Smart Environmental Monitoring System Using Enhanced Bayes Bayesian Optimized Platform Robotics

Abstract

The two types of environments that affect skin wound healing are the internal environment, which is the environment of the neighboring portion beneath the wound site, and the exterior, which is close to the wound surface. Both kinds of environments are important for wound healing and might result in continual or sluggish wound healing. Although other earlier research offered wound care remedies, they concentrated on a specific environmental component, such as the pH value, moisture content of the wound, or healing enzymes. Realistically speaking, evaluating environmental impact based on the identification of one or two criteria is meaningless because both types of environments have a large number of additional aspects that must be taken into account during the inquiry. Moreover, prior research did not categorize general healing as being continuous or impeded based on the influence of the external environment. In this study, we suggested an innovative radial support vector machine with enhanced Bayesian optimization (R-SVM+EBO) approach for outside monitoring the environment to take into account the impact of the external environment on the recovery process of wounds. By giving patients a smart wound management tool to track and supervise wound healing from house, this study helps patients. When compared to other methods for smart environmental monitoring, the suggested method achieves the best performance.