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RFID Sensör Etiketleri Kullanarak Vücut Sıcaklığı İle İlgili Risk Faktörü Değerlendirmesi

Yıl 2023, Cilt: 38 Sayı: 2, 585 - 592, 28.07.2023
https://doi.org/10.21605/cukurovaumfd.1334191

Öz

Yüksek vücut sıcaklığına sahip kişilerin tespit edilmesi ve tanımlanması, COVID-19 gibi vücut sıcaklığının belirtisi olan hastalıkların yayılmasını önlemede kritik önem taşır. Yükselmiş vücut sıcaklığını tanımlamak için termal kameralar veya manuel sıcaklık kontrol yöntemleri yaygın olarak kullanılır. Bu çalışmada, belirli bir toplulukta her bir kişinin vücut sıcaklığındaki değişimi ve aile geçmişi, alışkanlıklar ve sosyal yaşam gibi diğer risk faktörleri dahil olmak üzere daha yüksek hastalık riski taşıyan insanların tanımlanmasını ve izlenmesini amaçlayan yeni bir yöntem sunuyoruz. Sonuçlar, her bir kullanıcının RFID okuyucularıyla donatılmış belirli yerlerden geçtiği her seferinde kullanıcının kimlik numarasıyla birlikte vücut sıcaklığının izlenebileceği ve kaydedilebileceğini göstermektedir. Yapay zeka destekli risk puanlama sistemi kullanılarak, tanımlanmış parametrelere göre bir risk faktörü değerlendirilir. Kullanıcının değerlendirilen risk puanı belirli bir değerin üstünde ise, sistem yüksek riskli skorlu kişiyi izole etme alarmı üretir. Bu nedenle, potansiyel olarak enfekte olabilecek herhangi bir kişinin izole edilmesi, sağlık profesyonellerinin enfeksiyonların yayılmasını izole topluluklar aracılığıyla azaltmasına yardımcı olur.

Kaynakça

  • 1. Landt, J., 2005. The History of RFID. IEEE Potentials, 24(4), 8-11.
  • 2. Baumbauer, C.L., Anderson, M.G., Ting, J., 2020. Printed, Flexible, Compact UHF-RFID Sensor Tags Enabled by Hybrid Electronics. Sci Rep 10, 16543.
  • 3. Jeong, J.Y., Yeo, J., Lee, H.S., Pyo, C.S., 2007. Technology Trend of RFID Sensor Tags. Electronics and Telecommunications Trends, 22(3), 38.
  • 4. Catarinucci, L., Colella, R., Consalvo, S.I., Patrono, L., Rollo, C., Sergi, I., 2020. Iot-Aware Waste Management System Based on Cloud Services and Ultra-Low-Power RFID Sensor-Tags. IEEE Sensors Journal, 20( 24), 14873-14881.
  • 5. Colella, R., 2021. Design Of UHF RFID Sensor-Tags For The Biomechanical Analysis of Human Body Movements. IEEE Sensors Journal, 21(13), 14090-14098.
  • 6. Mejjaouli, S., Babiceanu, R.F., Nisanci, I., 2014. The use of RFID Sensor Tags for Perishable Products Monitoring in Logistics Operations. Proceedings of The Winter Simulation Conference, Georgia, 2001-2012,
  • 7. Toda, T., Shinomiya, N., 2019. Machine Learning-Based Fall Detection System for the Elderly using Passive RFID Sensor Tags. 13th International Conference On Sensing Technology (ICST), Sydney, Australia, 1-6.
  • 8. Che, Z., Deng, F., He, Y., Liang, Z., Fu, Z., Zhang, C., 2018, A Self-Powered RFID Sensor Tag for Long-Term Temperature Monitoring in Substation, J Electr Eng Technol., 13(1), 501-512
  • 9. Chen, X., Liu, J., Xiao, F., Chen, S., Chen, C., 2021. Thermotag: Item-Level Temperature Sensing with a Passive RFID Tag. Proceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services (Mobisys '21). New York, USA, 163-174.
  • 10. Catarinucci, L., Colella, R., Esposito, A., 2012. RFID Sensor-Tags Feeding a Context-Aware Rule-Based Healthcare Monitoring System. J Med Syst 36, 3435-3449.
  • 11. Catarinucci, L., Colella, R., Esposito, A., Tarricone, L., Zappatore, M., 2009. A Context-Aware Smart Infrastructure Based on RFID Sensor-Tags and Its Application to the Health-Care Domain. IEEE Conference on Emerging Technologies & Factory Automation, Spain, 1-8.
  • 12. Benouakta, S., Hutu, F., Duroc, Y., 2021. Passive UHF RFID Yarn for Temperature Sensing Applications. RFID-TA. 11th IEEE International Conference on RFID Technology and Applications, Delhi, India, 1-3.
  • 13. Guangwei, L., 2014. Locatable-Body Temperature Monitoring Based on Semi-Active UHF RFID Tags. Sensors, 14, 5952-5966.
  • 14. Rashee, A., Iranmanes, E., Li, W., Fen, X., Andrenk, A.S., Wan, K., 2017. Experimental Study of Human Body Effect on Temperature Sensor Integrated RFID Tag. IEEE International Conference on RFID Technology & Application, Poland, 243-247.
  • 15. EPC Radio-Frequency Identity Protocols Class-1 Generation-2 UHF RFID Protocol for Communications At 860 Mhz - 960 Mhz, Epcglobal Inc. www.Epcglobalinc.Org, Erişim Tarihi: 31 Ocak 2005.
  • 16. Braun, W.V., 2018. Passive UHF RFID 915mhz EPC Gen2v2 and ISO/IEC 29167-10 with I2C Interface and Temperature Sensor. NMV2D Datasheet, 10.
  • 17. Burkov, A., 2019. The Hundred-Page Machine Learning Book. 1st Ed.; Andriy Burkov: Quebec, Canada, 160.
  • 18. Ghasemkhani, B., Yilmaz, R., Birant, D., Kut, R.A., 2022. Machine Learning Models for the Prediction of Energy Consumption Based on Cooling and Heating Loads in Internet-of-Things-Based Smart Buildings. Symmetry, 14(8), 1553.
  • 19. Kang, Z., Catal, C., Tekinerdogan, B., 2020. Machine Learning Applications in Production Lines: A Systematic Literature Review. Comput Ind Eng, 149, 106773.

Body Temperature Related Risk Factor Assessment Using RFID Sensor Tags

Yıl 2023, Cilt: 38 Sayı: 2, 585 - 592, 28.07.2023
https://doi.org/10.21605/cukurovaumfd.1334191

Öz

Detecting and identifying individuals with high body temperature can be critical for preventing the spread of diseases with high body temperature as a symptom like COVID-19. Thermal cameras or manual temperature inspection methods are widely used to identify elevated body temperature. In this work, we propose a novel method to identify and track people with higher disease risk, including the body temperature change of each person in a specified community and other risk factors like family backgrounds, habits, and social life. Results show that each person's body temperature can be tracked and recorded with the user’s ID number every time the user passes from specific locations equipped with RFID readers. By using an artificial intelligence-supported risk scoring system, a risk factor is evaluated based on the parameters defined accordingly. If the evaluated risk score of the user is above a specific value, the system generates an alarm to isolate the person with a high-risk score. Therefore, isolating any potentially infected individual helps health professionals reduce the spreading speed of infections through isolated communities.

Kaynakça

  • 1. Landt, J., 2005. The History of RFID. IEEE Potentials, 24(4), 8-11.
  • 2. Baumbauer, C.L., Anderson, M.G., Ting, J., 2020. Printed, Flexible, Compact UHF-RFID Sensor Tags Enabled by Hybrid Electronics. Sci Rep 10, 16543.
  • 3. Jeong, J.Y., Yeo, J., Lee, H.S., Pyo, C.S., 2007. Technology Trend of RFID Sensor Tags. Electronics and Telecommunications Trends, 22(3), 38.
  • 4. Catarinucci, L., Colella, R., Consalvo, S.I., Patrono, L., Rollo, C., Sergi, I., 2020. Iot-Aware Waste Management System Based on Cloud Services and Ultra-Low-Power RFID Sensor-Tags. IEEE Sensors Journal, 20( 24), 14873-14881.
  • 5. Colella, R., 2021. Design Of UHF RFID Sensor-Tags For The Biomechanical Analysis of Human Body Movements. IEEE Sensors Journal, 21(13), 14090-14098.
  • 6. Mejjaouli, S., Babiceanu, R.F., Nisanci, I., 2014. The use of RFID Sensor Tags for Perishable Products Monitoring in Logistics Operations. Proceedings of The Winter Simulation Conference, Georgia, 2001-2012,
  • 7. Toda, T., Shinomiya, N., 2019. Machine Learning-Based Fall Detection System for the Elderly using Passive RFID Sensor Tags. 13th International Conference On Sensing Technology (ICST), Sydney, Australia, 1-6.
  • 8. Che, Z., Deng, F., He, Y., Liang, Z., Fu, Z., Zhang, C., 2018, A Self-Powered RFID Sensor Tag for Long-Term Temperature Monitoring in Substation, J Electr Eng Technol., 13(1), 501-512
  • 9. Chen, X., Liu, J., Xiao, F., Chen, S., Chen, C., 2021. Thermotag: Item-Level Temperature Sensing with a Passive RFID Tag. Proceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services (Mobisys '21). New York, USA, 163-174.
  • 10. Catarinucci, L., Colella, R., Esposito, A., 2012. RFID Sensor-Tags Feeding a Context-Aware Rule-Based Healthcare Monitoring System. J Med Syst 36, 3435-3449.
  • 11. Catarinucci, L., Colella, R., Esposito, A., Tarricone, L., Zappatore, M., 2009. A Context-Aware Smart Infrastructure Based on RFID Sensor-Tags and Its Application to the Health-Care Domain. IEEE Conference on Emerging Technologies & Factory Automation, Spain, 1-8.
  • 12. Benouakta, S., Hutu, F., Duroc, Y., 2021. Passive UHF RFID Yarn for Temperature Sensing Applications. RFID-TA. 11th IEEE International Conference on RFID Technology and Applications, Delhi, India, 1-3.
  • 13. Guangwei, L., 2014. Locatable-Body Temperature Monitoring Based on Semi-Active UHF RFID Tags. Sensors, 14, 5952-5966.
  • 14. Rashee, A., Iranmanes, E., Li, W., Fen, X., Andrenk, A.S., Wan, K., 2017. Experimental Study of Human Body Effect on Temperature Sensor Integrated RFID Tag. IEEE International Conference on RFID Technology & Application, Poland, 243-247.
  • 15. EPC Radio-Frequency Identity Protocols Class-1 Generation-2 UHF RFID Protocol for Communications At 860 Mhz - 960 Mhz, Epcglobal Inc. www.Epcglobalinc.Org, Erişim Tarihi: 31 Ocak 2005.
  • 16. Braun, W.V., 2018. Passive UHF RFID 915mhz EPC Gen2v2 and ISO/IEC 29167-10 with I2C Interface and Temperature Sensor. NMV2D Datasheet, 10.
  • 17. Burkov, A., 2019. The Hundred-Page Machine Learning Book. 1st Ed.; Andriy Burkov: Quebec, Canada, 160.
  • 18. Ghasemkhani, B., Yilmaz, R., Birant, D., Kut, R.A., 2022. Machine Learning Models for the Prediction of Energy Consumption Based on Cooling and Heating Loads in Internet-of-Things-Based Smart Buildings. Symmetry, 14(8), 1553.
  • 19. Kang, Z., Catal, C., Tekinerdogan, B., 2020. Machine Learning Applications in Production Lines: A Systematic Literature Review. Comput Ind Eng, 149, 106773.
Toplam 19 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Akış ve Sensör Verileri, Elektronik
Bölüm Makaleler
Yazarlar

Reyat Yılmaz Bu kişi benim 0000-0001-9108-0576

Özgür Tamer Bu kişi benim 0000-0002-5776-6627

Recep Alp Kut Bu kişi benim 0000-0002-5781-334X

Nihal Fidan Bu kişi benim 0009-0008-4905-2967

Yayımlanma Tarihi 28 Temmuz 2023
Yayımlandığı Sayı Yıl 2023 Cilt: 38 Sayı: 2

Kaynak Göster

APA Yılmaz, R., Tamer, Ö., Kut, R. A., Fidan, N. (2023). Body Temperature Related Risk Factor Assessment Using RFID Sensor Tags. Çukurova Üniversitesi Mühendislik Fakültesi Dergisi, 38(2), 585-592. https://doi.org/10.21605/cukurovaumfd.1334191