Precision Crop Management with Depth Estimation Height Data

Based on Patent Research | CN-118504795-A (2024)

Monitoring plant height is crucial for optimal cash crop growth. Inaccurate measurements can hinder timely intervention. Current methods often lack precision and efficiency. Depth estimation, a computer vision task, offers a solution. This technique estimates plant height from images, using pre-trained models. It enables precise monitoring and informed decisions. Growers can then optimize growing conditions, leading to better yields and resource management. This is similar to how surveyors use tools to determine land elevation.

SOLUTION OVERVIEW

Reimagining Manual Checks with AI Analysis

For crop production, depth estimation offers a solution for precise plant height monitoring. This technology uses pre-trained models to analyze crop images, accurately gauging plant height. The system captures images, then processes them to generate detailed height data, enabling continuous oversight of plant development and informed interventions for optimal growth in agricultural fields. The result is a more informed approach to crop management.

This technology can be integrated into existing farm management systems, automating the monitoring process and reducing the need for manual checks by agronomists. Like surveyors using tools to determine land elevation, depth estimation provides precise crop height measurements. This enables growers to optimize irrigation and fertilization. The improved data insights can lead to better yields and more efficient resource management, enhancing overall crop vitality.

HOW IT WORKS

Images to Plant Height Conversion

Capturing Crop Images in the Field

Capturing crop images is the initial step. High-resolution images of the plants are taken using cameras or drones. These images serve as the primary input for the depth estimation process, providing the visual data needed for analysis.

Analyzing Images Using Depth Estimation

Analyzing Images Using Depth Estimation Algorithms is crucial. The system employs pre-trained models to analyze the captured images. These models estimate the depth of each plant, effectively gauging its height from the image data based on plant height influence characteristic data.

Generating Plant Height Data

Generating Plant Height Data for Monitoring is the next phase. The depth estimation results are then converted into precise plant height measurements. This data provides detailed insights into plant development, enabling continuous oversight of growth patterns.

Providing Data-Driven Insights

Providing Data-Driven Insights for Growers is the final step. The processed plant height data is presented to growers in an accessible format. This enables informed interventions, like optimized irrigation and fertilization, ultimately leading to better yields and more efficient resource management.

Potential Benefits

Enhanced Precision in Height Monitoring

Improved Accuracy in Plant Height. Depth estimation provides precise plant height measurements, unlike manual methods, ensuring timely intervention and optimized growth conditions.

Automated Monitoring Efficiency

Reduced Need for Manual Checks. Automating the monitoring process lessens the need for agronomists' manual inspections, which saves time and labor costs.

Data-Driven Resource Optimization

Optimized Resource Management. Better data insights from plant height monitoring enable growers to refine irrigation and fertilization strategies, improving resource allocation.

Increased Crop Yield and Health

Better Yields and Crop Vitality. By optimizing growing conditions through precise height monitoring, growers can achieve healthier crops and increased overall yields.

Implementation

1 Camera Installation. Install necessary field cameras. Ensure cameras are properly positioned for optimal image capture.

2 Software Configuration. Configure the depth estimation software. Integrate with existing farm management systems, if available.

3 Image Capture Protocol. Establish a routine for image capture. Use drones or fixed cameras for consistent data collection.

4 Data Processing. Process captured images using the AI model. Generate plant height data for each image set.

5 Data Analysis. Visualize plant height data, identify trends. Adjust irrigation or fertilization based on insights.

6 System Maintenance. Maintain system and update models. Ensure reliable operation for long-term monitoring.

Source: Analysis based on Patent CN-118504795-A "Automatic monitoring method and system suitable for cash crops" (Filed: August 2024).