Development of an Innovative Optimal Route Selection Model Based on an Improved Multi-Objective Genetic Algorithm (IMOGA) Method in IoT Healthcare

One of the most widely used IoT applications, healthcare aims to reduce the need for hospitalisation by monitoring patients' vital signs throughout the day for several weeks. Many sensors, including as vital and unstructured message sensors as well as environmental monitoring sensors, are deployed in healthcare systems to collect patient information and lower costs for the patients. Several issues along the transmission channel could result in the loss of data gathered by sensors integrated into medical equipment. In order to identify nearly optimal routes and create a cutting-edge optimal route selection model for IoT healthcare, this article employs the Improved Multi-Objective Genetic Algorithm (IMOGA) technique. For a variety of causes, data transmitted by sensors integrated into medical equipment may be lost. As a result, creating a safe communication method in IoT networks is crucial for the healthcare industry. As a result, the best path for medical data is chosen while taking energy, distance, and delay into account. The performances of the adopted work are then contrasted. According on experimental findings, Energy, distance, and delay have all been improved by the suggested strategy by 14%, 2%, and 5.6%, respectively.