Geo-Spatial Crop Image Matching for Precision Targeted Spraying
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Solution Overview
Problem
Current agricultural techniques for producing and harvesting crops are inefficient, as they often require significant land, chemicals, time, labor, and resources, posing challenges for sustainable food production as the global population grows.
Innovation Solution
An agricultural observation and treatment system that uses cameras, light emitting devices, and a treatment device mounted on a gimbal to identify and treat specific agricultural objects with precision, utilizing artificial intelligence and computer vision to determine target locations and apply treatments efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional agricultural techniques are used for producing and harvesting crops, then food production can be maintained with current methods, but significant land, chemicals, time, labor, and resources are required, making the process inefficient and unsustainable
Solution Approach 1:
The patent replaces traditional mechanical and chemical agricultural systems with an optical-electronic system. Image sensors capture visual data of crops, AI algorithms process this data to identify treatment needs, and treatment devices precisely apply treatments only where needed. This substitution of mechanical/chemical methods with optical-electronic intelligence reduces resource consumption while improving productivity
Solution Approach 2:
The system implements local quality by applying treatments selectively to specific locations rather than uniformly across entire fields. The image sensors identify individual plants or regions requiring treatment, and the treatment device delivers chemicals or other treatments only to those specific locations, reducing overall chemical usage while maintaining effective crop management
2Productivity
If traditional crop production methods are used, then current agricultural practices can be maintained, but the amount of land and chemicals required poses challenges for sustainable food production
Solution Approach 1:
The system replaces blanket chemical application methods with precision-targeted delivery. Image sensors detect crop conditions and AI algorithms determine treatment requirements, enabling chemical applications only where and when needed. This substitution reduces harmful chemical exposure to the environment while maintaining crop production output
Solution Approach 2:
The patent introduces an intermediary intelligence layer between crop monitoring and treatment application. AI algorithms analyze image data to identify which crops need treatment and where to apply treatments, acting as an intermediary that prevents unnecessary chemical application and reduces environmental harm while maintaining productivity
3Ease of operation
If incremental agricultural techniques are used, then existing farming methods can be maintained, but the amount of land, chemicals, time, labor, and other costs remain challenging
Solution Approach 1:
The system enables continuous monitoring and treatment operations through automated image capture and processing. Image sensors continuously scan crops, AI algorithms continuously analyze data and identify treatment needs, and treatment devices continuously apply treatments as needed. This continuous automated operation reduces time consumption compared to manual inspection and treatment application while maintaining ease of operation
Solution Approach 2:
The system implements self-service by enabling the agricultural operation to monitor and treat itself without constant human intervention. Image sensors automatically capture crop data, AI algorithms automatically analyze conditions and determine treatment requirements, and treatment devices automatically apply treatments. This self-service capability reduces labor requirements and time consumption while keeping operations simple
Data Source
AI summary
Various embodiments of an apparatus, methods, systems and computer program products described herein are directed to an agricultural observation and treatment system and method of operation. The agricultural treatment system may determine a first real-world geo-spatial location of the treatment system. The system can receive captured images depicting real-world agricultural objects of a geographic scene. The system can associate captured images with the determined geo-spatial location of the treatment system. The treatment system can identify, from a group of mapped and indexed images, images having a second real-word geo-spatial location that is proximate with the first real-world geo-spatial location. The treatment system can compare at least a portion of the identified images with at least a portion of the captured images. The treatment system can determine a target object and emit a fluid projectile at the target object using a treatment device.