摘 要
森林病虫害是威胁全球森林生态系统健康和可持续发展的重要因素，传统监测手段存在效率低、覆盖范围有限及实时性不足等问题。为此，本研究旨在设计一种基于智能传感器网络的森林病虫害监测系统，以实现高效、精准和实时的监测目标。研究采用无线传感网络技术结合机器学习算法，构建了多层感知与数据处理架构，通过优化节点布局和能耗管理策略，显著提升了系统的覆盖能力和运行稳定性。实验结果表明，该系统能够准确识别多种主要病虫害类型，监测精度达到92%以上，且具备较强的环境适应能力。此外，本研究创新性地引入边缘计算技术，有效降低了数据传输延迟并提高了决策响应速度。总体而言，该设计为森林病虫害的智能化监测提供了新思路，对提升森林资源保护水平具有重要意义。关键词：森林病虫害监测; 智能传感器网络; 机器学习算法; 边缘计算; 环境适应能力
Abstract
Forest pests and diseases are significant factors threatening the health and sustainable development of global forest ecosystems. Traditional monitoring methods suffer from low efficiency, limited coverage, and insufficient real-time performance. To address these challenges, this study aims to design a forest pest and disease monitoring system based on intelligent sensor networks for achieving efficient, precise, and real-time monitoring ob jectives. By integrating wireless sensor network technology with machine learning algorithms, a multi-layer perception and data processing architecture was constructed. Through optimized node deployment and energy consumption management strategies, the system's coverage capability and operational stability were significantly enhanced. Experimental results demonstrate that the system can accurately identify various major types of forest pests and diseases, achieving a monitoring accuracy of over 92%, along with strong environmental adaptability. Additionally, this study innovatively incorporates edge computing technology, effectively reducing data transmission latency and improving decision-making response speed. Overall, this design provides new insights into the intelligent monitoring of forest pests and diseases and is of great significance for enhancing the protection level of forest resources.Key words:Forest Pest Monitoring; Intelligent Sensor Network; Machine Learning Algorithm; Edge Computing; Environmental Adaptability
目 录
摘 要 I
Abstract II
引 言 1
第1章、森林病虫害监测需求分析 3
1.1、森林生态系统特点 3
1.2、病虫害监测现状与挑战 3
1.3、智能传感器网络的必要性 4
第2章、智能传感器网络架构设计 5
2.1、网络拓扑结构选择 5
2.2、数据传输协议优化 5
2.3、能量管理策略设计 6
第3章、传感器节点功能与部署策略 7
3.1、传感器节点硬件设计 7
3.2、数据采集与预处理技术 7
3.3、节点部署与覆盖优化 8
第4章、系统性能评估与应用前景 9
4.1、监测精度与可靠性分析 9
4.2、系统成本与效益评估 9
4.3、未来发展方向探讨 9
结 论 11
参考文献 12
