A Review of an Energy-Efficient Routing Algorithm for Wireless Body Area Networks Using Machine Learning

The Wireless Body Area Network (WBAN) having sensors and actuators are embedded into the human body to communicate via wearable devices in a wireless environment. Humans can wear devices into the body with various limitations. The healthcare industry plays a vital role in the WBAN to communicate and monitor the patients as a technology-based service. The sensor nodes are capable of transmitting into the human body efficiently. The nodes are communicated via wireless with the other sensors embedded in the human body. The tiny nodes having multipath communication in WBAN. In this paper, WBAN infrastructure and architecture, transmission technologies for body area networks, limitations, and energy-efficient constraints for different aspects of the routing algorithm using machine learning techniques are illustrated. It describes the energy-efficient routing protocol of WBAN is presented in this paper. Finally, as a source of motivation towards the future development of research incorporating machine learning into the supervised learning algorithms into WBAN is also provided.