ABSTRACT

The need for Wireless Sensors Networks (WSNs) in real-world applications like mobiles multimedia for medical institutions is skyrocketing. Nevertheless, one of the major impediments to increased investments in this innovation is the power issue. They suggest a novel approach in this study to overcome challenges caused by restricted power sources. Rather than a binary transmitter, that uses amplitudes/ phases, modulators /demodulators units to enhance the number of bits transferred per symbol, some quaternary transceivers (in the design on the nodes of a sensor) is used. Because of the additional bits communicated by each symbol, the systems will use less power during transmitting. Furthermore, for energy-constrained WSNs, Neural Networks Statics Randomly Accesses Memories (NN-SRAM) solution in some clustered-based systems is provided. During the data's dissemination procedure, the technique minimizes overall energies usage in storage and transmissions. These neural network statics randomly accesses memory solution in some clustered bases systems decreases the energies consumptions of total systems by roughly 76.991 percent, according to simulated findings based on MATLAB as well as Spice software’s tools. Keywords: Wireless Sensor Networks; Neural Network; energy-constrained; Simulation; Healthcare
Publication date: 01/11/2021

https://ijbpas.com/pdf/2021/November/MS_IJBPAS_2021_NOV_SPCL1104.pdf

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https://doi.org/10.31032/IJBPAS/2021/10.11.1104