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Coupled IoT and artificial intelligence for having a prediction on the bioengineering problem

  • Chunping Wang (Shanghai Technical Institute of Electronics & Information) ;
  • Keming Chen (Shanghai Technical Institute of Electronics & Information) ;
  • Abbas Yaseen Naser (Information Technology Unit, Al mustaqbal University College) ;
  • H. Elhosiny Ali (Research Center for Advanced Materials Science (RCAMS), King Khalid University)
  • Received : 2021.07.15
  • Accepted : 2023.01.10
  • Published : 2023.02.25
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Abstract

The vibration of microtubule in human cells is the source of electrical field around it and inside cell structure. The induction of electrical field is a direct result of the existence of dipoles on the surface of the microtubules. Measuring the electrical fields could be performed using nano-scale sensors and the data could be transformed to other computers using internet of things (IoT) technology. Processing these data is feasible by artificial intelligence-based methods. However, the first step in analyzing the vibrational behavior is to study the mechanics of microtubules. In this regard, the vibrational behavior of the microtubules is investigated in the present study. A shell model is utilized to represent the microtubules' structure. The displacement field is assumed to obey first order shear deformation theory and classical theory of elasticity for anisotropic homogenous materials is utilized. The governing equations obtained by Hamilton's principle are further solved using analytical method engaging Navier's solution procedure. The results of the analytical solution are used to train, validate and test of the deep neural network. The results of the present study are validated by comparing to other results in the literature. The results indicate that several geometrical and material factors affect the vibrational behavior of microtubules.

Keywords

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