Published Technical Disclosure Archive

AI-Driven Pest Management: IoT Insect Control System

Publication ID: 24-11856951_0008_PTD
Published: October 26, 2025
Category:Synergistic Combinations

Legal Citation

pr1or.art Inc., “AI-Driven Pest Management: IoT Insect Control System,” Published Technical Disclosure No. 24-11856951_0008_PTD, Published October 26, 2025, available at https://archive.pr1or.art/24-11856951_0008_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. 11,856,951.

Background and Problem Solved

The original patent disclosed methods for managing resistance to transgenic insecticidal traits and/or chemical insecticides using pheromones. However, these methods were limited in their ability to adapt to changing environmental and insect population conditions. The present invention addresses these limitations by incorporating IoT-enabled sensors to monitor insect populations, AI-driven data analysis to optimize pheromone release, and blockchain-based data management to track resistance development.

Novelty and Inventive Step

The present invention is novel in its integration of pheromone-based mating disruption with IoT-enabled sensors, AI-driven data analysis, and blockchain-based data management. The inventive step lies in the use of machine learning algorithms to optimize pheromone release and the incorporation of RNA interference technology to enhance the effectiveness of transgenic insecticidal traits.

Alternative Embodiments and Variations

Alternative embodiments of the invention may include the use of different types of sensors, such as drones or satellite imaging, to monitor insect populations. Additionally, the system may be adapted for use in different agricultural settings, such as greenhouses or indoor farming facilities.

Potential Commercial Applications and Market

The integrated pest management system has significant commercial potential in the agricultural industry, particularly in the areas of precision agriculture, sustainable farming practices, and integrated pest management. The system may be marketed to farmers, researchers, and agricultural companies seeking to reduce the environmental impact of pest control methods while improving crop yields.

CPC Classifications

SectionClassGroup
A A01 A01N37/02

Field of Art

Agricultural biotechnology and pest management, specifically focusing on insect resistance management techniques involving transgenic traits, pheromone disruption, and population control strategies

Person of Ordinary Skill (PHOSITA) Profile

A person with advanced degree in entomology, agricultural engineering, or biotechnology, with expertise in genetic engineering, insect population dynamics, and pest management technologies. Familiar with IoT sensing, data analytics, and genetic modification techniques

Obviousness Rationale

A PHOSITA would recognize that the PTD represents a predictable technological evolution of the source patent's core resistance management strategy by integrating modern digital technologies and advanced sensing techniques. The fundamental approach of managing insect resistance through targeted population control remains consistent, with the PTD merely applying contemporary technological tools to enhance the existing methodology. The combination of pheromone disruption with IoT sensing and machine learning represents an incremental and foreseeable advancement in the field of agricultural pest management.

Obvious Combinations & Variations

Source Patent Element
Method of managing resistance in field plot systems using transgenic insecticidal traits
PTD Variation
Integration of IoT-enabled sensor networks for real-time insect population monitoring
Obviousness Reasoning
Applying digital sensing technologies to existing pest management strategies is a known technique with predictable results in agricultural monitoring systems
Source Patent Element
Refuge strategies for managing insect resistance
PTD Variation
Machine learning algorithms to optimize pheromone release and resistance management
Obviousness Reasoning
Using computational intelligence to refine existing population control methods represents a standard technological progression with expected outcomes
Source Patent Element
Chemical and transgenic approaches to insect resistance management
PTD Variation
RNA interference technology integrated with pheromone-based disruption
Obviousness Reasoning
Combining genetic modification techniques with existing resistance management strategies is a logical and foreseeable extension of known biotechnological approaches
Source Patent Element
Field plot systems for managing insect populations
PTD Variation
Blockchain-based data management platform for tracking resistance development
Obviousness Reasoning
Implementing distributed data tracking in agricultural research represents a standard technological enhancement with predictable information management benefits
Source Patent Element
Mating disruption techniques for pest control
PTD Variation
Graphene-based pheromone delivery system
Obviousness Reasoning
Exploring advanced material technologies for improving existing delivery mechanisms is a routine approach in biotechnological research with expected incremental improvements
35 U.S.C. § 103 Summary: Based on the teachings of US Patent 11856951 and the comprehensive technological extensions disclosed herein, a person having ordinary skill in the art would find the claimed variations obvious and lacking inventive step. The present disclosure demonstrates that the integration of IoT sensing, machine learning, and advanced material technologies represents a predictable and incremental advancement in existing insect resistance management methodologies, thereby rendering potential patent claims obvious under 35 U.S.C. Section 103.

Original Patent Information

Patent NumberUS 11,856,951
TitleMethod for managing resistance to insecticidal traits and chemicals using pheromones
Assignee(s)PROVIVI, INC.