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양식장 환경 데이터 모니터링 시스템의 구현 및 성능 평가

Implementation and Performance Evaluation of Environmental Data Monitoring System for the Fish Farm

  • Wahyutama, Aria Bisma (Department of Information and Communication Engineering, Changwon National University) ;
  • Hwang, Mintae (Department of Information and Communication Engineering, Changwon National University)
  • 투고 : 2021.12.09
  • 심사 : 2021.12.22
  • 발행 : 2022.05.31

초록

본 논문은 양식장의 환경 데이터 모니터링 시스템 개발 및 성능 평가 결과를 담고있다. 하드웨어 개발을 위해 용존 산소량, 질소 이온 농도, 염도 및 해수 온도 데이터 수집을 위한 아날로그 센서들과 외부 온습도 및 위치 정보를 수집하기 위한 디지털 센서들을 이용하였으며, 이들 수집 데이터들을 클라우드 기반의 Firebase DB에 전달하기 위한 통신 모듈로 LoRa 송수신 세트를 이용하였다. Firebase에 저장되는 수집 데이터들은 웹 브라우저와 모바일 단말기 상에서 그래프 형태로 출력해 양식장 환경 데이터 변화를 실시간으로 관찰할 수 있도록 하였으며, 임계치를 지정해 수집 데이터가 이 범위를 벗어나는 경우 모바일 단말기 상에 실시간 알림이 도착하도록 구현하였다. 개발 시스템의 성능 평가를 위해 하드웨어 모듈에서부터 웹/모바일 애플리케이션까지 타임 스탬프 기반의 응답 시간을 측정한 결과 6.2초에서 6.85초 사이의 변화를 보여주고 있어 만족할 만한 결과임을 알 수 있었다.

This paper contains the results of the development and performance evaluation of the environmental data monitoring system for the fish farm. For the hardware development, the analogue sensor is used to collect dissolved oxygen, pH, salinity, and temperature of the fish farm water, and the digital sensor is used for collecting ambient temperature, humidity, and location information via a GPS module to be sent to cloud-based Firebase DB. A set of LoRa transmitters and receivers is used as a communication module to upload the collected data. The data stored in Firebase is retrieved as a graph on a web and mobile application to monitor the environmental data changes in real-time. A notification will be delivered if the collected data is outside the determined optimal value. To evaluate the performance of the developed system, a response time from hardware modules to web and mobile applications is ranging from 6.2 to 6.85 seconds, which indicates satisfactory results.

키워드

과제정보

This work was supported by Gyeongnam SW Convergence Cluster 2.0 under the contract

참고문헌

  1. Food and Agriculture Organization of the United Nations. The State of World Fisheries and Aquaculture 2020 [Internet]. Available: https://www.fao.org/state-of-fisheries-aquaculture.
  2. M. A. El Bably, H. H. Emeash, A. N. Mohamed, and N. R., "Influence of water quality on fish productivity," Journal of Veterinary Medical Research, vol. 20, no. 1, pp. 313-318, Mar. 2010. https://doi.org/10.21608/jvmr.2020.77634
  3. W. Khan, A. Vahab, A. Masood, and N. Hasan, "Water Quality Requirements and Management Strategies for Fish Farming A Case Study of Ponds Around Gurgaon Canal NUH Palwal," International Journal of Trend in Scientific Research and Development, vol. 2, no. 1, pp. 388-393, Dec. 2017. https://doi.org/10.31142/ijtsrd5914
  4. A. M. Helal, A. M. Attia, and M. M. Mustafa, "Water Conservation and Management of Fish Farm in Lake Mariout," Life Science Journal, vol. 14, no. 11, pp. 44-51, Jan. 2017.
  5. M. J. Sottile and R. G. Minnich, "Supermon: a high-speed cluster monitoring system," in Proceedings of the IEEE International Conference on Cluster Computing, Chicago: IL, USA, pp. 39-46, 2002.
  6. S. Saha, R. H. Rajib, and S. Kabir, "IoT Based Automated Fish Farm Aquaculture Monitoring System," in International Conference on Innovations in Science, Engineering and Technology (ICISET), Chittagong, Bangladesh, pp. 201-206, 2018.
  7. C. Tziortzioti, D. Amaxilatis, I. Mavrommati, and I. Chatzigiannakis, "IoT sensors in sea water environment: Ahoy! Experiences from a short summer trial," Electronic Notes in Theoretical Computer Science, vol. 343, pp. 117-130, May. 2019. https://doi.org/10.1016/j.entcs.2019.04.014
  8. Firebase. Firebase Realtime Database [Internet]. Available: https://firebase.google.com/docs/database.
  9. W. Chmielarz, "The usage of smartphone and mobile applications from the point of view of customers in Poland," Information (Switzerland) MDPI, vol. 11, no. 4, Apr. 2020.