Crop Detection System With Integrated LED Lighting And Thermal Management
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current crop detection systems in agriculture face challenges in reliably detecting plants under varying field conditions, including ambient lighting variations, and require effective thermal management to operate efficiently in harsh environments.
Innovation Solution
A crop detection system incorporating a set of sensors, Light-Emitting Diodes (LEDs), and a computing system, which provides supplemental lighting and thermal management to enhance plant detection and localization, and can be integrated with agricultural implements for precision operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If supplemental lighting is added to improve crop detection under varying ambient lighting conditions, then detection reliability is improved, but device complexity and energy consumption increase
Solution Approach 1:
The patent combines multiple functions into a single integrated housing unit: optical sensors for crop detection, LEDs for supplemental lighting, and thermal management components all housed together. This merging approach improves detection reliability under varying lighting conditions while controlling overall system complexity through integration rather than separate components.
Solution Approach 2:
The housing structure serves multiple functions simultaneously: it provides mechanical protection for sensors, mounts the LED arrays for lighting, incorporates thermal management features, and facilitates mounting to agricultural implements. This multi-functionality approach addresses the technical contradiction by achieving improved detection reliability while avoiding proportional increases in system complexity.
2Reliability
If thermal management components are added to operate efficiently in harsh environments, then operational reliability is improved, but device complexity increases
Solution Approach 1:
Thermal management components are integrated within the same housing that contains the optical sensors and LEDs. This consolidation approach ensures operational reliability in harsh thermal environments while controlling system complexity through unified design rather than separate thermal management systems.
3Volume of moving object
If multiple sensors and LEDs are integrated into a single housing, then space utilization is improved, but manufacturing complexity increases
Solution Approach 1:
The housing is designed as a modular unit that can be manufactured separately and then integrated with agricultural implements. This segmentation approach allows for simplified manufacturing of the sensor-LED-thermal management assembly while achieving compact integration when deployed, thus improving space utilization without excessive manufacturing complexity.
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 enables reliable crop detection and localization across diverse field conditions, reduces the need for manual weeding, and operates effectively in harsh environments with improved thermal management, facilitating precision agricultural operations.
Implementation Method 1
A crop detection system incorporating a set of sensors, Light-Emitting Diodes (LEDs), and a computing system, which provides supplemental lighting
Data Source
AI summary
A system for crop detection and/or analysis can include a set of sensors; a plurality of Light-Emitting Diodes (LEDs); a computing system; a housing; and a set of thermal components. Additionally or alternatively, the system can include any other suitable components. A method for crop detection and/or analysis can include any or all of: activating a set of lighting elements; collecting a set of images; and processing the set of images. Additionally or alternatively, the method can include any or all of: actuating and/or otherwise activating a set of implements; training and/or updating (e.g., retraining) a set of models used in processing the set of images; and/or any other suitable processes.