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FLPSO-AMPS:一种优化的WSN模型,用于2级智慧城市的空气质量监测

Lingaraj K¹, Rashmi Laxmikant Malghan², Karthik Rao M C³

¹Department of Computer Science and Engineering, Rao Bahadur Y Mahabaleswarappa Engineering College, Ballari, 583104, Karnataka, India.

Scientific reports

|October 15, 2025

概括

本研究介绍了FLPSO-AMPS,这是一种用于空气污染监测的无线传感器网络 (WSN) 节能路由的新方法. 它提高了智能城市的网络寿命和数据可靠性.

科学领域:

计算机科学计算机科学
环境科学环境科学
网络工程网络工程

背景情况:

无线传感器网络 (WSN) 对于环境数据收集至关重要,但在能源效率,延迟和数据包丢失方面面临挑战.
现有的路由方法努力优化WSN寿命,并确保可靠的数据传输,如空气质量监测等应用程序.

研究的目的:

在基于WSN的空气污染监测系统 (APMS) 中引入FLPSO-AMPS,一种基于模糊逻辑的粒子群集优化方法,用于节能路由.
通过优化路由路径以实时收集污染物数据来提高二级智慧城市的网络寿命和性能.

主要方法:

开发了FLPSO-AMPS,集成了模糊逻辑和粒子优化 (PSO) 以实现智能路由路径选择.
集成实时污染物数据和移动意识优化,以提高WSN性能.

主要成果:

与现有方法相比,FLPSO-AMPS在模拟中表现出优异的性能.
实现了显著的改进:能源效率提高10%,任务延迟减少15%,数据包交付率 (PDR) 增加24.5%,数据包丢失率 (PLR) 减少11.5%,吞吐量减少20.1%.

结论:

FLPSO-AMPS为智能城市的智能,资源高效的空气质量监测提供了一个潜在的框架.
这种方法提高了APMS的网络寿命和数据传输可靠性.

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