基于云的特种作物收获管理系统

Li Tan, Ronald Haley, Riley Wortman
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引用次数: 4

摘要

收获劳动力是特种作物生产的主要成本因素。如今,收割劳动力的积累仍然是手工完成的,这很容易出错,而且成本很高。通过将基于云的web应用程序与专门设计的劳动监测设备(lmd)集成,我们开发了一个收获管理系统,用于监测和积累收获劳动力。该系统由两个主要部分组成:果园内数据收集网络,收集收获数据并将其传输到基于云的劳动力管理软件(LMS);并且,LMS处理收获数据并通过平板电脑友好的web界面将结果传递给用户。该系统采用专利技术,即使在复杂的多对多雇佣关系下,也能准确地积累多个果园的收获劳动活动。该系统为专业作物收获的利益相关者提供了多重好处:采摘者可以根据他采摘的水果的实际重量准确地获得补偿;果园管理者可以实时监控劳动力活动,并根据系统生成的分析报告改进果园运营。云计算平台提供的动态资源分配,保证了系统在收获季节和非收获季节处理实时收获数据的波动需求。该系统的设计针对云计算进行了优化,改善了对果园数据的访问,同时保护了种植者的隐私。该系统的原型已在美国太平洋西北地区的现场测试中得到验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cloud-Based Harvest Management System for Specialty Crops
Harvesting labor is a major cost factor in the production of specialty crops. Today accruing harvest labors is still done by hands, which is error-prone and costly. By integrating cloud-based web application with purposely designed labor monitoring devices (LMDs), we developed a harvest management system for monitoring and accruing harvest labors. The system comprises of two major components: an in-orchard data collection network collecting harvest data and transmitting them to a cloud-based labor management software (LMS); and, LMS processing harvest data and delivering results to users via a tablet-friendly web interface. Using a patented technology, the system accurately accrues harvest labor activities for multiple orchards, even under complex many-to-many employment relations. The system provides multi-fold benefits to stakeholders of specialty crop harvesting: a picker can be compensated accurately by the actual weight of the fruits he picked; and an orchard manager may monitor labor activities in real time and improve his orchard operation based on the analytical reports generated by the system. The dynamic resource allocation provided by a cloud computing platform ensures that the system can handle the fluctuating demand for processing real-time harvest data during and off harvest seasons. The design of the system is optimized for cloud computing, improving the access to orchard data while preserving their privacy for growers. A prototype of the system has been validated in field tests in United States' Pacific Northwest Region.
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