Drone Field Scanning for Animal Detection Ahead of Farm Machines
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Solution Overview
Problem
Current methods for detecting animals and obstacles in agricultural fields using drones are either time-consuming, labor-intensive, or have limited detection ranges, making them unsuitable for modern high-efficiency field processing machines, and often require excessive reaction times or inaccurate information sharing.
Innovation Solution
Integrating a drone system with a field processing machine into a higher-level management system for data exchange, using standardized area data formats like ISOXML, and employing thermal imaging cameras for sensitive detection, allowing for real-time information sharing and optimized processing control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If sensors are mounted on the field cultivators themselves, then the detection range is extended and field scanning is eliminated, but the detection range remains limited and response time must be excessively fast
Solution Approach 1:
The detection system is segmented into two parts: a drone that performs advance scanning of the field area and a field cultivator that receives the scanned data. This segmentation allows the drone to detect animals and obstacles from a distance and transmit the data to the cultivator, providing sufficient response time while maintaining reliable detection coverage.
2Loss of time
If the drone follows at a large distance, then advance warning time is increased, but animals or obstacles may not be detected in curves or turning areas
Solution Approach 1:
The drone's position relative to the field cultivator is dynamic rather than fixed. The drone automatically adjusts its distance and position based on the cultivator's movement, especially during curves or turning areas, ensuring continuous detection coverage while maintaining sufficient advance warning time.
3Ease of operation
If manual remote control is used, then the drone can be operated flexibly, but accurate information sharing about areas to be covered is prone to errors
Solution Approach 1:
The system implements automated feedback mechanisms where the drone receives real-time position and route data from the field cultivator and management system, automatically adjusts its scanning area accordingly, and transmits detection results back to update the enriched area data. This closed-loop feedback eliminates manual control errors while maintaining operational flexibility.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Ensures accurate and efficient detection of animals and obstacles, enabling precise control of field processing machines to avoid collisions and providing valuable data for future operations, improving safety and operational efficiency.
Implementation Method 1
employing thermal imaging cameras for sensitive detection
Data Source
Figure 1
AI summary
The invention relates to a method for detecting animals and/or obstacles on an area to be cultivated by an agricultural field cultivation machine (1) using a drone system (2) comprising at least one drone equipped with a non-contact sensor for detecting the animals or obstacles. The method is characterized in that the drone system (2) and the field cultivation machine (1) are in data communication with a higher-level management system (3), and area data (11-14) are exchanged between the management system (3) and the drone system (2) on the one hand, and between the management system (3) and the field cultivation machine (1) on the other. The invention further relates to a system for carrying out the method.