IoT Based Indoor Disinfection Coordinating System Against the New Coronavirus
Öz
Anahtar Kelimeler
Kaynakça
- [1] N. Zhu et al., “A novel coronavirus from patients with pneumonia in China, 2019,” N. Engl. J. Med., vol. 382, no. 8, pp. 727–733, 2020.
- [2] World Health Organization (2020) Novel Coronavirus (2019-nCoV). Situation Report-51, 11 March 2020.
- [3] World Health Organization (2020) Novel Coronavirus (2019-nCoV). Situation Report-137, 5 June 2020.
- [4] H. A. Rothan and S. N. Byrareddy, “The epidemiology and pathogenesis of coronavirus disease (COVID-19) outbreak,” J. Autoimmun., vol. 109, no. February, pp. 18–21, 2020.
- [5] Y. H. Jin et al., “A rapid advice guideline for the diagnosis and treatment of 2019 novel coronavirus (2019-nCoV) infected pneumonia (standard version),” Med. J. Chinese People’s Lib. Army, vol. 45, no. 1, pp. 1–20, 2020.
- [6] T. Singhal, “A Review of Coronavirus Disease-2019 (COVID-19),” Indian J. Pediatr., vol. 87, no. 4, pp. 281–286, 2020.
- [7] World Health Organization (2020) Novel Coronavirus (2019-nCoV). Situation Report-11, 31 January 2020.
- [8] R. P. Singh, M. Javaid, A. Haleem, and R. Suman, “Internet of things (IoT) applications to fight against COVID-19 pandemic,” Diabetes Metab. Syndr., vol. 14, no. 4, pp. 521–524, 2020.
Ayrıntılar
Birincil Dil
İngilizce
Konular
Yapay Zeka, Elektrik Mühendisliği
Bölüm
Araştırma Makalesi
Yazarlar
Fırat Aydemir
*
Türkiye
Yayımlanma Tarihi
31 Aralık 2020
Gönderilme Tarihi
12 Haziran 2020
Kabul Tarihi
5 Aralık 2020
Yayımlandığı Sayı
Yıl 2020 Cilt: 4 Sayı: 2
Cited By
Anomaly Diagnosis Using Autoencoder in Edge Computing Systems
International Scientific and Vocational Studies Journal
https://doi.org/10.47897/bilmes.1132562Examining The Effect of Pre-processed Covid-19 Images On Classification Performance Using Deep Learning Method
International Scientific and Vocational Studies Journal
https://doi.org/10.47897/bilmes.1359954