Targeted Plant Treatment Using ML Weed Detection

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Solution Overview

Problem

Current agricultural techniques for producing and harvesting crops face challenges in land, chemical, time, and labor costs, necessitating a more efficient and effective system for managing agricultural activities, particularly in detecting and controlling undesirable vegetation.

Innovation Solution

A machine learning-based agricultural treatment system mounted on a vehicle that uses image processing and sensors to identify agricultural objects, determine treatment parameters, and apply targeted treatments using a treatment mechanism.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If traditional agricultural techniques are used for producing and harvesting crops, then current practices can be maintained, but land, chemical, time, and labor costs remain high and efficiency is limited

Engineering Contradiction:

Improveagricultural operation efficiencyVSAvoidchemical use

Core Design Contradiction:

ProductivityVSQuantity of substance

Solution Approach 1:

The patent replaces traditional mechanical and chemical agricultural practices with an automated optical detection and treatment system. Image sensors capture visual data of crops and weeds, machine learning algorithms process the images to identify target objects, and the system automatically applies treatments only to detected weeds, eliminating the need for broad chemical application and manual labor

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system enables autonomous agricultural operations where the machine learning model automatically detects, classifies, and determines treatment parameters for agricultural objects without human intervention. The treatment mechanism self-regulates based on real-time image analysis, applying treatments only where and when needed

Inventive Principle:

Principle #25Self-service

2Productivity

Engineering Contradiction:

Improveagricultural operation efficiencyVSAvoidtime for detection and treatment

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The system performs continuous detection and treatment operations as the agricultural vehicle moves through the field. Image sensors continuously capture images, the machine learning model processes them in real-time, and the treatment mechanism continuously applies treatments to detected weeds, eliminating idle time between detection and treatment actions

Inventive Principle:

Principle #20Continuity of useful action

Solution Approach 2:

The machine learning model is pre-trained with extensive agricultural image data to enable rapid identification and classification of crops and weeds. Treatment parameters are pre-determined based on object classification, allowing the system to immediately execute treatments without delay for analysis or decision-making

Inventive Principle:

Principle #10Preliminary action

3Measurement precision

If machine learning-based detection is implemented, then treatment precision is improved, but device complexity increases

Engineering Contradiction:

Improvetarget detection accuracyVSAvoidsystem complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system uses a single integrated platform that combines image sensing, machine learning processing, and treatment application. The machine learning model serves multiple functions including object detection, classification, and treatment parameter determination, reducing the need for multiple separate systems and sensors

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The machine learning algorithm acts as an intermediary between image capture and treatment application. It processes raw image data, identifies target objects, and translates visual information into treatment commands, simplifying the overall system architecture by centralizing the decision-making function

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS12426589B2Multiaction treatment of plants in an agricultural environment

Publication Date: 2025.09.30 VERDANT ROBOTICS INC

AI summary

A method includes traversing, by the treatment system, along a path in an agricultural environment, receiving, by the treatment system, one or more sensor readings comprising one or more agricultural objects, identifying one or more objects of interest from the one or more agricultural objects by analyzing the one or more sensor readings, determining a first target object of the one or more objects of interest for treatment, selecting a treatment policy to treat the first target object, and activating the treatment mechanism to treat the first target object with the treatment policy.