Publication

Abstract : The concept of smart healthcare is gradually transforming the medical unit from traditional to an efficient and convenient system. Smart healthcare employs technologies like cloud computing, big data, artificial intelligence, and internet of things. Medical robots are found to be promising in smart healthcare systems. These robots are rapidly growing in the medical system to assist the manpower effectively and efficiently. Medicine adherence is crucial to provide an effective treatment among patients. The work focuses on allocation of a specific mobile robot to provide inpatients with medicine. The system considers inpatient room in the form of 10x10 grid. The proposed system incorporates a path planning module, state of charge estimation module and a graphical user interface. The user is provided with a friendly platform to enter the destination, that corresponds to a bed location. An option to enter the obstacles to incorporate temporary arrangements is also provided on the platform. The path planning module employs the Q learning algorithm to plan the path based on the robot locations and destination. The state of charge estimation module determines the charge required to reach the destination, following the path. The robot with sufficient state of charge and best planned path is selected for the task of medicine dispensing task. The system also incorporates features to allow bots with state of charge less than minimum threshold, to head back to the base station for charging. The system finally displays the allotted robot with the remaining state of charge after the transit. The proposed system is analyzed for the effective performance under different test cases. The bot allocation system provides a promising solution by reducing human workload, risk of errors, and manpower costs, while performing on-time medicine delivery.