Real-time monitoring Patients Using Novel RFID Network Planning Scheme

Musadaq ., Cansever G.

4 th International Iraqi Conference on Engineering Technology and its Applications (IICETA 2021), Najaf, Irak, 1 - 03 Eylül 2021, ss.1-8

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Basıldığı Şehir: Najaf
  • Basıldığı Ülke: Irak
  • Sayfa Sayıları: ss.1-8
  • Yıldız Teknik Üniversitesi Adresli: Evet

Özet

Abstract—The increasing use of the Internet of Things (IoT) in the field of health care has become one of the phenomena that play a fundamental role in modern life and which aim to preserve the safety of people. Internet of things applications in this field focus on improving public health and reducing the risks of health changes and the accompanying sudden events for patients such as the occurrence of heart attacks, as well as monitoring people with infectious diseases to know their daily activities accurately. From here emerged the importance of RFID radio monitoring systems as an effective tool in this field. This paper provides an immediate definition of radiofrequency associated with particle swarm optimization (PSO) as a patient monitoring system. The current new method for improving healthcare quality has been developed by combining the Patient Move Topology Network with the RFID Detection System. The proposed system locates the RFID readers to reveal patient tag data. This task includes three objective functions, the first one is to find the reader’s optimal number to be employed in the system, secondly, covering all patients, and the third one is to reduce the overlapping among the spread area of readers which helps with avoiding data to be confused. The algorithm that used to accomplish the goal achieved by using the pixel local neighborhood to calculate the local density range in a neighborhood around each pixel in the case study used. The result of this step will define the boundary conditions of Altinbas University as a case study for this work. Then the Monte Carlo simulation will generate random tag data. Finally, the PSO algorithm will position the readers by solving the multiobjective functionality. Experimental results show that the proposed system is capable of achieving high tag coverage for tracking and locating people with fewer readers in actual conditions.