研究目的
To propose a novel and cost-effective technique (LEDCOM) for data communication in precision agriculture that combines ground sensors and UAVs using computer vision methods to analyze crop site data.
研究成果
The proposed LEDCOM methodology offers a novel approach for data communication in precision agriculture, addressing congestion of traditional wireless sensor networks and reducing power consumption. It is cost-effective and shows promising performance in recognizing LED array binary patterns.
研究不足
The presented idea is tested only under sunny and bright conditions. High resolution images are best suited for this problem.
1:Experimental Design and Method Selection:
The methodology involves encoding ground sensor data into LED patterns, capturing these patterns with UAV imaging sensors, and decoding them using computer vision techniques.
2:Sample Selection and Data Sources:
Images of LED arrays with 4, 5, and 6 LEDs were captured under sunny conditions.
3:List of Experimental Equipment and Materials:
Arduino UNO Micro-controller Board, LED arrays, mobile phone with 12MP camera, Parrot ARDrone
4:0, Raspberry Pi 3 board. Experimental Procedures and Operational Workflow:
Sensor data is encoded into binary patterns on LED arrays, images are captured by UAV, and KAZE features are used for template matching to decode the patterns.
5:Data Analysis Methods:
KAZE features are extracted and matched between template and input images to classify LED states.
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