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Related Concept Videos

Light Acquisition02:16

Light Acquisition

In order to produce glucose, plants need to capture sufficient light energy. Many modern plants have evolved leaves specialized for light acquisition. Leaves can be only millimeters in width or tens of meters wide, depending on the environment. Due to competition for sunlight, evolution has driven the evolution of increasingly larger leaves and taller plants, to avoid shading by their neighbors with contaminant elaboration of root architecture and mechanisms to transport water and nutrients.

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Farm Monitoring System with Drones and Optical Camera Communication.

Shinnosuke Kondo1, Naoto Yoshimoto2, Yu Nakayama1

  • 1Department of Electrical Engineering and Computer Science, Tokyo University of Agriculture and Technology, Tokyo 184-8588, Japan.

Sensors (Basel, Switzerland)
|September 28, 2024
PubMed
Summary

This study introduces a low-cost agricultural sensor network using drones and Optical Camera Communication (OCC). The system enables high-density sensing by transmitting data via LED panels to a drone-mounted camera, reducing costs and improving accessibility.

Keywords:
LEDdroneoptical camera communicationpoint-to-multipoint communicationsensor network

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Area of Science:

  • Agricultural Technology
  • Wireless Communication
  • Robotics

Background:

  • Drones and sensors are vital for modern agriculture, but high infrastructure costs limit widespread adoption of high-density sensing.
  • Existing communication methods face challenges in areas with underdeveloped infrastructure or radio silence.

Purpose of the Study:

  • To propose a cost-effective agricultural sensor network system utilizing drones and Optical Camera Communication (OCC).
  • To enable high-density sensing in remote or infrastructure-limited agricultural areas.
  • To develop an efficient drone trajectory control algorithm for data collection.

Main Methods:

  • Developed an agricultural sensor network transmitting data from LED panels to a drone-mounted camera via OCC.
  • Proposed a novel trajectory control algorithm for the drone to optimize data collection.
  • Trained a YOLOv5 object detection model using 5178 images of LED panels captured by the drone.
  • Utilized On-Off Keying (OOK) modulation for data transmission.

Main Results:

  • Computer simulations showed the proposed trajectory algorithm reduced drone flight time by 30% compared to shortest-path algorithms.
  • Real-world experiments achieved a bit error rate (BER) below 10-3 using OOK modulation.
  • Demonstrated the system's applicability in a leaf mustard farm, collecting significant image data.

Conclusions:

  • The proposed drone-based OCC system offers a viable, low-cost solution for high-density agricultural sensing.
  • The system is effective even in environments with limited infrastructure or radio silence.
  • The developed trajectory control algorithm enhances data collection efficiency.