A Secure and Stable Humanoid Healthcare Information Processing and Supervisory Method with IoT-Based Sensor Network

Abstract

Nowadays, the Internet of things-(IoT-) based emerging technologies are playing a very pervasive role in healthcare systems where information is required on a real-Time basis. These systems may provide real-Time alerts with continuous monitoring to the concern in the odd conditions. Thus, these systems help the elderly and ill person with a good quality life and reduce the number of caregiver persons. Based on the above facts, this paper proposes a secure, efficient, and stable humanoid healthcare information processing and supervisory method with an IoT-based sensor network. Here, five different parameters specifically network residual energy, node density, node average energy, number of neighbors surrounded of a node, and distance between the sensor node and sink are considered for effective utilization of the energy of the sensor nodes. This method also reduces the communication distance of the nodes which helps in proficient data collection from the human body. The performance of the proposed and the existing work is considered the stability period, number of alive and dead nodes, total energy consumption, number of packets send to cluster heads, and base station metrics with two different monitoring areas. Thus, the stability period of the proposed method is increased by 144.52% with respect to the existing method protocol.