精准农业劳动力监测与数据分析集成云平台

Li Tan, Ronald Haley, Riley Wortman, Y. Ampatzidis, M. Whiting
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引用次数: 9

摘要

收获劳动力已成为樱桃和其他特种作物行业的主要成本。我们开发了一个集成的解决方案,提供实时劳动力监控、工资应计额和基于劳动力数据的分析。我们的解决方案的核心是一个基于云的信息系统,它从专门设计的劳动监测设备收集劳动数据,并通过移动友好的用户界面可视化实时劳动生产率数据。我们的解决方案使用专有流程[1],在多对多雇佣关系下准确地将劳动数据与其相关的工人和职位关联起来。我们还描述了我们的通信API和协议,它们是专门为提高果园内数据通信的可靠性而设计的。除了在提高劳动监测的效率和准确性方面的直接好处外,我们的解决方案还可以基于收获的劳动数据进行数据分析和可视化。作为一个例子,我们讨论了基于收获劳动数据的产量映射方法。我们实现了该平台,并将系统部署在基于云的计算平台上,以获得更好的可扩展性。该系统的早期版本已于2012年收获季节在美国太平洋西北地区的樱桃园进行了测试。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An integrated cloud-based platform for labor monitoring and data analysis in precision agriculture
Harvest labor has became a prevailing cost in cherry and other Specialty Crops industry. We developed an integrated solution that provided real-time labor monitoring, payroll accrual, and labor-data-based analysis. At the core of our solution is a cloud-based information system that collects labor data from purposely designed labor monitoring devices, and visualizes real-time labor productivity data through a mobile-friendly user interface. Our solution used a proprietary process [1] to accurately associate labor data with its related worker and position under a many-to-many employment relation. We also describe our communication API and protocol, which are specifically designed to improve the reliability of data communication within an orchard. Besides its immediate benefits in improving the efficiency and accuracy of labor monitoring, our solution also enables data analysis and visualization based on harvest labor data. As an example, we discuss our approach of yield mapping based on harvest labor data. We implemented the platform and deployed the system on a cloud-based computing platform for better scalability. An early version of the system has been tested during the 2012 harvest season in cherry orchards in the U.S. Pacific Northwest Region.
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