completely returned to normal. In this research, we aimed to investigate how the big data and artificial intelligence studies which have been applied in China are used to fight against the pandemic and the situation is taken under control by the installation of digital infrastructure, the analysis and monitoring of the data provided by the sensors and cameras.

References

  • [1] https://www.worldometers.info/coronavirus, Erişim Tarihi: 19 Aralık 2020.
  • [2] Coronavirus Disease (COVID-19) Pandemic, WHO, 2020. https://www.who.int/emergencies/diseases/novel-coronavirus-2019, Erişim Tarihi: 19 Aralık 2020.
  • [3] Coronavirus (COVID-19), Hastalık Kontrol ve Önleme Merkezleri (CDC), 2020. https://www.cdc.gov/coronavirus/2019-nCoV/index.html, Erişim Tarihi: 19 Aralık 2020.
  • [4] https://www.google.com/covid19, Erişim Tarihi: 01 Ocak 2021
  • [5] https://www.bing.com/covid/, Erişim Tarihi: 01 Ocak 2021
  • [6] https://www.whitehouse.gov/briefings-statements/white-house-announces-new-partnership-unleash-u-s-supercomputing-resources-fight-covid-19/, Erişim Tarihi: 19 Aralık 2020.
  • [7] https://blog.arxiv.org/2020/03/30/new-covid-19-quick-search/, Erişim Tarihi:19 Aralık 2020.
  • [8] https://www.who.int/csr/resources/publications/surveillance/plague.pdf, Erişim Tarihi:20 Aralık 2020
  • [9] Parıldar, H., “Tarihte Bulaşıcı Hastalık Salgınları”, Tepecik Eğit. ve Araşt. Hast. Dergisi, 30:19-26, 2020.
  • [10] https://tr.euronews.com/2020/07/07/fotograflarla-1918-ispanyol-gribi-abd-salg-nlara-kars-kat-edilen-mesafeyi-sorguluyor, Erişim Tarihi:24 Mart 2021
  • [11] https://coronaboard.kr/en/, Erişim Tarihi: 24 Mart 2021
  • [12] Q. Pham, D. C. Nguyen, T. Huynh-The, W. Hwang and P. N. Pathirana, “Artificial Intelligence (AI) and Big Data for Coronavirus (COVID-19) Pandemic: A Survey on the State-of-the-Arts”, in IEEE Access, vol. 8, pp. 130820-130839, 2020, doi: 10.1109/ACCESS.2020.3009328.
  • [13] Salman Y. G., “Transforming laparoendoscopic surgical protocols during the COVID-19 pandemic; big data analytics, resource allocation and operational considerations”, International Journal of Surgery, Volume 80, Pages 21-25, ISSN 1743-9191, 2020, https://doi.org/10.1016/j.ijsu.2020.06.027.
  • [14] Z. Hu, Q. Ge, S. Li, L. Jin and M. Xiong, “Artificial intelligence forecasting of COVID-19 in China”, arXiv:2002.07112, 2020,
  • [15] IBM Releases Novel AI-Powered Technologies to Help Health and Research Community Accelerate the Discovery of Medical Insights and Treatments for COVID-19, 2020. https://www.ibm.com/blogs/research/2020/04/ai-powered-technologies-accelerate-discovery-covid-19/, Erişim Tarihi: 01 Ocak 2021
  • [16] https://covid19-hpc-consortium.org/, Erişim Tarihi: 01 Ocak 2021
  • [17] https://www.cov-irt.org/, Erişim Tarihi: 01 Ocak 2021
  • [18] https://web.archive.org/web/20191009032639/https://www.comparitech.com/vpn-privacy/the-worlds-most-surveilled-cities/, Erişim Tarihi: 01 Ocak 2021
  • [19] https://merics.org/en/report/tracing-testing-tweaking, Erişim Tarihi: 25 Aralık 2020
  • [20] https://www.cbronline.com/news/china-to-roll-out-temperature-taking-infrared-cameras, Erişim Tarihi: 01 Ocak 2021
  • [21] https://www.imf.org/en/Topics/imf-and-covid19/Fiscal-Policies-Database-in-Response-to-COVID-19, Erişim Tarihi: 01 Ocak 2021
  • [22] Demi̇rdöğmez, M., Taş, H., Gülteki̇n, N., “Koronavirüs’ün (Covid-19) E-Ticarete Etkileri”, OPUS Uluslararası Toplum Araştırmaları Dergisi, 16 (29), 1907-1927, 2020. DOI: 10.26466/opus.734477
  • [23] https://business.blogthinkbig.com/the-big-data-and-iot-applications-fighting-coronavirus/, Erişim Tarihi:02 Aralık 2020
  • [24] https://towardsdatascience.com/coronavirus-a-big-data-lesson-from-south-korea-5bb703b8b0ae, Erişim Tarihi:02 Aralık 2020
  • [25] Rastogi, Y.R., Sharma, A., Nagraik, R., Aygün, A., Şen, F., “The Novel Coronavirus 2019-Ncov: Its Evolution and Transmission into Humans Causing Global Covıd-19 Pandemic”, International Journal of Environmental Science and Technology, 17, 4381–4388., 2020. doi:10.1007/s13762-020-02781-2
  • [26] A. A. Hussain, O. Bouachir, F. Al-Turjman and M. Aloqaily, “AI Techniques for COVID-19”, IEEE Access, vol. 8, pp. 128776-128795, 2020, doi: 10.1109/ACCESS.2020.3007939.
  • [27] Robinson, K., “A False Promise of Covid-19 ‘Big’ Health Data? Health Data Integrity and The Ethics and Realities of Australia’s Health Information Management Practice”, Health Information Management Journal, 50, 9–12., 2021. doi:10.1177/1833358320941190
  • [28] P. Yu, Z. Xia, J. Fei and S. K. Jha, “An Application Review of Artificial Intelligence in Prevention and Cure of Covid-19 Pandemic”, Computers, Materials & Continua, vol. 65, no.1, pp. 743–760, 2020.
  • [29] L. Akin and M. G. Gözel, “Understanding Dynamics of Pandemics”, Turkish Journal of Medical Sciences, vol. 50, no. SI–1, pp. 515–519, 2020.
  • [30] J. Fan, B. D. Hambly, and S. Bao, “The Epidemiology of COVID-19 in the Gansu and Jinlin Provinces, China”, Frontiers in Public Health, vol. 8, 2020.
  • [31] T. Alamo, D. Reina, M. Mammarella, and A. Abella, “Covid-19: Open-Data Resources for Monitoring, Modeling, and Forecasting the Epidemic”, Electronics, vol. 9, no. 5, p. 827, 2020.
  • [32] Y. Wang, J. Li, X. Zhao, G. Feng, and X. (Robert). Luo, “Using Mobile Phone Data for Emergency Management: A Systematic Literature Review”, Information Systems Frontiers, vol. 22, no. 6, pp. 1539–1559, 2020.
  • [33] C. Zheng, X. Deng, Q. Fu, Q. Zhou, J. Feng, H. Ma, et al., “Deep Learning-Based Detection For COVID-19 From Chest CT Using Weak Label”, medRxiv, 2020.
  • [34] A. Zhavoronkov, V. Aladinskiy, A. Zhebrak, B. Zagribelnyy, V. Terentiev, D. S. Bezrukov, et al., “Potential 2019-nCoV 3C-like Protease Inhibitors Designed Using Generative Deep Learning Approaches”, Insilico Med. Hong Kong Ltd A, vol. 307, no. 2, pp. E1, 2020.
  • [35] A. Adadi and M. Berrada, “Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)”, IEEE Access, vol. 6, pp. 52138-52160, 2018.
  • [36] https://www.weforum.org/agenda/2020/04/how-next-generation-information-technologies-tackled-covid-19-in-china/, Erişim Tarihi: 01 Ocak 2021
  • [37] https://www.bbc.com/turkce/haberler-dunya-52638919, Erişim Tarihi: 01 Ocak 2021

Covid-19 Virüsü Salgını İle Mücadelede Büyük Veri Çalışmaları: Çin Örneği

Year 2021, , 4 - 14, 21.12.2021
https://doi.org/10.5281/zenodo.4718425

Abstract

Koronavirüs salgını, bütün dünyada köklü değişikliklere sebep olarak hepimizin hayatını büyük ölçüde etkiledi. Çalışma ve eğitim şekillerimizden, iletişim ve etkileşim yöntemlerimize, alışveriş davranışlarımıza kadar çeşitli alanlarda değişikliklere sebep oldu. Çin, koronavirüsle savaşmak için büyük veri, yapay zekâ, bulut bilişim, blok zinciri, 5G gibi akıllı teknolojileri aktif olarak kullandı. Şirketler algoritmalarını halka açık hale getirdi, araştırmacılar verileri paylaştı. Şirketler, eğitimciler ve uzaktan çalışanlar için önemli video yayın araçlarına erişim olanakları artırıldı. Etkileri hala bütün dünyada çeşitli kısıtlamalar altında devam ederken ve birçok ülkede ikinci dalganın etkileri ağır bir şekilde seyrederken, Güney Kore, Singapur, Tayvan ve özellikle Çin gibi ülkelerde salgın kontrol altına alındı ve neredeyse hayat tamamen normale döndü. Bu çalışmada, Çin’de uygulanan büyük veri ve yapay zekâ çalışmalarının salgınla mücadelede nasıl kullanıldığı ve durumun dijital altyapı kurulumu, algılayıcıların (sensörlerin), kameraların sağladığı verileri analizi ve takibi ile kontrol altına alındığı incelenmektedir.

References

  • [1] https://www.worldometers.info/coronavirus, Erişim Tarihi: 19 Aralık 2020.
  • [2] Coronavirus Disease (COVID-19) Pandemic, WHO, 2020. https://www.who.int/emergencies/diseases/novel-coronavirus-2019, Erişim Tarihi: 19 Aralık 2020.
  • [3] Coronavirus (COVID-19), Hastalık Kontrol ve Önleme Merkezleri (CDC), 2020. https://www.cdc.gov/coronavirus/2019-nCoV/index.html, Erişim Tarihi: 19 Aralık 2020.
  • [4] https://www.google.com/covid19, Erişim Tarihi: 01 Ocak 2021
  • [5] https://www.bing.com/covid/, Erişim Tarihi: 01 Ocak 2021
  • [6] https://www.whitehouse.gov/briefings-statements/white-house-announces-new-partnership-unleash-u-s-supercomputing-resources-fight-covid-19/, Erişim Tarihi: 19 Aralık 2020.
  • [7] https://blog.arxiv.org/2020/03/30/new-covid-19-quick-search/, Erişim Tarihi:19 Aralık 2020.
  • [8] https://www.who.int/csr/resources/publications/surveillance/plague.pdf, Erişim Tarihi:20 Aralık 2020
  • [9] Parıldar, H., “Tarihte Bulaşıcı Hastalık Salgınları”, Tepecik Eğit. ve Araşt. Hast. Dergisi, 30:19-26, 2020.
  • [10] https://tr.euronews.com/2020/07/07/fotograflarla-1918-ispanyol-gribi-abd-salg-nlara-kars-kat-edilen-mesafeyi-sorguluyor, Erişim Tarihi:24 Mart 2021
  • [11] https://coronaboard.kr/en/, Erişim Tarihi: 24 Mart 2021
  • [12] Q. Pham, D. C. Nguyen, T. Huynh-The, W. Hwang and P. N. Pathirana, “Artificial Intelligence (AI) and Big Data for Coronavirus (COVID-19) Pandemic: A Survey on the State-of-the-Arts”, in IEEE Access, vol. 8, pp. 130820-130839, 2020, doi: 10.1109/ACCESS.2020.3009328.
  • [13] Salman Y. G., “Transforming laparoendoscopic surgical protocols during the COVID-19 pandemic; big data analytics, resource allocation and operational considerations”, International Journal of Surgery, Volume 80, Pages 21-25, ISSN 1743-9191, 2020, https://doi.org/10.1016/j.ijsu.2020.06.027.
  • [14] Z. Hu, Q. Ge, S. Li, L. Jin and M. Xiong, “Artificial intelligence forecasting of COVID-19 in China”, arXiv:2002.07112, 2020,
  • [15] IBM Releases Novel AI-Powered Technologies to Help Health and Research Community Accelerate the Discovery of Medical Insights and Treatments for COVID-19, 2020. https://www.ibm.com/blogs/research/2020/04/ai-powered-technologies-accelerate-discovery-covid-19/, Erişim Tarihi: 01 Ocak 2021
  • [16] https://covid19-hpc-consortium.org/, Erişim Tarihi: 01 Ocak 2021
  • [17] https://www.cov-irt.org/, Erişim Tarihi: 01 Ocak 2021
  • [18] https://web.archive.org/web/20191009032639/https://www.comparitech.com/vpn-privacy/the-worlds-most-surveilled-cities/, Erişim Tarihi: 01 Ocak 2021
  • [19] https://merics.org/en/report/tracing-testing-tweaking, Erişim Tarihi: 25 Aralık 2020
  • [20] https://www.cbronline.com/news/china-to-roll-out-temperature-taking-infrared-cameras, Erişim Tarihi: 01 Ocak 2021
  • [21] https://www.imf.org/en/Topics/imf-and-covid19/Fiscal-Policies-Database-in-Response-to-COVID-19, Erişim Tarihi: 01 Ocak 2021
  • [22] Demi̇rdöğmez, M., Taş, H., Gülteki̇n, N., “Koronavirüs’ün (Covid-19) E-Ticarete Etkileri”, OPUS Uluslararası Toplum Araştırmaları Dergisi, 16 (29), 1907-1927, 2020. DOI: 10.26466/opus.734477
  • [23] https://business.blogthinkbig.com/the-big-data-and-iot-applications-fighting-coronavirus/, Erişim Tarihi:02 Aralık 2020
  • [24] https://towardsdatascience.com/coronavirus-a-big-data-lesson-from-south-korea-5bb703b8b0ae, Erişim Tarihi:02 Aralık 2020
  • [25] Rastogi, Y.R., Sharma, A., Nagraik, R., Aygün, A., Şen, F., “The Novel Coronavirus 2019-Ncov: Its Evolution and Transmission into Humans Causing Global Covıd-19 Pandemic”, International Journal of Environmental Science and Technology, 17, 4381–4388., 2020. doi:10.1007/s13762-020-02781-2
  • [26] A. A. Hussain, O. Bouachir, F. Al-Turjman and M. Aloqaily, “AI Techniques for COVID-19”, IEEE Access, vol. 8, pp. 128776-128795, 2020, doi: 10.1109/ACCESS.2020.3007939.
  • [27] Robinson, K., “A False Promise of Covid-19 ‘Big’ Health Data? Health Data Integrity and The Ethics and Realities of Australia’s Health Information Management Practice”, Health Information Management Journal, 50, 9–12., 2021. doi:10.1177/1833358320941190
  • [28] P. Yu, Z. Xia, J. Fei and S. K. Jha, “An Application Review of Artificial Intelligence in Prevention and Cure of Covid-19 Pandemic”, Computers, Materials & Continua, vol. 65, no.1, pp. 743–760, 2020.
  • [29] L. Akin and M. G. Gözel, “Understanding Dynamics of Pandemics”, Turkish Journal of Medical Sciences, vol. 50, no. SI–1, pp. 515–519, 2020.
  • [30] J. Fan, B. D. Hambly, and S. Bao, “The Epidemiology of COVID-19 in the Gansu and Jinlin Provinces, China”, Frontiers in Public Health, vol. 8, 2020.
  • [31] T. Alamo, D. Reina, M. Mammarella, and A. Abella, “Covid-19: Open-Data Resources for Monitoring, Modeling, and Forecasting the Epidemic”, Electronics, vol. 9, no. 5, p. 827, 2020.
  • [32] Y. Wang, J. Li, X. Zhao, G. Feng, and X. (Robert). Luo, “Using Mobile Phone Data for Emergency Management: A Systematic Literature Review”, Information Systems Frontiers, vol. 22, no. 6, pp. 1539–1559, 2020.
  • [33] C. Zheng, X. Deng, Q. Fu, Q. Zhou, J. Feng, H. Ma, et al., “Deep Learning-Based Detection For COVID-19 From Chest CT Using Weak Label”, medRxiv, 2020.
  • [34] A. Zhavoronkov, V. Aladinskiy, A. Zhebrak, B. Zagribelnyy, V. Terentiev, D. S. Bezrukov, et al., “Potential 2019-nCoV 3C-like Protease Inhibitors Designed Using Generative Deep Learning Approaches”, Insilico Med. Hong Kong Ltd A, vol. 307, no. 2, pp. E1, 2020.
  • [35] A. Adadi and M. Berrada, “Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)”, IEEE Access, vol. 6, pp. 52138-52160, 2018.
  • [36] https://www.weforum.org/agenda/2020/04/how-next-generation-information-technologies-tackled-covid-19-in-china/, Erişim Tarihi: 01 Ocak 2021
  • [37] https://www.bbc.com/turkce/haberler-dunya-52638919, Erişim Tarihi: 01 Ocak 2021
There are 37 citations in total.

Details

Primary Language Turkish
Subjects Artificial Intelligence, Software Engineering (Other)
Journal Section Review Article
Authors

Ugur Ertoy 0000-0001-6747-9309

Muammer Akçay 0000-0003-0244-1275

Publication Date December 21, 2021
Submission Date March 2, 2021
Acceptance Date April 24, 2021
Published in Issue Year 2021

Cite

APA Ertoy, U., & Akçay, M. (2021). Covid-19 Virüsü Salgını İle Mücadelede Büyük Veri Çalışmaları: Çin Örneği. Journal of Science, Technology and Engineering Research, 2(2), 4-14. https://doi.org/10.5281/zenodo.4718425
AMA Ertoy U, Akçay M. Covid-19 Virüsü Salgını İle Mücadelede Büyük Veri Çalışmaları: Çin Örneği. JSTER. December 2021;2(2):4-14. doi:10.5281/zenodo.4718425
Chicago Ertoy, Ugur, and Muammer Akçay. “Covid-19 Virüsü Salgını İle Mücadelede Büyük Veri Çalışmaları: Çin Örneği”. Journal of Science, Technology and Engineering Research 2, no. 2 (December 2021): 4-14. https://doi.org/10.5281/zenodo.4718425.
EndNote Ertoy U, Akçay M (December 1, 2021) Covid-19 Virüsü Salgını İle Mücadelede Büyük Veri Çalışmaları: Çin Örneği. Journal of Science, Technology and Engineering Research 2 2 4–14.
IEEE U. Ertoy and M. Akçay, “Covid-19 Virüsü Salgını İle Mücadelede Büyük Veri Çalışmaları: Çin Örneği”, JSTER, vol. 2, no. 2, pp. 4–14, 2021, doi: 10.5281/zenodo.4718425.
ISNAD Ertoy, Ugur - Akçay, Muammer. “Covid-19 Virüsü Salgını İle Mücadelede Büyük Veri Çalışmaları: Çin Örneği”. Journal of Science, Technology and Engineering Research 2/2 (December 2021), 4-14. https://doi.org/10.5281/zenodo.4718425.
JAMA Ertoy U, Akçay M. Covid-19 Virüsü Salgını İle Mücadelede Büyük Veri Çalışmaları: Çin Örneği. JSTER. 2021;2:4–14.
MLA Ertoy, Ugur and Muammer Akçay. “Covid-19 Virüsü Salgını İle Mücadelede Büyük Veri Çalışmaları: Çin Örneği”. Journal of Science, Technology and Engineering Research, vol. 2, no. 2, 2021, pp. 4-14, doi:10.5281/zenodo.4718425.
Vancouver Ertoy U, Akçay M. Covid-19 Virüsü Salgını İle Mücadelede Büyük Veri Çalışmaları: Çin Örneği. JSTER. 2021;2(2):4-14.
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