Reduce energy consumption in sensors using a smartphone, smartwatch, and the use of SFLA algorithms (REC-SSS)

Abstract

Wireless body area networks are a technology for remote medical care. Because of the limited energy of the sensors, one of the problems of long-distance medical care is the high energy consumption when sending information of sensors to the sink. Choosing the proper route when sending information to the sink will reduce energy consumption and increase network lifetime. The current paper used the shuffled frog leaping algorithm (SFLA) to find an appropriate route that can send information of sensors to the lowest energy to the sink or coordinator. Also, to prevent data traffic in the sink, the sensors are divided into two groups of four. With the advent of the Internet of things and increasing use of them among people, the use of this technology has attracted the attention of remote medical care. Smartphones and smartwatches can measure information from different parts of the body, such as the heart, stroll, and glucose, based on their built-in sensors such as accelerometers, gyroscopes, and advanced cameras. These two smart devices are used in three different roles (coordinator, sink, and sensor) to improve energy efficiency in remote medical care. The paper is shown an appropriate path to reduce energy consumption in sensors using a smartphone, smartwatch, and the use of SFLA algorithms (REC-SSS). The simulation results show that the network stability increased by 12.5%,132%, and 3.5% compared to SIMPLE, M-ATTEMPT, and EERP, respectively. Also, in the proposed schema, the lifetime of the network is increased by 26% over SIMPLE, M-ATTEMPT, and EERP.