Published Technical Disclosure Archive

AI-Powered Harvesting Machine Unloading System

Publication ID: 24-11856889_0005_PTD
Published: October 26, 2025
Category:Future Evolutions & Paradigm Shifts

Legal Citation

pr1or.art Inc., “AI-Powered Harvesting Machine Unloading System,” Published Technical Disclosure No. 24-11856889_0005_PTD, Published October 26, 2025, available at https://archive.pr1or.art/24-11856889_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. 11,856,889.

Background and Problem Solved

The original patent's automated camera system control for harvesting machine unloading, while innovative, has limitations in terms of adaptability, efficiency, and accuracy. The new invention addresses these limitations by introducing advanced technologies that enable real-time optimization, autonomous operation, and modular adaptability.

Novelty and Inventive Step

The new claims introduce a paradigm shift in harvesting machine unloading by incorporating AI, machine learning, and advanced sensor technologies, which are not obvious extensions of the original patent's automated camera system control. The inventive step lies in the integration of these technologies to achieve real-time optimization, autonomous operation, and modular adaptability.

Alternative Embodiments and Variations

Alternative embodiments of the invention could include the use of other types of sensors, such as radar or ultrasonic sensors, or the integration of additional AI-powered modules for predicting weather patterns or soil conditions. Variations of the invention could also include different types of receiving vehicles, such as autonomous or self-driving vehicles, or different harvesting operations, such as those involving multiple harvesting machines.

Potential Commercial Applications and Market

The next-generation harvesting machine unloading system has significant commercial potential in the agricultural industry, particularly in the areas of precision agriculture, autonomous farming, and sustainable harvesting practices. The system's ability to increase efficiency, reduce waste, and optimize unloading operations makes it an attractive solution for farmers, agricultural companies, and equipment manufacturers.

CPC Classifications

SectionClassGroup
A A01 A01D41/127
A A01 A01D90/02
B B65 B65G67/22
H H04 H04N23/69
B B65 B65G2814/0302

Field of Art

Agricultural machinery automation, specifically harvesting machine unloading systems with camera and sensor-based positioning and control technologies

Person of Ordinary Skill (PHOSITA) Profile

An engineer with expertise in agricultural machinery, computer vision, sensor integration, and control systems, typically holding a BS/MS in agricultural engineering, mechanical engineering, or robotics with 3-5 years industry experience

Obviousness Rationale

A PHOSITA would recognize that the PTD's AI and machine learning extensions are predictable variations of the source patent's automated camera and positioning control system. The core technical problem of optimizing harvesting machine unloading remains consistent, with the PTD merely introducing more sophisticated computational approaches to solving the same fundamental challenge of efficient material transfer between harvesting and receiving vehicles.

Obvious Combinations & Variations

Source Patent Element
Camera system with variable focal length and digital zoom logic for tracking receiving vehicle position
PTD Variation
3D point cloud generation using LiDAR for determining optimal spout positioning
Obviousness Reasoning
Extending camera-based positioning to LiDAR is a known technique for enhanced spatial mapping, representing a predictable technological progression using alternative sensor technologies
Source Patent Element
Automated control system for adjusting unloading spout configuration based on vehicle position
PTD Variation
Self-organizing neural network predicting optimal receiving vehicle positions
Obviousness Reasoning
Applying machine learning to existing positioning control represents an obvious enhancement using standard AI techniques to improve existing automated systems
Source Patent Element
Optical sensor generating pixel-based image representations for tracking unloading operations
PTD Variation
Drone-based 360-degree imaging for real-time unloading feedback
Obviousness Reasoning
Expanding single-camera imaging to multi-perspective drone imaging is a predictable extension of existing visual tracking methodologies
Source Patent Element
Conveyance subsystem with configurable unloading modes
PTD Variation
Modular, interchangeable sensor suite for adapting to different vehicle types
Obviousness Reasoning
Implementing adaptable sensor configurations represents a standard design approach for enhancing system flexibility and generalizability
Source Patent Element
Automated control system responding to receiving vehicle positioning signals
PTD Variation
Autonomous navigation and self-driving harvesting machine control
Obviousness Reasoning
Extending existing positioning and control logic to full autonomous operation is a foreseeable technological progression in agricultural automation
35 U.S.C. § 103 Summary: Based on US Patent 11856889's teachings of automated harvesting machine unloading control, the present publication demonstrates that a person of ordinary skill in the art would find the claimed variations obvious through predictable combinations of known sensor, control, and machine learning technologies, thereby rendering subsequent claims of novelty invalid under standard obviousness analysis.

Original Patent Information

Patent NumberUS 11,856,889
TitleAutomated camera system control for harvesting machine unloading
Assignee(s)Deer & Company