基于3G和DDNS的果园环境远程监控系统

针对果园监控现场偏远分散、环境要素复杂、受气候影响较大、监控和管理困难等特点,研究了以3G和DDNS动态域名作为无线通讯方式的果园环境远程监控与管理的关键技术:即利用3G网络结合DDNS动态域名技术将果园内传感器感知到的空气温湿度、土壤温湿度、雨量、太阳光合辐射等果园气象环境因子以及果树视频图像远程传输到监控中心服务器,并使用ASP.NET技术以及ADO.NET技术实现在Internet互联网上实时发布果园环境数据,为用户提供果园环境远程监控管理的相关技术.实际应用结果表明,基于该关键技术的果园环境监控系统工作性能稳定、可靠,有效克服了传统远程监控中的数据传输瓶颈问题.为果园生产管理和果树远程诊断提供了一个良好的平台,大大提高了现代果园管理效率.     

基于无线短消息的鱼塘远程监测系统

鱼塘监测包括水产养殖生态环境指标监测及防盗监测。论文提出一种新颖的基于无线短消息服务(SMS)和RS485总线的鱼塘远程监测系统的设计。针对鱼塘监测系统在实际中的应用需求,着重讨论了鱼塘监测系统中无线远程监测的设计与实现。     

可信的企业生态环境

企业需要向合作伙伴、供应商、客户、承包商及员工提供远程的安全数据访问,这就需要建立一个足够安全可靠的生态环境。     

基于物联网技术的智慧农业无线控制系统设计

农业领域的重点工作是收割,随着农业现代化技术的发展,追求安全、可靠、高效的农产物收割是智慧农业发展的重点.本文基于物联网技术,提出一种远程无线控制方法,解决水果的半自动采摘,提高每工时的生产效率.通过无线远程控制流动站上的机械臂在果园中漫游,农户可以使用固定有各种传感器的手套远程控制它,这些传感器可以将机械臂远程定位以收获水果.本文讨论了固定有各种传感器的手套的设计、4自由度机械臂和无线控制接口的设计,并对系统的设置以及实验室条件下的测试和评估进行了分析.     

中国物联网(2013年7月)大事记

7月1日 重庆首个物联网社区亮相,可通过手机或电脑远程遥控指挥家电。 7月3日 国内首个信息化生态环境监测系统落户青海湖自然保护区。 7月3日 陕西物联网产业联盟大会暨陕西省物联网产业展示中心揭幕仪式在西安国际港务区举行。     

基于树莓派的果园智能喷药车用遥控器设计与实现

为了实现"机器换人",降低用工成本,结合果园智能喷药车功能需求,文中研究设计了一种基于树莓派的果园智能喷药车用遥控器。该遥控器不仅可用于控制果园喷药车的行进方向及动力,还可用于果园喷药车位置点的采集、路径的编辑/下发、模式切换、导航控制功能。实验表明,该遥控器可满足果园智能喷药车的功能需求,工作稳定。     

数字化果园管理系统

数字化果园管理系统是实现果园精准管理的基础.本研究以单株果树为最小管理单元,利用ArcGISServer提供的网络地理信息系统(Web Geographic Information System,WebGIS)应用服务构建了基于富互联网应用(Rich Internet Application,RIA)的数字化果园管理系统框架,设计了数据表并给出了格表之间的实体关系,采用ExtJS实现了系统功能.通过采集山东省某苹果园的果树及相关设施的坐标位置,生成果园地图,以此为空间数据,应用数字化果园管理系统对果园、果树、环境监测设备及生产操作记录等进行统一管理;实际应用表明,系统能提高管理效率、增强统计分析能力、提供可视化管理手段,是信息技术在果园管理中应用的新尝试.     

地表水质远程监控的无人值守系统实现

针对生态环境恶化导致的地表水水质难以实现大范围监控的难题,设计了一种基于无线传感器网络(WSN)的无人值守地表水水质远程监控系统.介绍了水质在线监控系统架构、监测网络组网与通信,说明了监控的实现.实际测试数据说明,设计的系统在检测指标上可达到国家规定的标准要求,是可行与可用的.     

基于分布式微服务架构的重型车污染物排放监管平台设计

随着汽车尾气污染问题日益严峻, 生态环境部要求所有国六重型车安装远程排放管理车载终端以监测其尾气排放. 本文设计了一种基于分布式微服务架构的重型车污染物排放分区监管平台, 该平台采集特定区域内所有安装车载终端的重型车实时数据, 对重型车主要尾气污染物氮氧化物、颗粒物进行定量分析, 同时提出了一种判定污染物所属具体行政区的算法, 从而实现了各行政区域内重型车污染物排放总量统计和展示. 最终该平台部署于淄博市生态环境局, 运行正常且数据可靠, 为环保部门的精准监管和治理提供了有力的数据支撑.     

浅谈远程医疗系统的设计与实现

目前,远程信息交流、远程诊治等基于远程医疗系统的医疗服务结构已经成为了一种全新的医疗模式。远程医疗具体包括了远程诊断、远程医疗教育、远程会诊以及远程医疗信息服务等一系列医学活动。以设计省级平台远程医疗系统为例,通过介绍远程医疗系统的组成,探究其设计和实现过程。     

The use of airborne lidar for orchard tree inventory

The tree inventory in orchards is of great interest for orchard management and for government insurance plans. However, the conventional inventory is time‐consuming and expensive. Here a remote sensing method is introduced for orchard inventory. Airborne LIDAR (light detection and ranging) data were employed to obtain tree topography, and multispectral images were used as a reference. LIDAR vector data were converted to raster data for tree crown delineating purpose and in order to be easily superimposed on multispectral data in the same database. A tree crown delineation model was developed using a tree height image derived from the difference between canopy and ground LIDAR altitudes. The number of trees was computed from the delineation model. Spatially separated trees were precisely counted by fine definition of their crowns. For larger trees, although they have irregular crown form, like multi‐tops, holes in the centre or overlapped branches, the model developed in this study provided reliable results for crown delineation.     

The polarization phase difference of orchard trees

Abstract

An image obtained by the Jet Propulsion Laboratory's airborne L-band polarimeter (SAR) over an agricultural area near Fresno, California was analysed for the signatures of polarization phase difference (PPD). The PPD of orchard trees was found to be distinctly different from that of bare fields or fields covered with other crops. Thus the PPD signatures obtained from a polarimeter may be useful in the understanding of the radar remote sensing of the Earth's surface.     

成像光谱技术在土地利用动态遥感监测中的应用研究

随着数字化调查技术的发展，国土资源管理对土地利用动态遥感监测提出了更高的要求，目前主要采用的多光谱数据由于受光谱分辨率限制以及“同谱异物，同物异谱”现象的影响，难以满足管理需要。成像光谱数据具有较高光谱分辨率。在类别细分方面具有一定的优势，在当前土地利用动态遥感监测中具有一定的应用潜质。该文针对成像光谱数据特点，探索了与成像光谱数据相适应的土地利用动态遥感监测方法，提出了异常光谱检测法，该方法在试验区应用中取得了良好效果。     

基于 AHP-TOPSIS 的果园作业平台舒适性评价及优化

果园作业平台是重要的果园机械装备之一,为了优化果园作业平台的舒适性体验, 提出了基于 AHP-TOPSIS 的果园作业平台舒适性评价及优化方法。首先,建立果园作业平台舒适 性层次分析模型,对 4 款典型机型进行舒适性评价,评价结果显示,操控台的人机界面是影响果 园作业平台舒适性的显著因素,工作台的移动平稳性是影响果园作业平台舒适性的重要因素;然 后以 3GP-160 自走式果园作业平台的操控台为例,利用逼近理想解法(TOPSIS)确定操控台元件的 优先排序,并结合人机界面设计原则对操控台进行了优化设计;最后采用 RAMSIS 客观评价法和 量化主观评价法对优化设计方案进行评价,结果表明,优化后的操控台尺寸、布局满足人体模型 的可视区域、可达区域要求,操作姿态比较轻松、舒适,能满足果农的舒适性要求。     

Long-term monitoring of citrus orchard dynamics using time-series Landsat data: a case study in southern China

ABSTRACT

Citrus orchard planting is a typical land-use change process that can impact terrestrial ecosystem services both locally and globally. Long-term monitoring of citrus orchard dynamics is critical for understanding its change patterns as well as the potential driving factors. Satellite remote-sensing imagery has been a primary data source for this purpose. However, most previous studies with multi-year intervals only captured some, but not all detailed information on citrus orchard expansion. In this study, we developed a framework for mapping annual citrus orchard extent and track its long-term dynamics in Xunwu County, China, using the historical Landsat repository from 1990 to 2016. The results suggested that the average overall accuracy of original annual mapping was 87.73%, and its performance was significantly improved after the temporal filtering approach (91.46%). Several features (e.g. elevation, slope, normalized difference vegetation index) played more important roles in citrus orchard identification. With the achieved annual mapping layers, we found a rapid citrus orchard expansion trend during the study interval (i.e. from 22.18 to 697.21 km²). Moreover, this expansion process was unevenly distributed in time. Spatially, emerging citrus orchards were primarily transformed from forests and croplands and mainly distributed in areas with elevations from 200 to 500 m and slopes range from 5° to 20°. This study demonstrated the potential of mapping citrus orchard dynamics at a higher temporal frequency with remote-sensing time-series, which can contribute to providing reference for sustainable land-use policy.     

Performance analysis of textural features for characterization and classification of SAR images

A new method has been presented to compare the performance of textural features for characterization and classification of SAR (Synthetic Aperture Radar) images. In contrast to the conventional comparative studies based on classification accuracy, this method emphasizes the sensitivity of texture measures for grey level transformation and multiplicative noise of different speckle levels. Texture features based on grey level run length, texture spectrum, power spectrum, fractal dimension and co-occurrence have been considered. A number of image samples of built-up, barren land, orchard and sand regions were considered for the study. The interpretation of the results is expected to provide useful information for the remote sensing community, which employs textural features for segmentation and classification of satellite images.     

Daily MODIS 500 m reflectance anisotropy direct broadcast (DB) products for monitoring vegetation phenology dynamics

Land surface vegetation phenology is an efficient bio-indicator for monitoring ecosystem variation in response to changes in climatic factors. The primary objective of the current article is to examine the utility of the daily MODIS 500 m reflectance anisotropy direct broadcast (DB) product for monitoring the evolution of vegetation phenological trends over selected crop, orchard, and forest regions. Although numerous model-fitted satellite data have been widely used to assess the spatio-temporal distribution of land surface phenological patterns to understand phenological process and phenomena, current efforts to investigate the details of phenological trends, especially for natural phenological variations that occur on short time scales, are less well served by remote sensing challenges and lack of anisotropy correction in satellite data sources. The daily MODIS 500 m reflectance anisotropy product is employed to retrieve daily vegetation indices (VI) of a 1 year period for an almond orchard in California and for a winter wheat field in northeast China, as well as a 2 year period for a deciduous forest region in New Hampshire, USA. Compared with the ground records from these regions, the VI trajectories derived from the cloud-free and atmospherically corrected MODIS Nadir BRDF (bidirectional reflectance distribution function) adjusted reflectance (NBAR) capture not only the detailed footprint and principal attributes of the phenological events (such as flowering and blooming) but also the substantial inter-annual variability. This study demonstrates the utility of the daily 500 m MODIS reflectance anisotropy DB product to provide daily VI for monitoring and detecting changes of the natural vegetation phenology as exemplified by study regions comprising winter wheat, almond trees, and deciduous forest.     

An efficient online citrus counting system for large-scale unstructured orchards based on the unmanned aerial vehicle

The accurate detection and counting of fruits in natural environments are key steps for the early yield estimation of orchards and the realization of smart orchard production management. However, existing citrus counting algorithms have two primary limitations: the performance of counting algorithms needs to be improved, and their system operation efficiency is low in practical applications. Therefore, in this paper, we propose a novel end-to-end orchard fruit counting pipeline that can be used by multiple unmanned aerial vehicles (UAVs) in parallel to help overcome the above problems. First, to obtain on-board camera images online, an innovative UAV live broadcast platform was developed for the orchard scene. Second, for this challenging specific scene, a detection network named Citrus-YOLO was designed to detect fruits in the video stream in real-time. Then, the DeepSort algorithm was used to assign a specific ID to each citrus fruit in the online UAV scene and track the fruits across video frames. Finally, a nonuniform distributed counter was proposed to correct the fruit count during the tracking process, and this can significantly reduce the counting errors caused by tracking failure. This is the first work to realize online and end-to-end counting in a field orchard environment. The experimental results show that the F1 score and mean absolute percentage error of the method are 89.07% and 12.75%, respectively, indicating that the system can quickly and accurately achieve fruit counting in large-scale unstructured citrus orchards. Although our work is discussed in the context of fruit counting, it can be extended to the detection, tracking and counting of a variety of other objects of interest in UAV application scenarios     

Development and initial assessment of objective fatigue measures for apple harvest work

Previous research has shown that neck, back and shoulder musculoskeletal strain is a major occupational health problem affecting migrant orchard harvest workers. Researchers seek to measure the effect of an ergonomic modification to the apple picking bucket on muscle fatigue, however objective measures for use in the orchard are not yet available.

The purpose of this study is to develop simple back, shoulder or arm strength measures, which detect statistically significant drops in strength over one workday. Candidate muscle strength measures were piloted in the laboratory, adapted for the orchard and evaluated (n=102). Data were analyzed for morning to afternoon fatigue, and for correlation between fatigue score and hours worked.

In the laboratory, the timed arm hold (35.7% time reduction, 95% CI: 21.81–49.61), and the timed spinal extension (31.8% time reduction, 95% CI: 23.54–39.96) showed significant fatigue. In the orchard (n=102), only the timed arm hold showed significant (11.4%, p<.0001) fatigue. The potential effect of field conditions and subject motivation on these results needs further exploration.