# Sensors Energy Optimization for Renewable Energy-Based WBANs on Sporadic Elder Movements
## 3 Power Consumption Aspect in WBAN  
The WBAN nodes should consume as little power as possible in order to extend the network's lifespan and improve its stability. As the WBAN would use renewable energy, we must understand why we need to add the energy optimization feature in the model. The energy might be abundant, but while marking a model as ideal, we check some standards. For example, out of the given models which gives the most efficient output while being energy conservative. Such models are best for the longer run and promote energy conservation, model stability and energy optimization. In our case, the sensors might be one of the components which could be using energy a lot more than they actually need to or possibly the energy is not optimally used by the sensors and so the study addresses the uses and suggests some possible solutions. Using energy-efficient routing algorithms, we sought to reduce the WBAN's power usage as much as possible in this section of the paper. Due to inherited difficulties and specifications, existing routing protocols for wireless sensor networks and mobile ad hoc networks do not work efficiently with WBAN. Figure 1 shows the WBAN routing protocols that are now in use, followed by a review of the various routing protocols that have been established so far. When using the Quality of Service Conscious (QSC) Routing Protocol, a modular strategy-based protocol can increase parameters like dependability and packet delivery \begin{table}
\begin{tabular}{c c c} \hline \hline
**Study** & **Primary Purpose of Study** & **Methodology Used** \\ \hline [PERSON], et al., 2020 [26] & To increase the efficiency of rotor speed for generation of wind energy. & Optimal torque control method’s (OPT) efficiency is better than other methods. \\ \hline [PERSON] et al., 2015 [27] & To elevate the levels of energy optimization for Wireless Sensor Networks (WSN) where energy level is highly unstable. & Lyapunov drift-plus-penalty with perturbation technique is applied to obtain more persistent results. \\ \hline [PERSON] et al., 2021 [28] & To propose scheme of hybrid-diode topology for Solar energy based WSN. & To optimize the energy levels, one-port hybrid diode topology is used. \\ \hline [PERSON] et al., 2021 [29] & To tackle the major issues for developing mobile wind turbine systems. & The sensor readings for wind speed are collected using drone-based networking units. \\ \hline [PERSON] et al., 2021 [30] & To build a system for low level energy harvesting. & Lyapunov drift-plus-penalty with perturbation technique is applied to obtain more persistent results. \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Comparative study for analysis of power optimization for low-energy based sensor used in wireless sensor networks. Figure 1: Routing protocol of WBAN. ratio [31]. These interconnected modules provide various challenges to the WBAN system's design. In WBAN, biomedical sensors that detect changes in body temperature are placed inside or on the patient. Wireless communication generates magnetic and electric fields through radio transmissions. Absorption, power consumption, and the circuitry of the node all contribute to an increase in temperature when radio signals are present [32]. Consequently, the human body is vulnerable to the effects of these electromagnetic waves. In order to minimize the effects of the magnetic and electric fields generated by sensors, several approaches [33] have been developed. The use of computer clusters as the basis for the routing protocol (CBRP) nodes in this third type of routing protocol technique are used to form small clusters, and each cluster is led by a single cluster head. The only means to communicate with the base station is through this cluster head. This has resulted in a reduction in the amount of communication between sensors and base stations. Routing based on postural movement-based routing protocol (PMBRP) Postural movement introduces discontinuity issues into any relationship between two sensor nodes.