AI-Powered Silo Material Distribution Optimization System

Publication ID: 24-11856896_0006_PTD

Published: October 26, 2025

Category:Direct Improvements & Enhancements

Legal Citation

pr1or.art Inc., “AI-Powered Silo Material Distribution Optimization System,” Published Technical Disclosure No. 24-11856896_0006_PTD, Published October 26, 2025, available at https://archive.pr1or.art/24-11856896_0006_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. 11,856,896.

Background and Problem Solved

The original patent disclosed a method for assisting a compaction-appropriate distribution of harvested material in a flat silo. However, it had limitations in terms of efficiency, safety, and adaptability to varying material properties. The new invention addresses these limitations by introducing advanced sensors, machine learning, and weather forecasting integration to optimize the distribution process.

Novelty and Inventive Step

The new claims introduce novel elements, including the use of machine learning algorithms, real-time sensor data, and weather forecasting integration, which differentiate the invention from the original patent and provide a non-obvious solution to the identified limitations.

Alternative Embodiments and Variations

Alternative embodiments may include different types of sensors, machine learning algorithms, or weather forecasting data sources. Variations may also involve adapting the system for use in different types of silos or with various types of harvested materials.

Potential Commercial Applications and Market

The enhanced method and system have significant commercial potential in the agricultural and livestock industries, where efficient and safe storage of harvested material is critical. The technology can be integrated into existing silo systems or marketed as a standalone solution, offering a competitive advantage in terms of efficiency, cost savings, and environmental sustainability.

CPC Classifications

Section	Class	Group
A	A01	A01F25/183
A	A01	A01D43/0633
A	A01	A01F25/166

Section 103 Obviousness Analysis (PHOSITA)

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Field of Art

Agricultural machinery and material handling systems, specifically focused on harvested material distribution and compaction in flat silos, involving control systems, sensor technologies, and material handling optimization

Person of Ordinary Skill (PHOSITA) Profile

A mechanical engineer with expertise in agricultural equipment design, control systems, sensor integration, and material handling techniques, possessing knowledge of agricultural machinery, data processing, and optimization algorithms

Obviousness Rationale

A PHOSITA would recognize that the PTD's variations represent predictable extensions of the source patent's core methodology by integrating standard technological improvements such as machine learning, sensor arrays, and data analytics platforms into existing material distribution control systems. The proposed modifications leverage well-established techniques in agricultural machinery automation and represent incremental technological advancements that would be apparent to a skilled practitioner seeking to enhance the original patent's efficiency and precision. These variations demonstrate standard engineering problem-solving approaches that apply known technological solutions to existing technical challenges.

Obvious Combinations & Variations

Source Patent Element

Control unit for managing distribution of harvested material in a flat silo

PTD Variation

Integration of machine learning algorithms to predict optimal distribution patterns

Obviousness Reasoning

Applying machine learning to control systems is a known technique for improving predictive capabilities and represents a predictable result of combining existing control technologies with modern data processing techniques

Source Patent Element

Distribution tool with adjustable spacing and vertical attitude

PTD Variation

Real-time sensor array for detecting moisture levels and dynamically adjusting distribution parameters

Obviousness Reasoning

Enhancing mechanical control systems with sensor feedback is a standard engineering approach for improving precision and represents an obvious design optimization technique

Source Patent Element

Silo vehicle with control mechanisms for material distribution

PTD Variation

Cloud-based data analytics platform for processing sensor data and providing real-time recommendations

Obviousness Reasoning

Integrating cloud computing and remote data processing with existing control systems is a well-known technological progression that would be obvious to a PHOSITA seeking enhanced system performance

Source Patent Element

Method for compaction-appropriate material distribution

PTD Variation

Weather forecasting data integration to adjust distribution parameters

Obviousness Reasoning

Incorporating external environmental data into control systems is a predictable enhancement that represents a finite set of obvious solutions for improving agricultural machinery performance

35 U.S.C. § 103 Summary: Pursuant to 35 U.S.C. § 103, the variations disclosed in this publication would have been obvious to a person having ordinary skill in the art at the time of the invention, as they represent predictable technological extensions of US Patent 11856896, combining known techniques in sensor integration, machine learning, and data analytics with existing material distribution control methodologies. The proposed modifications constitute routine engineering design choices that would be apparent to a skilled practitioner seeking incremental improvements in agricultural machinery control systems.

Original Patent Information

Patent Number	US 11,856,896
Title	Method for assisting a compaction-appropriate distribution of harvested material in a flat silo
Assignee(s)	Deer & Company