戴建国, 王守会, 赖军臣, 赵庆展, 马富裕. 基于智能手机的棉花苗情调查与决策支持系统[J]. 农业工程学报, 2017, 33(21): 200-206. DOI: 10.11975/j.issn.1002-6819.2017.21.024
    引用本文: 戴建国, 王守会, 赖军臣, 赵庆展, 马富裕. 基于智能手机的棉花苗情调查与决策支持系统[J]. 农业工程学报, 2017, 33(21): 200-206. DOI: 10.11975/j.issn.1002-6819.2017.21.024
    Dai Jianguo, Wang Shouhui, Lai Junchen, Zhao Qingzhan, Ma Fuyu. Cotton growth statuses investigation and decision support system based on smartphone[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2017, 33(21): 200-206. DOI: 10.11975/j.issn.1002-6819.2017.21.024
    Citation: Dai Jianguo, Wang Shouhui, Lai Junchen, Zhao Qingzhan, Ma Fuyu. Cotton growth statuses investigation and decision support system based on smartphone[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2017, 33(21): 200-206. DOI: 10.11975/j.issn.1002-6819.2017.21.024

    基于智能手机的棉花苗情调查与决策支持系统

    Cotton growth statuses investigation and decision support system based on smartphone

    • 摘要: 针对新疆棉花生产过程中基层植保力量不足的问题,该文设计开发了棉花苗情调查与决策支持系统。该系统基于"云到端"模式,云端采用基于角色的访问控制(role-based access control,RBAC)解决多用户权限分配与菜单管理问题,提供数据管理分析、专家决策支持服务;用户端基于智能手机提供数据采集、专家决策意见接收功能。云到端之间的数据通信采用表述性状态转移(representational state transfer,REST)架构,提供RESTful的数据访问服务,解决系统之间松耦合、可扩展等问题。系统在新疆生产建设兵团第六师105团经过3 a的应用,结果表明:该调查系统能够快速获取文字和图片2种形式的棉田苗情信息,并能够方便的通过农田地图、柱状图、曲线图、Excel表格等多种方式对数据进行有效的分析和展示,大大提高了工作效率。通过搭起基层农户与生产管理者、农学专家之间的信息快速传输通道,加快了知识转化,减轻了基层植保压力。该系统加以扩展即可用于其他农作物的田间调查,同时这种调查模式稍加改造还可应用于林业、畜牧业等多个行业的信息普查。

       

      Abstract: Abstract: Consistent growth status investigation is the most important basis for appropriate measures of cotton production management during cotton growth period, which is very significant for the increase in production. Therefore, the growth status investigation is a routine work of cotton production in Xinjiang Production and Construction Corps, and the work from the end of April to the end of August lasts for 4 months every year. However, the current work is usually a manual survey, the data are recorded on paper, and the investigation process is very time-consuming and the data cannot be easily analyzed, which seriously affect the work efficiency. In the background, we developed the cotton growth status investigation system based on smartphone. The system includes 2 parts: mobile-side and server-side, for 4 kinds of users: agricultural technicians, agronomists, agricultural production managers and system administrators. The agricultural technicians use mobile terminal system in the cotton field to collect both text and picture data which are sent to the server system, while they receive production instructions. The server system is constructed by the REST (representational state transfer) architecture to provide the data management and analysis service interface for the mobile terminal system, and to deploy functional modules such as data processing, production instruction management and system management. Agronomists use the system to get the current cotton growth status and pest information and publish production guidance. The agricultural production managers use the system to allocate investigative tasks, check the implementation of the investigation, publish relevant cultivation or plant protection measures, and give farmers assistance and guidance. The system administrator is responsible for the management of the system's basic data (such as farmland, users and other basic information) to ensure the normal operation of the system. According to user requirements, the system can collect 6 kinds of data: cotton growth status, cotton spider mite, cotton aphid, adult cotton bollworm, cotton bollworm larvae and cotton bollworm eggs. In this article, we concisely introduced the advantages and practical feasibilities of cotton growth investigation by smartphone, and the design and implement methods of the investigation system are introduced based on android platform. We analyzed the main functions of server-side, and introduced the system design and development based on .net platform. We also presented the investigation criteria and methods for the 6 kinds of data. The system has been used in the 105th Group of the 6th Division of the Xinjiang Production and Construction Corps for 3 years, and the application experience showed that cotton production information could be quickly collected by the investigation system, and all of the data could be easily analyzed and displayed by field map and statistical analysis charts. The system can be easily extended to other areas of data surveys, such as forestry and animal husbandry.

       

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