Invention Grant
US09087312B1 Modeling of costs associated with in-field and fuel-based drying of an agricultural commodity requiring sufficiently low moisture levels for stable long-term crop storage using field-level analysis and forecasting of weather conditions, grain dry-down model, facility metadata, and observations and user input of harvest condition states 有权
使用野外水平分析和预测天气条件,谷物干燥模型,设施元数据以及对农业商品进行现场和燃料干燥的成本建模,需要足够低的水分含量以稳定长期作物储存 收获条件状态的观察和用户输入

  • Patent Title: Modeling of costs associated with in-field and fuel-based drying of an agricultural commodity requiring sufficiently low moisture levels for stable long-term crop storage using field-level analysis and forecasting of weather conditions, grain dry-down model, facility metadata, and observations and user input of harvest condition states
  • Patent Title (中): 使用野外水平分析和预测天气条件,谷物干燥模型,设施元数据以及对农业商品进行现场和燃料干燥的成本建模,需要足够低的水分含量以稳定长期作物储存 收获条件状态的观察和用户输入
  • Application No.: US14603382
    Application Date: 2015-01-23
  • Publication No.: US09087312B1
    Publication Date: 2015-07-21
  • Inventor: John J. MewesDustin M. Salentiny
  • Applicant: ITERIS, INC.
  • Applicant Address: US CA Santa Ana
  • Assignee: ITERIS, INC.
  • Current Assignee: ITERIS, INC.
  • Current Assignee Address: US CA Santa Ana
  • Agency: Lazaris IP
  • Main IPC: G06F15/18
  • IPC: G06F15/18 G06Q10/06
Modeling of costs associated with in-field and fuel-based drying of an agricultural commodity requiring sufficiently low moisture levels for stable long-term crop storage using field-level analysis and forecasting of weather conditions, grain dry-down model, facility metadata, and observations and user input of harvest condition states
Abstract:
A modeling framework for evaluating the impact of weather conditions on farming and harvest operations applies real-time, field-level weather data and forecasts of meteorological and climatological conditions together with user-provided and/or observed feedback of a present state of a harvest-related condition to agronomic models and to generate a plurality of harvest advisory outputs for precision agriculture. A harvest advisory model simulates and predicts the impacts of this weather information and user-provided and/or observed feedback in one or more physical, empirical, or artificial intelligence models of precision agriculture to analyze crops, plants, soils, and resulting agricultural commodities, and provides harvest advisory outputs to a diagnostic support tool for users to enhance farming and harvest decision-making, whether by providing pre-, post-, or in situ-harvest operations and crop analyzes.
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