Bridging FANETs and MANETs for synchronous data collection in precision agriculture activities using AirPro-FL: An energy aware fuzzy logic routing protocol

IF 6 3区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Georgios Kakamoukas , Anastasios Economides , Stamatia Bibi , Panagiotis Sarigiannidis
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引用次数: 0

Abstract

The use of Flying Ad-hoc Networks (FANETs) in precision agriculture requires the development of advanced routing protocols to manage UAV-specific challenges effectively. This paper presents AirPro-FL, a proactive routing protocol that uses fuzzy logic to optimize UAV performance in precision agriculture tasks. Unlike conventional FANET research, which often relies on stochastic mobility models that do not accurately reflect real-world agricultural missions, AirPro-FL is designed to address these gaps by enhancing UAV cooperation in scanning operations such as crop scouting, crop surveying and mapping, spraying applications, and geofencing. Traditionally, these agricultural activities rely on a single UAV, often resulting in inefficiencies. The UAV’s limited real-time data transmission capabilities, vulnerability to operational failures, and potential mission execution delays contribute to reduced overall effectiveness. The proposed system involving multiple UAVs significantly speeds up mission completion and enables real-time data transfer through the cooperation between FANETs and Mobile Ad-hoc Networks (MANETs). This innovation empowers agricultural stakeholders to make faster and more reliable decisions based on accurate data collection. Simulation results indicate that AirPro-FL consistently achieves the highest Packet Delivery Ratio (PDR) across all scenarios, halves the average end-to-end delay compared to the second-best protocol, and exhibits superior energy efficiency. The protocol’s success in optimizing data collection during scanning operations underscores its broader applicability beyond agriculture, extending to other fields such as environmental monitoring, disaster management, and surveillance, where similar mobility patterns are employed.
使用AirPro-FL桥接fanet和manet进行精准农业活动中的同步数据收集:一种能量感知模糊逻辑路由协议
在精准农业中使用飞行自组织网络(fanet)需要开发先进的路由协议,以有效地管理无人机特有的挑战。提出了一种利用模糊逻辑优化无人机在精准农业任务中的性能的主动路由协议AirPro-FL。与传统的FANET研究不同,传统的FANET研究通常依赖于不能准确反映真实农业任务的随机移动模型,而AirPro-FL旨在通过加强无人机在扫描操作中的合作,如作物侦察、作物测绘、喷洒应用和地理围栏等,来解决这些差距。传统上,这些农业活动依赖于一架无人机,往往导致效率低下。无人机有限的实时数据传输能力、易受操作故障的影响和潜在的任务执行延迟导致整体效能降低。该系统涉及多架无人机,可显著加快任务完成速度,并通过fanet和移动自组网(manet)之间的合作实现实时数据传输。这一创新使农业利益相关者能够根据准确的数据收集做出更快、更可靠的决策。仿真结果表明,与第二优协议相比,AirPro-FL在所有场景中始终实现最高的分组交付率(PDR),平均端到端延迟减少一半,并表现出优越的能源效率。该协议在优化扫描作业期间的数据收集方面的成功,突显了其在农业以外的更广泛适用性,可扩展到环境监测、灾害管理和监测等采用类似移动模式的其他领域。
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来源期刊
Internet of Things
Internet of Things Multiple-
CiteScore
3.60
自引率
5.10%
发文量
115
审稿时长
37 days
期刊介绍: Internet of Things; Engineering Cyber Physical Human Systems is a comprehensive journal encouraging cross collaboration between researchers, engineers and practitioners in the field of IoT & Cyber Physical Human Systems. The journal offers a unique platform to exchange scientific information on the entire breadth of technology, science, and societal applications of the IoT. The journal will place a high priority on timely publication, and provide a home for high quality. Furthermore, IOT is interested in publishing topical Special Issues on any aspect of IOT.
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