In the current-generation wireless systems, there is a huge requirement on integrating big data which can able to predict the market trends of all application systems. Therefore, the proposed method emphasizes on the integration of nanosensors with big data analysis which will be used in healthcare applications. Also, safety precautions are considered when this nanosensor is integrated where depth and reflection of signals are also observed using different time samples. In addition, to analyze the effect of nanosensors, six fundamental scenarios that provide good impact on real-time applications are also deliberated. Moreover, for proving the adeptness of the proposed method, the results are equipped in both online and offline analyses for investigating error measurement, sensitivity, and permeability parameters. Since nanosensors are introduced, the efficiency of the projected technique is increased by implementing media access control (MAC) protocol with recurrent neural network (RNN). Further, after observing the simulation results, it is proved that the proposed method is more effective for an average percentile of 67% when compared to the existing methods.

中文翻译：

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大数据分析对使用神经网络的应用科学纳米传感器的影响

在当今的无线系统中，对整合能够预测所有应用系统市场趋势的大数据有着巨大的需求。因此，所提出的方法强调将纳米传感器与将用于医疗保健应用的大数据分析相结合。此外，当集成此纳米传感器时，还考虑了安全预防措施，其中还使用不同的时间样本观察了信号的深度和反射。此外，为了分析纳米传感器的效果，还考虑了对实时应用产生良好影响的六个基本场景。此外，为了证明所提出方法的适用性，在线和离线分析都配备了结果，用于调查误差测量、灵敏度和渗透率参数。由于引入了纳米传感器，通过使用循环神经网络 (RNN) 实施媒体访问控制 (MAC) 协议，可以提高预计技术的效率。此外，在观察模拟结果后，证明与现有方法相比，所提出的方法在平均百分位数为 67% 时更有效。