摘要
近年来,随着物联网(IoT)与5G技术的快速发展,传统林业管理正朝着智能化、自动化的方向进行变革。在智能林业生态系统中能实时地生成、分析数据,并将获取的数据传送至云服务器(CS),以此来应对诸如林业树木规模预测等复杂问题。这样的方式极大地促进林业工作者及相关利益方作出更为精准的决策,进而显著提升林业管理的效率与质量。然而,随着数据特征的日益复杂化及数据量的爆炸式增长,现有的技术手段在应对智慧林业大规模监测时无法满足高效化、精准化的需求。为解决这一问题,文章创新性地提出一种智慧林业部署方案,该方案深度融合5G技术、物联网以及深度学习技术,旨在实现对林业规模的持续、高效评估。该智慧林业部署方案采用三层体系结构,能协同作业,共同收集、处理并分析来自多种不同数据源的信息,从而全面、准确地评估林业的发展规模。
In recent years,with the rapid advancement of the Internet of Things(IoT) and 5G technology,traditional forestry management is undergoing transformation towards greater intelligence and automation.Within a smart forestry ecosystem,data is generated and analyzed in real-time,and subsequently transmitted to cloud servers(CS).This facilitates addressing complex challenges such as predicting the size of forested areas,enabling foresters and stakeholders to make more informed decisions.Consequently,this significantly enhances the efficiency and quality of forestry management.Nevertheless,as data becomes increasingly complex and volumes grow exponentially,current technologies struggle to meet the demands for high-efficiency and precision in large-scale smart forestry monitoring.To address these issues,this paper introduces an innovative smart forestry deployment strategy that integrates 5G technology,IoT,and deep learning techniques.This strategy aims to achieve continuous and efficient evaluation of forestry scales through a three-tier architecture designed to collaboratively collect,process,and analyze data from various sources,ensuring comprehensive and accurate assessments of forestry development.
作者
孔珊珊
周鹏
Kong Shanshan;Zhou Peng(Shandong Huayu University of Technology,Dezhou 253000,China)
出处
《办公自动化》
2025年第10期78-81,共4页
Office Informatization
基金
校级科技计划一般项目《基于5G的智慧林业网络部署方案研究》2023KJ106。
关键词
智慧林业
物联网
5G技术
smart forestry
Internet of Things
5G technology
作者简介
孔珊珊(1986-),女,汉族,山东鄄城人,工程师,硕士,研究方向:计算机网络技术;周鹏(1988-),男,汉族,山东淄博人,工程师,硕士,研究方向:计算机网络技术。
