UAV Fruit Counting with RF Tree Mapping for Dense Orchards
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Solution Overview
Problem
Conventional methods for fruit counting in fruit trees are inaccurate due to human subjectivity, weather-related fluctuations, and limitations in capturing images from ground-based cameras, which result in blind spots and overlapping measurements in dense orchards.
Innovation Solution
A fruit quantity measurement system using an unmanned aerial vehicle equipped with RGB and infrared cameras, GPS units, and RF transmitters, coupled with a monitoring server for deep learning-based fruit recognition, to accurately count fruits by analyzing images from above and matching location data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If ground-based cameras are used for fruit counting, then the system is simple to operate, but blind spots and overlapping measurements occur in dense orchards
Solution Approach 1:
The patent transitions from ground-based two-dimensional camera viewing to aerial three-dimensional imaging. By deploying cameras on UAVs that capture images from above, the system eliminates blind spots and overlapping issues inherent in ground-level perspectives, enabling complete coverage of dense orchard canopies without requiring complex ground-based camera arrangements.
2Device complexity
If manual sample survey methods are used for fruit counting, then the equipment complexity is low, but human subjectivity reduces accuracy
Solution Approach 1:
The patent replaces manual mechanical counting methods with automated optical detection and image processing systems. UAV-mounted cameras capture fruit images, and computer vision algorithms automatically identify and count fruits, eliminating human subjectivity while maintaining relatively simple system architecture through the use of standard imaging equipment and software-based analysis.
3Measurement precision
If individual still images are captured for each fruit tree, then measurement precision can be maintained, but productivity decreases due to time-consuming manual processes
Solution Approach 1:
The patent implements continuous automated imaging and processing across the entire orchard. UAVs systematically flight over multiple fruit trees in sequence, capturing images continuously without manual intervention between trees. The image processing system simultaneously analyzes captured images, enabling high-speed processing of hundreds of trees that maintains per-tree measurement precision while dramatically increasing overall productivity compared to manual methods.
4Device complexity
If conventional fruit recognition methods are used, then the system is simple, but accuracy decreases due to weather-related fluctuations and pest damage
Solution Approach 1:
The patent performs preliminary identification and classification of fruits based on image analysis before final counting. The system pre-processes images to distinguish fruits from leaves, branches, and other background elements, and identifies damaged or abnormal fruits separately. This preliminary action enables more reliable counting by establishing baseline characteristics that account for weather-related variations and pest damage, improving measurement reliability without significantly increasing system complexity.
Data Source
AI summary
A fruit quantity measurement system includes an unmanned aerial vehicle configured to receive GPS information about a fruit tree region of a predetermined area and an RF signal transmitted from an RF transmitter installed for each fruit tree and provide fruit tree images captured using at least one image sensor while flying based on a predetermined flight plan over the fruit tree region, and a monitoring server configured to be connected to the unmanned aerial vehicle through a communication network to receive GPS information and an RF signal from the unmanned aerial vehicle, match and store location data for each fruit tree, analyze the fruit tree image, measure the number of fruits for each fruit tree, store fruit counting information, and provide the stored location data or fruit counting information for each fruit tree according to a request from a user terminal authorized in advance.