Camera-Guided Manure Scraper Control for Barn Alley Obstacles
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Solution Overview
Problem
Traditional manure handling equipment faces challenges in efficiently navigating complex barn alleys, detecting obstacles, and dynamically adjusting cleaning schedules due to inconsistent manure distribution and properties, leading to inefficient operation and potential safety hazards.
Innovation Solution
A system utilizing cameras mounted along the alley to create a virtual map of the scraper's route, enabling image processing for real-time object recognition and position detection, which controls the scraper's operation, speed, and cleaning schedule based on manure presence and obstacles, ensuring efficient and safe operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional manure handling equipment operates in barn alleys, then manure can be cleared, but the equipment cannot efficiently navigate complex routes or detect obstacles
Solution Approach 1:
The patent replaces mechanical navigation systems with optical sensing systems (cameras) and computational image processing to detect obstacles and navigate alleys. The camera system captures images of the alley environment, and image processing algorithms automatically identify obstacles, animals, and manure piles, enabling the scraper to adapt its route dynamically without complex mechanical sensors.
Solution Approach 2:
The system uses the camera and image processing to automatically detect and respond to environmental conditions without human intervention. The scraper autonomously identifies obstacles, adjusts its speed, and modifies its cleaning schedule based on real-time image analysis, making the system self-regulating and adaptive to changing barn conditions.
2Reliability
If manual operation is used to monitor barn conditions, then safety can be maintained, but labor requirements increase and response time decreases
Solution Approach 1:
The patent replaces manual visual monitoring with automated optical sensing systems. Cameras continuously capture images of the alley, and image processing algorithms automatically detect obstacles, animals, and hazardous conditions, providing immediate alerts and autonomous responses without requiring human presence in the barn.
Solution Approach 2:
The system introduces an intermediary layer of image processing technology between the physical environment and human operators. The camera and software act as intermediaries that translate visual information into actionable data, enabling remote monitoring and faster response times without direct human exposure to hazardous conditions.
3Ease of operation
If fixed cleaning schedules are used, then operational simplicity is maintained, but energy is wasted on unnecessary cleaning operations
Solution Approach 1:
The patent transforms the static, fixed cleaning schedule into a dynamic, adaptive schedule based on real-time environmental conditions. The system continuously monitors the alley using cameras and adjusts the scraper's operation timing and speed according to detected manure presence, animal activity, and obstacle locations, optimizing energy consumption while maintaining cleaning effectiveness.
Solution Approach 2:
The system implements feedback loops where image data from the alley is processed to determine actual cleaning needs. The image processing results feed back into the control system, which adjusts the cleaning schedule accordingly - delaying cleaning when the alley is clear and accelerating it when manure accumulates, thereby eliminating unnecessary energy expenditure.
4Productivity
If high-speed scraper operation is used, then cleaning productivity increases, but collision risk with animals or obstacles increases
Solution Approach 1:
The patent implements dynamic speed control where the scraper's operating speed is continuously adjusted based on real-time image analysis. When the alley is clear, the scraper operates at high speed for maximum productivity. When animals, obstacles, or hazardous conditions are detected, the system automatically reduces speed or stops, dynamically balancing productivity with safety.
Solution Approach 2:
The system uses real-time feedback from image processing to control scraper speed. The camera continuously monitors the alley ahead, and the image processing results provide immediate feedback to the control system, which adjusts the motor speed accordingly - maintaining high speed during safe conditions and reducing speed when potential hazards are detected, thereby preventing collisions while maximizing cleaning efficiency.
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
The system enhances the efficiency and safety of manure handling by dynamically adjusting the scraper's route, speed, and cleaning schedule in response to real-time conditions, reducing energy consumption and preventing collisions with animals or obstacles.
Implementation Method 1
One or more cameras are mounted along an alley where a scraper is to run... The cameras obtain/capture images, which may be provided to a processing unit provided/configured with/ adapted for image processing
Data Source
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AI summary
A method and arrangement is provided for controlling the operation of a manure scraper based on information obtained from one or more cameras mounted such as to capture images of the area of operation of the scraper.The solution enables a more efficient use of a widely spread technology for manure handling.