Integration of Machine Learning and IoT in Healthcare Domain

Abstract

Recent advancement in technology has been fruitful in the unification of Internet of things and machine learning in numerous domains. While IoT is involved in aggregation of data and resources, data analysis, expansion of data, learning and taking decision action on input data is taken care of by machine learning approach. The combination of these two technologies can be of great help in clinical sector in generation of a receptive and interrelated environment, thereby providing various services to healthcare staffs and patients. IoT devices are based on developing smart applications for medical usability like wearable modules, smart capsules, and sensory-based units to assist medical personnel in gathering data. Models based on machine learning are used to analyze and detect several variations in health status of a patient, suggest diagnosis methods and alternatives, thereby improving patient’s health outcome. This chapter discusses the role of machine learning as well as IoT in healthcare domain. Feasible and ongoing vital applications of both machine learning and IoT are highlighted. A framework for medical IoT along with possible solutions for medical IoT is presented. Future trends related to the integration of these two approaches are pointed out. Later an intelligent and smart prototype model for disease identification is discussed.