DOI QR코드

DOI QR Code

A Study on Portable Green-algae Remover Device based on Arduino and OpenCV using Do Sensor and Raspberry Pi Camera

DO 센서와 라즈베리파이 카메라를 활용한 아두이노와 OpenCV기반의 이동식 녹조제거장치에 관한 연구

  • 김민섭 (상명대학교 휴먼지능로봇공학과) ;
  • 김예지 (상명대학교 휴먼지능로봇공학과) ;
  • 임예은 (상명대학교 휴먼지능로봇공학과) ;
  • 황유성 (상명대학교 휴먼지능로봇공학과) ;
  • 백수황 (상명대학교 휴먼지능로봇공학과)
  • Received : 2022.06.28
  • Accepted : 2022.08.17
  • Published : 2022.08.31

Abstract

In this paper, we implemented an algae removal device that recognizes and removes algae existing in water using Raspberry Pi camera and DO (Dissolved Oxygen) sensor. The Raspberry Pi board recognizes the color of green algae by converting the RGB values obtained from the camera into HSV. Through this, the location of the algae is identified and when the amount of dissolved oxygen's decrease at the location is more than the reference value using the DO sensor, the algae removal device is driven to spray the algae removal solution. Raspberry Pi's camera uses OpenCV, and the motor movement is controlled according to the output value of the DO sensor and the result of the camera's green algae recognition. Algae recognition and spraying of algae removal solution were implemented through Arduino and Raspberry Pi, and the feasibility of the proposed portable algae removal device was verified through experiments.

본 논문에서는 라즈베리파이 카메라와 DO(Dissolved Oxygen)센서를 사용하여 수중에 존재하는 녹조를 인식하고 녹조를 제거하는 기능을 갖는 녹조제거장치를 구현하였다. 라즈베리파이 보드는 카메라로부터 취득한 RGB 값을 HSV로 변환하여 녹조의 색을 인식한다. 이를 통해 녹조의 위치를 파악하고, DO 센서를 활용해 해당 위치의 용존산소량의 감소량이 기준치 이상일 경우 녹조제거장치가 녹조 제거 용액을 살포하도록 구동한다. 라즈베리파이의 카메라는 OpenCV를 활용하였고, 모터의 움직임은 DO 센서의 출력값과 카메라의 녹조인식 결과에 따라 제어한다. 녹조인식 및 녹조제거용액의 살포 기능은 아두이노와 라즈베리파이를 통해 구현되었으며 실험을 통해 제안한 이동식 녹조제거장치의 타당성을 검증하였다.

Keywords

Acknowledgement

이 논문은 2021년도 정부(과학기술정보통신부)의 재원으로 한국연구재단의 지원을 받아 수행된 연구임(No. 2021R1F1A1061567). 위 논문은 "2022년 봄철학술대회 우수논문"입니다.

References

  1. Y. Cho, S. Jin, H. Choi, M. Ryu, and S. Yoo, "Estimation of the aesthetic and environmental costs of algal bloom," Environmental policy, vol. 24, no. 4, Dec. 2016, pp. 227-246.
  2. B. Kim, S. Sa, M. Kim, Y. Lee, and J. Kim, "The limiting nutrient of eutrophication in reservoirs of korea and the suggestion of a reinforced phosphorus standard for sewage treatment effluent," J. of the Korean Society for Water Quality, vol. 23, no. 4, 2007, pp. 512-517.
  3. Y. Lee, "Effect of lugol's iodine preservation on cyanobacterial biovolume and estimate of live cell biovolume using shrinkage ratio," J. of Korean Society on Water Environment, vol. 34, no. 4, 2018, pp. 375-381. https://doi.org/10.15681/KSWE.2018.34.4.375
  4. J. Shin, H. Yi, S. Jeong, and S. Hwang, "Construction of environmental friendly special-purpose ship for the removal of blue-green algae," Korean J. of Limnology, vol. 42, no. 3, 2009, pp. 404-406.
  5. J. Han, W. Park, J. Kim Y. Lee, J. Rho, Y. Kim, and B. Yoon, "The development of algae removal system to minimize the damage of algae bloom on freshwater," J. of the Korean Society for Marine Environmental Engineering, vol. 3, no. 1, 2000, pp. 62-69.
  6. Z. Lin and C. Kim, "Development of smart mirror system based on the raspberry pi," J. of the Korea Institute of Electronic Communication Sciences, vol. 16, no. 2, 2021, pp. 379-384. https://doi.org/10.13067/JKIECS.2021.16.2.379
  7. S. Oh, J. Lee, S. Lee, C. Park, and Y. Ko, "Design methodology of communication & control device for smart grid power facility based on DSP and raspberry pi," J. of the Korea Institute of Electronic Communication Sciences, vol. 16, no. 5, 2021, pp. 835-844. https://doi.org/10.13067/JKIECS.2021.16.5.835
  8. M. Ji, B. Kim, J. Kim, N. Park, and H. Park, "Study on the quadcopter for person search using PID control and HSV," J. of the Korea Institute of Electronic Communication Sciences, vol. 17, no. 1, 2022, pp. 139-146.
  9. D. Seo and K. Yoon, "A study on indoor air-quality improvement system using actuator," J. of Korean Institute of Information Technology, vol. 16, no. 1, 2021, pp. 183-190.
  10. J. Song, "Content-based image retrieval using HSV color and edge orientation," J. of Korean Institute of Information Technology, vol. 16, no. 5, 2018, pp. 113-118. https://doi.org/10.14801/jkiit.2018.16.5.113
  11. C. Park, J. Jeon, Y. Moon, and I. Eom, "Green algae detection using water body extraction and color information," J. of the Institute of Electronics and Information Engineers, vol. 56, no. 5, 2019, pp. 43-51. https://doi.org/10.5573/ieie.2019.56.5.43