School of Computer Sciences and Engineering, Sandip University, Nashik 422213, India.
Faculty of Information Technology, City University, Petaling Jaya 46100, Malaysia.
Sensors (Basel). 2022 Jul 28;22(15):5654. doi: 10.3390/s22155654.
The world is advancing to a new era where a new concept is emerging that deals with "wirelessness". As we know, renewable energy is the future, and this research studied the integration of both fields that results in a futuristic, powerful, and advanced model of wireless body area networks. Every new emerging technology does have some cons; in this case the issue would be the usage of excess energy by the sensors of the model. Our research is focused on solving this excessive usage of energy to promote the optimization of energy. This research work is aimed to design a power-saving protocol (PSP) for wireless body area networks (WBANs) in electronic health monitoring (EHM). Our proposed power-saving protocol (PSP) supports the early detection of suspicious signs or sporadic elder movements. The protocol focuses on solving the excessive energy consumption by the body attached to IoT devices to maximize the power efficiency (EE) of WBAN. In a WSNs network, the number of sensor nodes (SNs) interact with an aggregator and are equipped with energy harvesting capabilities. The energy optimization for the wireless sensor networks is a vital step and the methodology is completely based on renewable energy resources. Our proposed power-saving protocol is based on AI and DNN architectures with a hidden Markov model to obtain the top and bottom limits of the SN sources and a less computationally challenging suboptimal elucidation. The research also addressed many critical technical problems, such as sensor node hardware configuration and energy conservation. The study performed the simulation using the OMNET++ environment and represent through results the source rate to power critical SNs improves WBAN's scheme performance in terms of power efficiency of Sporadic Elder Movements (SEM) during various daily operations.
世界正在迈向一个新时代，一个新的概念正在出现，即处理“无线”。众所周知，可再生能源是未来，这项研究研究了这两个领域的融合，从而产生了一种未来主义、强大和先进的无线体域网模型。每一项新兴技术都有一些缺点；在这种情况下，问题将是模型传感器的能源消耗过多。我们的研究集中在解决这个能源过度消耗的问题，以促进能源优化。这项研究工作旨在为电子健康监测（EHM）中的无线体域网（WBAN）设计一种节能协议（PSP）。我们提出的节能协议（PSP）支持早期检测可疑迹象或零星老人运动。该协议专注于解决物联网设备附着的身体消耗过多的能量，以最大限度地提高 WBAN 的功率效率（EE）。在 WSNs 网络中，传感器节点（SNs）的数量与聚合器相互作用，并配备了能量收集能力。无线传感器网络的能量优化是一个至关重要的步骤，方法完全基于可再生能源。我们提出的节能协议基于人工智能和 DNN 架构，具有隐马尔可夫模型，以获得 SN 源的上限和下限，以及计算上较少挑战的次优阐明。该研究还解决了许多关键技术问题，例如传感器节点硬件配置和节能。该研究使用 OMNET++环境进行了仿真，并通过结果表示，提高了关键 SN 源的源速率，从而提高了 WBAN 在各种日常操作中突发老人运动（SEM）的功率效率方案性能。
