Smart approaches to Aquaponics 4.0 with focus on water quality - Comprehensive review

被引:5
作者
Chandramenon, Praveen [1 ]
Aggoun, Amar [1 ]
Tchuenbou-Magaia, Fideline [1 ]
机构
[1] Univ Wolverhampton, Ctr Engn Innovat & Res, Sch Engn Comp & Math Sci, Energy & Green Technol Res Grp, Wolverhampton WV1 1LY, England
关键词
Aquaponics; 4.0; Water replenishment; Water quality; Artificial Intelligence; Internet of Things; OREOCHROMIS-NILOTICUS; NITROGEN RECOVERY; SYSTEM; PLANT; FISH; PERFORMANCE; AQUACULTURE; NITRATE; GROWTH; ENERGY;
D O I
10.1016/j.compag.2024.109256
中图分类号
S [农业科学];
学科分类号
09 ;
摘要
The fast growth of the world population associated with the ever-increasing need for food and the significant contribution of agriculture to anthropogenic global warming is driving the changes from conventional farming approaches to innovative and sustainable agriculture ones. One of these approaches is aquaculture which is founded on the principle of circular economy combining aquaculture and hydroponics in symbiose with aquaculture waste serving as nutrients for plant growth. Conventional Aquaponics has evolved to Aquaponics 4.0 with a fully automated and remote-controlled system for producing foods at an industrial scale. The implementation of the Internet of Things (IoT) and Artificial Intelligence (AI) could simplify farmers' tasks with remote operations while allowing them to achieve automatic and precise control of inputs and outputs as well as to improve the overall efficiency of the system. This review focuses on the use of these smart technologies to analyze, monitor, and maintain good water quality and appropriate replenishment in Aquaponics systems. The identified research gap and future possible contributions in this area are also discussed.
引用
收藏
页数:12
相关论文
共 94 条
[1]  
Abbasi R., 2021, P CIRP, V100, P55, DOI [10.1016/j.procir.2021.05.009, DOI 10.1016/J.PROCIR.2021.05.009]
[2]  
Abbasi R., 2023, Crop diagnostic system: A robust disease detection and management system for leafy green crops grown in an aquaponics facility-NC-ND license, DOI [10.1016/j.aiia.2023.09.001, DOI 10.1016/J.AIIA.2023.09.001]
[3]   An ontology model to represent aquaponics 4.0 system's knowledge [J].
Abbasi, Rabiya ;
Martinez, Pablo ;
Ahmad, Rafiq .
INFORMATION PROCESSING IN AGRICULTURE, 2022, 9 (04) :514-532
[4]   An Internet-of-Things Enabled Smart Sensing System for Nitrate Monitoring [J].
Alahi, Md. Eshrat E. ;
Pereira-Ishak, Najid ;
Mukhopadhyay, Subhas Chandra ;
Burkitt, Lucy .
IEEE INTERNET OF THINGS JOURNAL, 2018, 5 (06) :4409-4417
[5]  
Alajas O.J., 2021, 2021 IEEE 13 INT C H, P1, DOI [10.1109/HNICEM54116.2021.9731946, DOI 10.1109/HNICEM54116.2021.9731946]
[6]   Water IoT Monitoring System for Aquaponics Health and Fishery Applications [J].
Alselek, Mohammad ;
Alcaraz-Calero, Jose M. ;
Segura-Garcia, Jaume ;
Wang, Qi .
SENSORS, 2022, 22 (19)
[7]  
Anita Bhatnagar Anita Bhatnagar, 2013, International Journal of Environmental Sciences, V3, P1980
[8]   Is Aquaponics Beneficial in Terms of Fish and Plant Growth and Water Quality in Comparison to Separate Recirculating Aquaculture and Hydroponic Systems? [J].
Atique, Faiqa ;
Lindholm-Lehto, Petra ;
Pirhonen, Juhani .
WATER, 2022, 14 (09)
[9]   Smart Aquaponics with Disease Detection [J].
Barosa, Roysing ;
Hassen, Sayed Issamuddine Sayed ;
Nagowah, Leckraj .
2019 SECOND INTERNATIONAL CONFERENCE ON NEXT GENERATION COMPUTING APPLICATIONS 2019 (NEXTCOMP 2019), 2019,
[10]   Effect of pH on Cucumber Growth and Nutrient Availability in a Decoupled Aquaponic System with Minimal Solids Removal [J].
Blanchard, Caroline ;
Wells, Daniel E. ;
Pickens, Jeremy M. ;
Blersch, David M. .
HORTICULTURAE, 2020, 6 (01)