Adaptive Energy Optimization Algorithm for Internet of Medical Things

Emerging trends in smart healthcare have revolutionized the medical market from child care to elderly patients. Internet of medical things (IoMT) in association with other state-of-the-art technologies playing the significant role in every field, but due to its autonomous and self-adaptive nature there is a great attention of everyone from each field particularly healthcare domain. For the disabled patients, it is very vital that a system must be self-driven and adaptive for facilitating them at every walk of their lives. In this regard, adaptive strategies with intelligent systems are the optimal solution for the medical applications. One of the critical challenges for the all miniaturized sensor devices is their resource-constrained nature while coping-up with the several issues during information exchanging and sharing knowledge with each other and intended device. Thus by keeping this dire need in mind, it is important to focus the adaptive transmission power control (TPC) based mechanism to fairly allocate the resources and facilitate the disabled patients. This paper proposes the novel adaptive energy optimization algorithm (AEOA) by adjusting the characteristics of the healthcare platform. Experimental results reveal that proposed AEOA outperforms the conventional methods by saving energy in the IoMT.