Smart Shrimp Farming Using Internet of Things (IoT) and Fuzzy Logic

Michael Johan; Suharjito Suharjito

doi:10.21512/comtech.v14i2.8981

Authors

Michael Johan Bina Nusantara University https://orcid.org/0000-0001-9382-2078
Suharjito Bina Nusantara University

DOI:

https://doi.org/10.21512/comtech.v14i2.8981

Keywords:

smart shrimp farming, Internet of Things (IoT), Fuzzy Logic

Abstract

In the case of ponds with Litopenaeus Vannamei shrimp, water quality parameters play a significant role in shrimp growth. Leveraging technology enhances water quality to optimize growth and survivability in the shrimp farming industry. The research aimed to empower local farmers with smart shrimp farming technologies, including Information Technology (IT), such as the Internet of Things (IoT), and Fuzzy Logic. The research also involved a comparison between Litopenaeus Vannamei shrimp in two different aquariums: one serving as a control group and the other implementing IoT and Fuzzy Logic for a period of 30 days. The initial Litopenaeus Vannamei shrimp stocking was 135 shrimps for control aquariums and 132 for experimental aquariums. Then, the research used Arduino ESP 8266, Raspberry Pi 3, and SciKit-Fuzzy library to record and process the data. Through the application of IoT and Fuzzy Logic, the research successfully increases survivability by 6%, specific growth rate by 28%, and length by 8% in 30 days compared to conventional methods. The results highlight the potential use of technology in Litopenaeus Vannamei shrimp farming. The proposed system’s hardware and software architecture can be easily scaled to accommodate the needs of Litopenaeus Vannamei shrimp farmers with multiple ponds, offering flexibility and adaptability.

Dimensions

Plum Analytics

Author Biographies

Michael Johan, Bina Nusantara University

Computer Science Department, BINUS Graduate Program – Master of Computer Science

Suharjito, Bina Nusantara University

Industrial Engineering Department, BINUS Graduate Program – Master of Industrial Engineering

References

Abdelrahman, H. A., & Boyd, C. E. (2018). Effects of mechanical aeration on evaporation rate and water temperature in aquaculture ponds. Aquaculture Research, 49(6), 2184–2192.

Abdullah, M., Idrus, S. M., Yusof, K. M., Azmi, A. I., Ismail, W., Kamaludin, K. H., ... & Yusof, F. (2021). Field trial and performance evaluation of IoT smart aquaculture monitoring system for Brackish Water shrimp farm. International Journal of Nanoelectronics and Materials, 14(Special Issue), 237–243.

Agustianto, K., Kustiari, T., Destarianto, P., & Wiryawan, I. G. (2021). Development of Realtime Surface Modeling Vehicle for Shrimp Ponds (ReSMeV-SP). In IOP Conference Series: Earth and Environmental Science (Vol. 672). IOP Publishing.

Atmaja, G. C. T., Putrada, A. G., & Rakhmatsyah, A. (2018). Optimasi tingkat hidup udang crystal red dengan menerapkan metode Fuzzy Logic Berbasis IoT. eProceedings of Engineering, 5(2), 3649–3656.

Balai Perikanan Budidaya Air Payau Situbondo. (2021). Budidaya udang Vaname di tambak milenial (Millenial Shrimp Farming/MSF). Retrieved from https://kkp.go.id/djpb/bpbapsitubondo/artikel/34255-budidaya-udang-vaname-di-tambak-milenial-millenial-shrimp-farming-msf

Bokingkito Jr, P. B., & Caparida, L. T. (2018). Using Fuzzy Logic for real-time water quality assessment monitoring system. In Proceedings of the 2018 2nd International Conference on Automation, Control and Robots (pp. 21–25).

Chakravarty, M. S., Ganesh, P. R. C., Amarnath, D., Sudha, B. S., & Babu, T. S. (2016). Spatial variation of water quality parameters of shrimp (Litopenaeus Vannamei) culture ponds at Narsapurapupeta, Kajuluru and Kaikavolu villages of East Godavari District, Andhra Pradesh. International Journal of Fisheries and Aquatic Studies, 4(4), 390–395.

Costea, C. R., Abrudean, M., Silaghi, H. M., & Silaghi, M. A. (2010). Control of flow rate with Fuzzy Logic for ball mill. In 2010 IEEE International Conference on Automation, Quality and Testing, Robotics (AQTR) (pp. 1–4). IEEE.

De Araújo, A. L. A. C., Da Silva Moreira, T., De Menezes, T. B. B., De Lima, R. L., De Mesquita Facundo, G., Da Silva, J. W. A., ... & Costa, F. H. F. (2020). Use of Lithothamnium sp.(Algen® Oceana) in Penaeus Vannamei culture. Brazilian Journal of Development, 6(5), 28268–28283.

DFRobot. (n.d.). Gravity: Analog dissolved oxygen sensor / meter kit for Arduino. Retrieved from https://www.dfrobot.com/product-1628.html

Durai, V., Alagappan, M., & Yuvarajan, P. (2021). Importance of water quality management in Whiteleg shrimp (Penaeus Vannamei) farming. AgriCos e-Newsletter, 2, 17–20.

Djunaidi, M., Setiawan, E., & Andista, F. W. (2005). Penentuan jumlah produksi dengan aplikasi metode Fuzzy–Mamdani. Jurnal Ilmiah Teknik Industri, 4(2), 95–104.

Firouzi, R., Rahmani, R., & Kanter, T. (2020). An autonomic IoT gateway for smart home using Fuzzy Logic Reasoner. Procedia Computer Science, 177, 102–111.

Herman, H., Adidrana, D., Surantha, N., & Suharjito, S. (2019). Hydroponic nutrient control system based on Internet of Things. CommIT (Communication and Information Technology) Journal, 13(2), 105–111.

Kumar, G. S., & Saminadan, V. (2019). Fuzzy Logic based Truly Random number generator for high-speed BIST applications. Microprocessors and Microsystems, 69(September), 188–197.

Manurung, A. P., Yusanti, I. A., & Haris, R. B. K. (2018). Tingkat Pertumbuhan dan kelangsungan hidup, pada pembesaran udang Galah (Macrobrachium Rosenbergii De Man 1879) Strain Siratu dan Strain Gimacro II. Jurnal Ilmu-Ilmu Perikanan dan Budidaya Perairan, 13(1), 27–36.

Ni, M., Yuan, J. L., Liu, M., & Gu, Z. M. (2018). Assessment of water quality and Phytoplankton community of Limpenaeus Vannamei pond in intertidal zone of Hangzhou Bay, China. Aquaculture Reports, 11, 53–58.

Ramadhan, G. K., & Utama, D. N. (2019). Fuzzy Tsukamoto based decision support model for purchase decision in pharmacy company. International Journal of Recent Technology and Engineering (IJRTE), 8(4), 2277–3878.

Rout, R. R., Vemireddy, S., Raul, S. K., & Somayajulu, D. V. (2020). Fuzzy Logic-based emergency vehicle routing: An IoT system development for smart city applications. Computers & Electrical Engineering, 88(December).

Rozie, F., Syarif, I., & Al Rasyid, M. U. (2020). Design and implementation of intelligent aquaponics monitoring system based on IoT. In International Electronics Symposium (IES), (pp. 534–540). IEEE.

Rusli, M. (2017). Dasar perancangan kendali logika Fuzzy. Universitas Brawijaya Press.

Shandikri, R., & Erfianto, B. (2021). Internet of Things: Water quality classifying based on estimation dissolved oxygen solubility and estimation unionized ammonia for small-scales freshwater aquaculture. KINETIK: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, 6(3), 259–268.

Sharawy, Z. Z., Abbas, E. M., Abdelkhalek, N. K., Ashry, O. A., Abd El-Fattah, L. S., El-Sawy, M. A., ... & El-Haroun, E. (2022). Effect of organic carbon source and stocking densities on growth indices, water microflora, and immune-related genes expression of Litopenaeus Vannamei Larvae in intensive culture. Aquaculture, 546.

Sharawy, Z. Z., Ashour, M., Abbas, E., Ashry, O., Helal, M., Nazmi, H., ... & Goda, A. (2020). Effects of dietary marine microalgae, Tetraselmis suecica, on production, gene expression, protein markers and bacterial count of Pacific White shrimp Litopenaeus Vannamei. Aquaculture Research, 51(6), 2216–2228.

Spolaor, S., Fuchs, C., Cazzaniga, P., Kaymak, U., Besozzi, D., & Nobile, M. S. (2020). Simpful: A user-friendly python library for Fuzzy Logic. International Journal of Computational Intelligence Systems, 13(1), 1687–1698.

Sukaridhoto, S., Basuki, D. K., Maulana, J., Arridha, R., & Avianto, T. (2017). Smart environment monitoring and analytic in real-time system for Vannamei shrimp. Journal of Telecomunication, Electronic,

and Computer Engineering, X(X), 1–6.

Tacon, A. G., Jory, D., & Nunes, A. (2013). Shrimp feed management: Issues and perspectives. On-Farm Feeding and Feed Management in Aquaculture, 583, 481–488.

Tatas, K., & Chrysostomou, C. (2017). Hardware implementation of dynamic Fuzzy Logic based routing in Network-on-Chip. Microprocessors and Microsystems, 52, 80–88.

Thakur, K., Patanasatienkul, T., Laurin, E., Vanderstichel, R., Corsin, F., & Hammell, L. (2018). Production characteristics of intensive Whiteleg shrimp (Litopenaeus Vannamei) farming in four Vietnam Provinces. Aquaculture Research, 49(8), 2625–2632.

Utama, D. N., Safitri, I. M., Safira, N. R., Alfaleh, A. L., & Singgih, F. R. (2020). Fuzzy based decision support model on determining the most eligible location of national multi-sport event. International Journal of Advanced Trends in Computer Science and Engineering, 9(4), 6140–6146.

Valencia-Castañeda, G., Frías-Espericueta, M. G., Vanegas-Pérez, R. C., Pérez-Ramírez, J. A., Chávez-Sánchez, M. C., & Páez-Osuna, F. (2018). Acute toxicity of ammonia, nitrite and nitrate to shrimp Litopenaeus Vannamei postlarvae in low-salinity water. Bulletin of Environmental Contamination and Toxicology, 101, 229–234.

Venkateswarlu, V., Seshaiah, P. V., Arun, P., & Behra, P. C. (2019). A study on water quality parameters in shrimp L. Vannamei semi-intensive grow out culture farms in coastal districts of Andhra Pradesh, India. International Journal of Fisheries and Aquatic Studies, 7(4), 394–399.

Yuswantoro, D., Natan, O., Angga, A. N., Gunawan, A. I., Dewantara, B. S. B., & Kurniawan, M. A. (2018). Fuzzy logic-based control system for dissolved oxygen control on indoor shrimp cultivation. In 2018 International Electronics Symposium on Engineering Technology and Applications (IES-ETA) (pp. 37–42). IEEE.