基于无线传感器网络的温室环境监控系统设计

针对温室环境监控的需要,基于无线传感器网络的特点,设计了面向温室环境的自动监控系统。给出了系统结构,详述了温室环境中无线传感网络的覆盖算法及数据融合算法,结合GPRS网络,实现了信息的远程共享,实验证明该系统能够实时监测温室环境中温湿度等环境参数,能较好地满足温室环境监控的应用需求。     

基于s3c6410的温室环境监控系统的设计

本文根据温室系统的需求,设计了基于s3c6410微处理器的温室环境监控系统。描述了温室监控系统的整体结构,介绍了linux下底层驱动的编写和温室环境因子的控制。该系统采用Linux操作系统,运行可靠性高、稳定性强,在温室中有很好的应用前景。     

温室环境无线监控系统设计

为提高温室环境监控的效率,针对传统的有线温室监控系统接线复杂和节点放置不灵活等缺点,提出一种基于无线传感器网络的温室环境监控系统的方案,并详细给出主节点和子节点的软硬件设计方案。试验结果表明,系统具有运行可靠、成本低、组网灵活以及人机交互界面友好等特点,实现了温室环境的本地监控和远程监控,能够满足当前我国温室环境监控的实际需要。     

基于无线传感网的温室大棚智能监控系统的研究

为了实现对温室大棚环境数据的有效监控,设计了基于无线传感网络的智能监控系统.系统的无线传感网络采用层次结构的路由协议,针对LEACH分簇算法和PEGASIS链路算法进行了融合和改进,提出了一种适用于温室大棚的链簇式路由协议.无线传感节点的设计采用了无线收发芯片nRF24L01+和微控制器STM32,汇聚节点可通过GPRS模块将环境数据上传到远端上位机PC,从而实现数据的远程监控、存储和图表分析显示等功能.     

基于PSO-BP数据融合的环境监控系统设计

传统的温室大棚监控系统一般都采用手动布线,存在控制难度大、成本高等问题,已不能满足农业发展的需求。针对上述问题,该文设计了一款基于PSO-BP的无线温室大棚环境监控系统。在大棚内部署Zig Bee传感器节点网络采集环境信息,利用ECDS算法选择路由节点。同时为了能够直观地展示大棚内各环境信息的分布情况,使用Kriging方法构建环境信息分布图。构造了反馈调节系统:由于大棚的各因数之间是相互作用的,为了有一个准确的决策结果,该系统将BP神经网络和PSO算法结合。利用改进后算法良好的映射能力和优化能力,对温室数据进行融合,精确决策。实验结果表明,该系统能够合理分配路由节点节省网络开销,较好地展示环境信息分布情况,同时能够精确地调节大棚环境。     

基于无线传感器网络的温室环境监控系统研究

为在完成温室内环境参数的自动采集和调控,设计了基于无线传感器网络的温室环境监控方案.介绍了温室监控系统整体结构,分析了基于CC2431无线传感器网络节点的硬件设计,并在此基础上进行了TinyOS操作系统的移植和节点的软件设计.由于该无线传感器网络节点具有功耗低、体积小、工作可靠、易于扩展等优点,基于该无线传感器网络的温室环境监控方案有很好的应用前景.     

基于ZigBee的温室环境无线测控系统

为了实现温室大棚环境的无线、远程实时监控,提出了一种以CC2430芯片为核心的ZigBee温室环境无线测控系统。描述了终端节点、路由节点和协调器节点的硬件组成和软件流程,并应用改进的Cluster-Tree路由算法组成ZigBee无线传感网络,实现数据的无线传输。利用串口通信技术实现无线传感网络与Yeelink物联网平台的通信,管理者可远程登陆Yeelink平台和手机APP查看温室环境信息以及控制节点状态。经实验测试,大棚内无线节点间的通信距离约80米,并且实现了光强、空气温湿度及土壤湿度的监控。测试表明系统构建简单,稳定可靠,为智能农业的设计提供了参考。     

双协议融合的WSNs温室环境监控系统设计

针对温室环境数据无线采集、视频监控及远程管理的需求,设计了一种基于无线传感器网络（ WSNs）的智能温室环境监控系统。系统采用ZigBee和WiFi融合通信技术组成智能网关,其中,ZigBee无线通信设备用于采集温室环境数据,WiFi通信设备用于无线视频传输和远程通信。所设计系统既避免了传统温室环境有线监控安装和维护的繁琐,同时解决了ZigBee WSNs传输速率较低、无线传输距离较近的缺点,温室环境监控功能得到拓展。经过测试验证,正常情况下网络丢包率小于1%,系统实现了温室环境远程监控管理的各项性能,具有良好的应用性和可扩展性。     

基于CANopen协议的温室环境控制系统设计与实现

设计了一种基于CANopen协议的温室环境测控系统。该系统由上位监控主站、下位数据采集从站以及下位控制输出从站组成,并运用VB软件开发了应用程序和人机交互界面。测试结果表明,该系统可以实时、稳定地实现温室环境各环境因子数据的采集、处理、显示、存储、逻辑算法、控制输出等功能,同时能可靠地控制温室各调控设备的启动和停止,实现了对温室内温、光、湿、气、肥等环境因子的自动测量与控制,提高了温室环境测控的自动化水平。     

基于作物生长模型的WSN温室环境智能监控系统

实现一种结合作物生长模型和无线传感网技术的应用于温室环境的智能监控系统。在环境监控中,为了解决温室监控范围广导致的节点能量消耗大等问题,设计了适合大规模温室环境监控的基于分簇的低功耗网络通信协议。主要以番茄为研究对象。智能决策的依据是番茄生长模拟模型。根据模型能预测番茄的发育期,进而对处于不同发育期的温室做出决策。     

Coordination control of greenhouse environmental factors

Optimal control of greenhouse climate is one of the key techniques in digital agriculture. Greenhouse climate, a nonlinear and uncertain system, consists of several major environmental factors such as temperature, humidity, light intensity, and CO₂ concentration. Due to the complex coupled correlations, it is a challenge to achieve coordination control of greenhouse environmental factors. This paper proposes a model-free coordination control approach for greenhouse environmental factors based on Q-learning. Coordination control policy is found through systematic interaction with the dynamic environment to achieve optimal control for greenhouse climate with the control cost constraints. In order to decrease systematic trial-and-error risk and reduce the computational complexity in Q-learning algorithm, case-based reasoning (CBR) is seamlessly incorporated into the Q-learning process. The experimental results demonstrate that this approach is practical, highly effective and efficient.     

一种利用HY-2卫星扫描微波辐射计数据反演极地海冰密集度的算法

海洋二号卫星(HY-2)是中国第一颗海洋动力环境监测卫星,如何有效地利用海洋二号卫星扫描辐射计数据监测海冰成为亟待解决的问题。根据海冰与海水辐射特征,提出一种基于多频段双极化反演海冰密集度方法,该方法利用简化的辐射传输模型和地物参考点模拟亮温并逼近观测亮温。该方法与NASA Team 2和ABA算法具有很好的可比性。应用该方法,可以有效利用HY-2卫星反演海冰密集度,监测海冰边缘与面积变化。     

基于ZigBee的温室环境监测系统的设计

本文基于ZigBee无线传输协议和CC2430芯片设计了一款温室大棚的环境监测系统。采用CC2430无线传输芯片作为环境数据采集的节点,并使用该芯片作为路由器和协调器,将采集到的环境数据传输到总监测室,方便对各个温室的环境进行观测,并可以随着温室规模的大小,扩大或者缩减网络的大小。     

A long short-term memory-based model for greenhouse climate prediction

Greenhouses can grow many off-season vegetables and fruits, which improves people's quality of life. Greenhouses can also help crops resist natural disasters and ensure the stable growth of crops. However, it is highly challenging to carefully control the greenhouse climate. Therefore, the proposal of a greenhouse climate prediction model provides a way to solve this challenge. We focus on the six climatic factors that affect crops growth, including temperature, humidity, illumination, carbon dioxide concentration, soil temperature and soil humidity, and propose a GCP_lstm model for greenhouse climate prediction. The climate change in greenhouse is nonlinear, so we use long short-term memory (LSTM) model to capture the dependence between historical climate data. Moreover, the short-term climate has a greater impact on the future trend of greenhouse climate change. Therefore, we added a 5-min time sliding window through the analysis experiment. In addition, sensors sometimes collect wrong climate data. Based on the existence of abnormal data, our model still has good robustness. We experienced our method on the data sets of three vegetables: tomato, cucumber and pepper. The comparison shows that our method is better than other comparison models.     

档案库房温湿度调控方法研究

对档案库房的温湿度进行监控并调节有助于各种类型档案的长久保存.文章重点研究了无线智能温湿度监控系统中用户终端的温湿度调控方法,根据本地气候变化特点,设计了一种简单有效的温湿度监控及调控算法.该算法借助单片机及各种调温装置,可以实现各种情况下的报警和温度调控.经实践检验,该算法能够满足档案库房管理的要求.     

高可靠性温室环境测控系统架构形式化建模与特性证明

温室环境测控系统由多个可并发执行的子系统共同协作来构造适宜的温室环境以确保作物有效生长.为提高温室环境测控系统设计的效率和可靠性,本文提出一个能为设计者提供指导性框架的融入容错技术的高可靠性温室环境测控系统架构.并且运用PVS形式化语言对系统架构进行了精确而无二义性的形式化建模,以及PVS证明工具对系统架构的容错特性进行了机械化证明,以确保系统架构能满足高可靠性需求.     

小型农作物温室大棚二氧化碳浓度监测系统

针对小型农作物温室环境指标监测的需要,设计实现了农作物温室大棚二氧化碳浓度监测系统。采用STC系列单片机控制,对农作物大棚内二氧化碳浓度进行近距离实时监测,采用TFT彩屏显示实时值和动态曲线,具有阀值调节,超过阀值报警,可实现小型温室农作物的生长环境二氧化碳浓度的实时监控。     

Time-scale decomposition of an optimal control problem in greenhouse climate management

Based on differences in dynamic response times in the crop production process, a hierarchical decomposition of greenhouse climate management is proposed. To a large extent the proposed decomposition builds on the time-scale decomposition of singularly perturbed systems commonly found in the literature. Main difference with these existing theoretical concepts is that the proposed decomposition is able to deal with rapidly fluctuating deterministic external inputs or disturbances acting on the fast sub-processes. For an example of economic optimal greenhouse climate management during one lettuce production cycle, the decomposition was successfully evaluated in simulations. Using these favourable results, a hierarchical concept for economic optimal greenhouse climate management is derived and discussed in view of application in horticultural practice.     

Nonlinear MPC based on a Volterra series model for greenhouse temperature control using natural ventilation

Suitable environmental conditions are a fundamental issue in greenhouse crop growth and can be achieved by advanced climate control strategies. In different climatic zones, natural ventilation is used to regulate both the greenhouse temperature and humidity. In mild climates, the greatest problem faced by far in greenhouse climate control is cooling, which, for dynamical reasons, leads to natural ventilation as a standard tool. This work addresses the design of a nonlinear model predictive control (NMPC) strategy for greenhouse temperature control using natural ventilation. The NMPC strategy is based on a second-order Volterra series model identified from experimental input/output data of a greenhouse. These models, representing the simple and logical extension of convolution models, can be used to approximate the nonlinear dynamic effect of the ventilation and other environmental conditions on the greenhouse temperature. The developed NMPC is applied to a greenhouse and the control performance of the proposed strategy will be illustrated by means of experimental results.     

基于EFM32的温室监控系统的设计与研究

针对农业大棚智能化发展的趋势和应用需求,本文以EFM32TG110基于Cortex-M3内核的单片机及CC2530 ZigBee模块为核心硬件,通过数据采集、数据融合算法及通信的相应软硬件设计,实现一个温室智能监控系统。实验结果表明,该系统能够有效地对大棚的温度、湿度及光照等因子进行远程智能检测并控制温室中的灯光,具有成本低、耗能少和实用性强等特点。