Abstract
References
- Mevlüt U., Uğur Ö., K. Fen and B. Dergisi, “Karadeniz Fen Bilimleri Dergisi The Black Sea Journal of Sciences,” vol. 9, no. 1, pp. 58–69, 2019.
- Yıldız M. , Bilişim Teknolojilerinin Uzman Sistem Boyutu İle Analizi, Sosyal Bilimler Meslek Yüksek Okulu Dergisi - Cilt :8 , sayı: 1-2 , sayfa : 189-212,2005.
- D. A. Uğur, “Görüntü İşlemeye Giriş Introduction to Image Processing İçerik,” pp. 1–25, 2013.
- Nursel Y., Konuşma Teorisi Ve Teknikleri, Kastamonu Eğitim Dergisi cilt:16 , No: 1 , sayfa : 249-266,Ü. Gazi, E. Sanatlar, and E. Bilgisayar,2008.
- Burçin Ataseven, Yapay Sinir Ağları İle Öngörü Modellemesi,2005.
- İsmail H. A., K. T. Üniversitesi, Bulanık Mantık : Bulanıklık Kavramı, pp. 80–85, 1999.
- Emre Ç., Destek Vektör Makinelerinin Eğitimi İçin Yeni Yaklaşımlar,2008.
- Gül G. , Çağtay T. , Uludağ G., “GENETİK ALGORİTMALAR ve UYGULAMA ALANLARI, Uludağ Üniversitesi iktisadi ve idari bilimler fakültesi sayı : 1 , sayfa 129 - 152 ,pp. 129–152, 2002.
- insanlaşan makineler ve yapay zeka, İstanbul Teknik Üniversitesi Vakfı Yayını sayı : 75, 2017.
- Muhammet A. , Enes Ç., Büyük Veri analizinde Yapay Zeka ve Makine Ögrenmesi uygulamaları, Mehmet Akif Ersoy Üniversitesi Sostal Bilimler Enstitüsü Dergisi Aralık 2017.
- Muhammet K., Ceren Ç. “ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING APPLICATIONS IN BIG DATA ANALYSIS,Mart 2020
- Seca Toker , Koronavirüs Salgını ile Mücadelede Büyük Veri Ve Yapay Zeka Çalışmaları Nisan 2020
- S.Toroman,T.B. Alakus,I. Turkoglu, Convolutional capsnet: A novel artificial neural network approach to detect COVID-19 disease from X-ray images using capsule networks, Chaos, Solitons and Fractals Nonlinear Science, and Nonequilibrium and Complex Phenomena, 13 July 202
- E. E. Hemdan, “COVIDX-Net : A Framework of Deep Learning Classifiers to Diagnose COVID-19 in X-Ray Images,” IEEE Commun. Surv. Tutorials, 2020.
- T. T. Nguyen, “Artificial Intelligence in the Battle against Coronavirus (COVID-19): A Survey and Future Research Directions,” arXiv:2008.07343v1, no. September, 2020.
- F. Shi et al., “Review of Artificial Intelligence Techniques in Imaging Data Acquisition , Segmentation and Diagnosis for COVID-19,” IEEE Rev. Biomed. Eng., pp. 1–13, 2020.
- Z. Allam, G. Dey, and D. S. Jones, “Artificial Intelligence ( AI ) Provided Early Detection of the Coronavirus ( COVID-19 ) in China and Will Influence Future Urban Health Policy Internationally,” AL,MDP, pp. 156–165, 2020.
- Z. Ceylan, “Science of the Total Environment Estimation of COVID-19 prevalence in Italy , Spain , and France,” Sci. Total Environ., vol. 729, p. 138817, 2020.
Abstract
In the course of the outbreak of coronovirus (Covid-19), which emerged in Wuhan, China at the end of 2019, and then spread all over the world, the biggest assistants in the fight against this virus were the technologies which used. Today, the areas where artificial intelligence is applied and the developments in the focus of artificial intelligence lead the technology. With Industry 4.0, there is no need for manpower to meet especially unqualified workforce in many business sectors. The idea of doing things by machines has begun to cause serious changes in the world. In order for the work to be done by the machines, importance has been given to the development of the decision making capabilities of the machines. The decision-making ability of the machines is based on previous periods. The lack of necessary computer hardware parts in testing the hypotheses made in the previous periods caused. It has not been applied in the past due to the high time and cost of hypotheses developed. Today, as a result of the rapid growth of technology, hardware elements with high processing capability can now be obtained at affordable prices. As a result of the acceleration of the developed hardware elements, many methods that took a long time in the past have reached the level that everyone can apply. We observe that what needs to be done for digital transformation in our country has been tested in many sectors. The most basic element for digital transformation is artificial intelligence technology. This is an indication that artificial intelligence technologies have started to be used in many areas of our lives. Accordingly, the use of artificial intelligence technologies in different areas, especially in medicine, played an important role in combating the epidemic during the coronavirus (Covid-19) epidemic process. In this study, the concept of artificial intelligence and the usage areas of artificial intelligence techniques are discussed in the literature section. Then, the applications developed using artificial intelligence technologies during the coronavirus (Covid-19) epidemic process were evaluated and the adequacy of the applications developed by analysing in the method section was discussed.
References
- Mevlüt U., Uğur Ö., K. Fen and B. Dergisi, “Karadeniz Fen Bilimleri Dergisi The Black Sea Journal of Sciences,” vol. 9, no. 1, pp. 58–69, 2019.
- Yıldız M. , Bilişim Teknolojilerinin Uzman Sistem Boyutu İle Analizi, Sosyal Bilimler Meslek Yüksek Okulu Dergisi - Cilt :8 , sayı: 1-2 , sayfa : 189-212,2005.
- D. A. Uğur, “Görüntü İşlemeye Giriş Introduction to Image Processing İçerik,” pp. 1–25, 2013.
- Nursel Y., Konuşma Teorisi Ve Teknikleri, Kastamonu Eğitim Dergisi cilt:16 , No: 1 , sayfa : 249-266,Ü. Gazi, E. Sanatlar, and E. Bilgisayar,2008.
- Burçin Ataseven, Yapay Sinir Ağları İle Öngörü Modellemesi,2005.
- İsmail H. A., K. T. Üniversitesi, Bulanık Mantık : Bulanıklık Kavramı, pp. 80–85, 1999.
- Emre Ç., Destek Vektör Makinelerinin Eğitimi İçin Yeni Yaklaşımlar,2008.
- Gül G. , Çağtay T. , Uludağ G., “GENETİK ALGORİTMALAR ve UYGULAMA ALANLARI, Uludağ Üniversitesi iktisadi ve idari bilimler fakültesi sayı : 1 , sayfa 129 - 152 ,pp. 129–152, 2002.
- insanlaşan makineler ve yapay zeka, İstanbul Teknik Üniversitesi Vakfı Yayını sayı : 75, 2017.
- Muhammet A. , Enes Ç., Büyük Veri analizinde Yapay Zeka ve Makine Ögrenmesi uygulamaları, Mehmet Akif Ersoy Üniversitesi Sostal Bilimler Enstitüsü Dergisi Aralık 2017.
- Muhammet K., Ceren Ç. “ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING APPLICATIONS IN BIG DATA ANALYSIS,Mart 2020
- Seca Toker , Koronavirüs Salgını ile Mücadelede Büyük Veri Ve Yapay Zeka Çalışmaları Nisan 2020
- S.Toroman,T.B. Alakus,I. Turkoglu, Convolutional capsnet: A novel artificial neural network approach to detect COVID-19 disease from X-ray images using capsule networks, Chaos, Solitons and Fractals Nonlinear Science, and Nonequilibrium and Complex Phenomena, 13 July 202
- E. E. Hemdan, “COVIDX-Net : A Framework of Deep Learning Classifiers to Diagnose COVID-19 in X-Ray Images,” IEEE Commun. Surv. Tutorials, 2020.
- T. T. Nguyen, “Artificial Intelligence in the Battle against Coronavirus (COVID-19): A Survey and Future Research Directions,” arXiv:2008.07343v1, no. September, 2020.
- F. Shi et al., “Review of Artificial Intelligence Techniques in Imaging Data Acquisition , Segmentation and Diagnosis for COVID-19,” IEEE Rev. Biomed. Eng., pp. 1–13, 2020.
- Z. Allam, G. Dey, and D. S. Jones, “Artificial Intelligence ( AI ) Provided Early Detection of the Coronavirus ( COVID-19 ) in China and Will Influence Future Urban Health Policy Internationally,” AL,MDP, pp. 156–165, 2020.
- Z. Ceylan, “Science of the Total Environment Estimation of COVID-19 prevalence in Italy , Spain , and France,” Sci. Total Environ., vol. 729, p. 138817, 2020.
Details
| Primary Language | English |
|---|---|
| Subjects | Engineering |
| Journal Section | Research Article |
| Authors | |
| Publication Date | December 31, 2020 |
| Published in Issue | Year 2020 Volume: 8 Issue: 4 |
Cite
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Akıllı Ev Sistemleri Üzerine Bir Model Önerisi
AJIT-e Online Academic Journal of Information Technology
https://doi.org/10.5824/ajite.2021.02.005.x
Address: Selcuk University, Faculty of Technology 42031 Selcuklu, Konya/TURKEY.