Application of Falcon Artificial Neural Networks and Fuzzy Inference System (F-ANFIS) for Designing an Internet-of-Things Based Business Model in the Field of Telemedicine

The main purpose of this study is to use Falcon's artificial neural networks and fuzzy inference system to designing an IOT-based business model in telemedicine at the National Institute of Medical Research Development of Iran. In fact, the research fatigue of NIMAD decision makers and physicians can be explained by the combining different ways of designing an IOT-based business model in telemedicine. In addition the need to use the T-MEDICINE+IOT.F-ANFIS system to increase confidence and reliability in Decision making, as well as the issue of the need for multiple expertise through the simultaneous using multi-disciplinary knowledge of different areas to solve the problem of internet of things-based business model. In this study, the Matlab R2017b programming environment was applied to design an Expert system based on Falcon neural networks. Finally, using the T-MEDICINE+IOT.F-ANFIS system outputs, the status of "IOT-based business model in telemedicine" can be analyzed based on variables such as following items: Using IOT in telemedicine; the ability to managing devices; The IOT networks position; IOT security; the degree of familiarity with the analyzing IOT applications. In fact, the final difference between the analyzing the outputs of the Expert system based on Falcon neuro-fuzzy system of this study, and the average views of Telemedicine physicians and IOT-based business model specialists, It is not significant and it equals to 0.065.