Wireless Body Area Network (WBAN) is a special purpose wireless sensors network designed to connect various self-autonomous medical sensors and appliances located inside and outside of human body. Interests in human Healthcare Monitoring System (HMS) are based on WBAN due to the increasing aging population and chronically ill patients at home. HMS is expected to reduce healthcare expenses by enabling the continuous monitoring of patient's health remotely in daily life activities. This research focuses on routing protocols in WBAN. The major problems in routing protocols are maximum energy consumption, path loss ratio, packet delivery ratio and maintaining stable signal to noise ratio. Real time analysis is required in HMS to support the patients through doctors, caregivers and hospital systems. Collected data is relayed by using existing wireless communication schemes towards the access point for further retransmission and processing. In this research, an Improved Quality of Service aware Routing Protocol (IM-QRP) is proposed for WBAN based HMS to remotely monitor the elderly people or chronically ill patients in hospitals and residential environments. The proposed protocol is capable to improve 10% residual energy, 30% reduction in path loss ratio, 10% improvement in packet transmission (link reliability) and 7% improvement in SNR as compared to existing CO-LEEBA and QPRD routing protocols. Convolutional Neural Network is used outside the WBAN environment to analyze the medical health records for healthcare diagnosis and intelligent decision-making.

A hybrid technique based on standard SRS modules for software requirement prioritization.