用于医疗保健应用的基于人工蜂群的无人机路由(ABCUR)算法的优化设计

IF 0.8 Q4 ROBOTICS
J. Vijitha Ananthi, P. Subha Hency Jose
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引用次数: 1

摘要

为了避免这种情况,作者提出了一种基于最优人工蜂群算法的无人机(UAV)路由算法,实现医患之间高效的数据通信。这个建议的方法分三个阶段起作用。设计/方法/方法近几十年来,无线体域网络在医疗保健应用中发挥了重要作用。它便于将患者的健康数据分析报告传送给相应的医生。在第一阶段,生物传感器通过控制节点与人体连接,收集的数据通过蓝牙传输到个人设备助理(PDA)。在第二阶段,收集的数据将使用人工蜂群算法通过物联网传输。第二种方法有助于确定最佳路线。在第三阶段,无人机将使用最佳路径将收集到的数据发送给医生、护理人员、救护车和云存储服务器。仿真结果表明,该网络的性能优于现有的方法。该算法具有较高的吞吐量、较低的时延、较高的链路速率和较高的传输速率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimal design of artificial bee colony based UAV routing (ABCUR) algorithm for healthcare applications
PurposeTo avoid this situation, the authors proposed an optimal artificial bee colony algorithm-based Unmanned Aerial Vehicle (UAV) routing algorithm for efficient data communication between doctors and patients. This proposed method worked in three stages.Design/methodology/approachIn recent decades, wireless body area networks have played an important role in health care applications. It facilitates the transmission of the patients' health data analysis report to the appropriate doctors.FindingsIn the first phase, biological sensors are connected to the human body via a controller node and collected data is transmitted via Bluetooth to the Personal Device Assistant (PDA). In the second phase, collected data will be transmitted via the Internet of things using an artificial bee colony algorithm. The second aids in determining the best route. In the third phase, unmanned aerial vehicles will use the best path to send collected data to doctors, caregivers, ambulances and cloud storage servers.Originality/valueThe simulation results show that the network's performance is superior when compared to existing approaches. The proposed algorithm achieves a high throughput, a lower delay, a higher link rate and a higher delivery rate.
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CiteScore
3.50
自引率
0.00%
发文量
21
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