US20260096547
2026-04-09
Human necessities
A01M7/0089
The patent application outlines a sophisticated system for controlling crop sprayers using advanced technologies. It leverages perception devices and machine learning to optimize spray coverage. The system adjusts tuning parameters dynamically, enhancing efficiency and consistency in agricultural spraying operations. This approach aims to improve the overall effectiveness of sprayers by minimizing delays and ensuring precise application of materials.
The technology is applicable in agricultural settings where sprayers are used to distribute various materials such as pesticides, fungicides, insecticides, herbicides, and fertilizers. These materials are converted into droplets for application over crops. The system's design addresses the need for improved coverage and reduced delays, which are common challenges in conventional spraying methods.
The system comprises perception devices that gather data on spray coverage and processing circuitry that uses machine learning to adjust tuning parameters. These adjustments are based on real-time perception data, differing from pre-set parameters. The system includes methods and non-transitory computer-readable media to execute these processes, ensuring the sprayer operates with optimal settings for each specific situation.
The system can be integrated into existing agricultural machinery, such as tractors pulling sprayers or self-propelled sprayers. It includes components like processors, memory, communication devices, and user interfaces. The system may be autonomous or operator-assisted, with capabilities for both electronic and mechanical control of the sprayers. By utilizing these technologies, the system aims to enhance precision and reduce operational delays in agricultural spraying tasks.