Machine learning based robotic End Effector System for Monitoring and Control of External Bleeding of Vehicle Accident Victims, Review Paper

Abstract

Vehicle accidents are on the rise in the roads due to over speeding, poor roads, and misjudgment during driving, not forgetting overloading and lack of proper vehicle maintenance. Private transport has increased rapidly, thereby resulting in many accidents on the roads. Whenever there is an accident, it has been realized that some accident victims who would have survived the accident end up dead due to continuous bleeding. As a result, many lives are lost because of a lack of emergency measures to avoid that constant loss of blood through external bleeding. In this regard, there is a need to design a robotic system based on machine learning (ML) to monitor and control the external bleeding from vehicle accident victims in the shortest possible time through the utilization of software such as SolidWorks, Matlab, and proteus. The nanotechnology-based system interfaced with the robotic end-effector shall be used to apply to stop gel through the utilization of Comsol software. The robotic system shall be integrated with a monitoring system for precise and useful quantification of the bleeding wound, thus the importance of machine learning to achieve accurate information. Keyword : Robotic end effector, Machine Learning, nanotechnology, monitoring of external bleeding.