AI-Driven Agricultural Harvester Optimization System

Publication ID: 24-11856890_0005_PTD

Published: October 26, 2025

Category:Future Evolutions & Paradigm Shifts

Legal Citation

pr1or.art Inc., “AI-Driven Agricultural Harvester Optimization System,” Published Technical Disclosure No. 24-11856890_0005_PTD, Published October 26, 2025, available at https://archive.pr1or.art/24-11856890_0005_PTD

This technical disclosure describes improvements that would be readily apparent to a Person Having Ordinary Skill In The Art (PHOSITA) when considered in combination with the foundational architecture disclosed in U.S. Patent No. 11,856,890.

Background and Problem Solved

The original patent, 'Automated turn patterns in an agricultural harvester,' addressed the need for automated control of agricultural harvesters. However, it relied on pre-defined turn patterns and did not account for real-time crop conditions, topography, or environmental factors. This invention overcomes these limitations by integrating advanced sensors, machine learning, and autonomous control to create a more efficient, adaptive, and sustainable harvesting system.

Novelty and Inventive Step

The new claims introduce a paradigm shift in agricultural harvesting by integrating real-time crop analysis, machine learning, and autonomous control. The invention's novelty lies in its ability to adapt to changing crop conditions, optimize harvesting efficiency, and reduce waste. The inventive step is the combination of advanced sensors, machine learning, and autonomous control to create a more efficient, adaptive, and sustainable harvesting system.

Alternative Embodiments and Variations

Alternative embodiments of the invention could include using different types of sensors, such as hyperspectral or thermal imaging, or integrating additional data sources, such as weather forecasts or soil moisture levels. Variations could include adapting the system for different types of crops or harvesting equipment, or developing specialized interfaces for different user groups.

Potential Commercial Applications and Market

The Intelligent Agricultural Harvesting System has significant commercial potential in the agricultural industry, particularly in large-scale farming operations. The system could increase crop yields, reduce waste, and improve harvesting efficiency, resulting in cost savings and increased profitability for farmers. The market for this technology is expected to grow rapidly as the agricultural industry adopts more advanced technologies to improve sustainability and efficiency.

CPC Classifications

Section	Class	Group
A	A01	A01D41/1278
G	G05	G05D1/0212
G	G05	G05D2201/0201

Section 103 Obviousness Analysis (PHOSITA)

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Field of Art

Agricultural automation and precision farming, focusing on autonomous harvesting systems with emphasis on navigation, control systems, and machine intelligence for agricultural equipment

Person of Ordinary Skill (PHOSITA) Profile

An engineer with expertise in agricultural engineering, robotics, machine learning, and control systems, typically holding a masters or PhD with 5-10 years experience in agricultural technology development

Obviousness Rationale

A PHOSITA would recognize that the PTD's variations represent predictable extensions of the source patent's automated turn pattern technology by integrating advanced sensing, machine learning, and adaptive control strategies. The fundamental concept of autonomous agricultural harvester navigation is already established in the source patent, making the PTD's proposed enhancements a logical progression of existing technological capabilities. The incremental improvements in sensor integration, predictive analytics, and autonomous decision-making would be considered obvious refinements to an existing technological framework.

Obvious Combinations & Variations

Source Patent Element

Detecting turn patterns of an agricultural harvester using processor-based guidance systems

PTD Variation

Integrating machine learning module to predict optimal turn patterns based on real-time crop yield analysis

Obviousness Reasoning

Applying machine learning to existing turn pattern detection is a known technique for improving automated navigation, representing a predictable application of existing technological capabilities

Source Patent Element

Operator input for defining harvester turn patterns

PTD Variation

Developing a hybrid human-machine interface with augmented reality and adaptive learning of operator decision-making

Obviousness Reasoning

Enhancing human-machine interaction through adaptive interfaces is a standard design evolution in autonomous systems, representing an obvious design choice for improving user experience

Source Patent Element

Agricultural harvester with guidance system for path control

PTD Variation

Creating a decentralized agricultural harvesting network with cloud-based route optimization and real-time performance monitoring

Obviousness Reasoning

Extending single-machine autonomous control to networked systems is a foreseeable technological progression, utilizing known communication and coordination technologies

Source Patent Element

Computer executable instructions for detecting harvester path and turn patterns

PTD Variation

Implementing multispectral sensing and predictive analytics for real-time crop condition adaptation

Obviousness Reasoning

Incorporating advanced sensing technologies into existing control systems represents an obvious technological improvement using known sensor integration techniques

Source Patent Element

Agricultural harvester with path detection capabilities

PTD Variation

Generating 3D field maps for optimized land allocation and harvesting strategy

Obviousness Reasoning

Using computational mapping techniques to enhance harvesting efficiency is a predictable application of existing geospatial and agricultural mapping technologies

35 U.S.C. § 103 Summary: Based on the teachings of US Patent 11856890 and the disclosed technological variations, a person having ordinary skill in the art would find the proposed agricultural harvesting system innovations obvious and non-patentable, as they represent predictable extensions of existing autonomous agricultural navigation and control technologies through standard engineering design choices and known technological integration strategies.

Original Patent Information

Patent Number	US 11,856,890
Title	Automated turn patterns in an agricultural harvester
Assignee(s)	Deer & Company