A REVIEW OF SMART FISH FARMING SYSTEMS

Yıl 2016, Cilt: 2 Sayı: 4, 193 - 200, 03.08.2016

Faizan Hasan Mustafa Awangku Hassanal Bahar Pengiran Bagul Shigeharu SENOO Senoo Rossita Shapawi

https://doi.org/10.3153/JAEFR16021

Öz

This paper reviews smart fish
farming systems that demonstrate how complex science and technology can be made
easy for application in seafood production systems. In this context, the focus
of this paper is on the use of artificial intelligence (AI) in fish culture. AI
mimics some of the capabilities of human brain via its Artificial Neural
Network (ANN) in performing certain tasks in a fish hatchery that are crucial
for aquaculture systems. Water quality is of utmost importance for survival,
growth and all other living activities of captive stocks of fish.  The AI-based systems can be designed for
controlling the main parameters of water quality such as salinity, dissolved
oxygen, pH and temperature. This systems approach uses software application
that runs on an application server connected to multi-parameter water quality
meters such as those offered by YSI. The software captures these parameter
values from YSI device and checks if they are within the optimum range. If not,
then an alarm system is triggered for immediate remedial action that can be
executed by personnel handling the hatchery management roles. This improves
accuracy, saves cost and action time to ensure sustainability life-supporting
system in the hatchery. Despite complexity in evolving this system, the
application is simple enough to be operated by an organized fish farming
community.  Because this study introduces
a rather new approach to aquaculture management, presentation of a detailed
background scenario was deemed necessary to put the pertinent issues in the
right perspective. 

Anahtar Kelimeler

Smart, Fish farming, Innovation, Tech-nology, Community benefits

Kaynakça

• Bechtold, W.R. (1993). A practical guide to expert systems: Part A. Instrumentation and Control Systems, 66, 41-43.
• Bechtold, W.R. (1994). A practical guide to expert systems: Part B. Instrumentation and Control Systems, 67, 75-78.
• Fridley, R.B. (1993). Constraints to marine aquaculture: what role can engineering and technology play? In: J.K. Wang (ed.), Techniques for Modern Aquaculture (pp. 1-7). American Society of Agricultural Engineers, St. Joseph, MI.
• Hansen, E. (1987). Computer-aided control and monitoring of aquaculture plants. In: L.G. Balchen (ed.), Automation and Data Processing in Aquaculture (pp. 187-192). Pergamon Press, Oxford.
• Hayden, A. (1997). Current and potential regulation of open ocean aquaculture. In: C.E. Helsley (ed., Open Ocean Aquaculture 1997: Chartering the Future of Ocean Farming (pp. 3-14), Proceedings of the International Conference University of Hawaii Sea Grant College Program, Honolulu, HI.
• Helsley, C. (1997). Open ocean aquaculture conference summary, commentary and thoughts for the future. In: Helsley, C.E. (ed.), Open Ocean Aquaculture 1997, Chartering the Future of Ocean Farming, Proceedings of the International Conference (University of Hawaii Sea Grant College Program, Honolulu, HI.
• Hoy, L.B. (1985). A microcomputer-based system for feed control, temperature control and temperature recording in an experimental fish hatchery. Computers and Electronics in Agriculture 1, 105-110.
• Jiang, H., Ding, W., Ali, M. & Wu, X. (2012). IEA/AEE, pages 104-113. Springer-Verlag, Berlin.
• Lee, P.G. (1995). A review of automated control systems for aquaculture and design criteria for their implementation. Aquaculture Engineering 14, 205-227.
• Lee, P.G. (2000). Process control and artificial intelligence software for aquaculture. Aquacultural Engineering 23, 13-36.
• McCoy, H.D. (1993). Open ocean fish farming. Aquaculture Management 19, 66-74.
• Munasinghe, L., Gempesaw, C.M., Bacon, J.R., Lussier, W.W. & Konwar, L. (1993). AMACS: a user-unfriendly windows-based aquaculture monitoring and controlling software. In: Wang, L.K. (ed.), Techniques for Modern Aquaculture, (pp. 71-80), American Society of Agricultural Engineers, St. Joseph, MI.
• Phillip, G.L. (2000). Process control and artificial intelligence software for aquqaculture. Aquacultural Engineering 23, 13-36.
• Rusch, K.A. & Malone, R.F. (1993). A micro-computer control and monitoring strategy applied to aquaculture. In: L.K. Wang, L.K. (ed.). Techniques for Modern Aquaculture (pp. 53 – 60), (American Society of Agricultural Engineers, St. Joseph, MI.
• Turk, P.E., Lawrence, A.L. & Lee, P.G. (1997). Design and operation of an environmentally isolated marine shrimp broodstock culture system using closed, recirculating water filtration. In: Advances in Aquacultural Engineering (pp. 209-218), Northeast Regional Engineering Service, Cornell, NY.
• Whitsell, A., Whitson, L.L. & Lee, P.G. (1997). A machine vision system for aquaculture: real-time identification of individual animals and estimation of animal activity. In: Advances in Aquacultural Engineering (pp. 112-128), Northeast Regional Agricultural Engineering Service, Cornell, NY.
• Whitson, L., Turk, P. & Lee, P.G. (1993). Biological denitrification in closed recirculating marine culture system. In: Techniques for Modern Aquaculture (Wang, J.K., ed.), (pp. 458-466), American Society of Agricultural Engineers, St. Joseph, MI.
• Whitson, L., Turk, P. & Lee, P.G. (1993). Biological denitrification in closed recirculating marine culture system. In: Wang, J.K. (ed.), Techniques for Modern Aquaculture American Society of Agricultural Engineers, St. Joseph, MI.