Information fusion in aquaculture: a state-of the art review

doi:10.15302/J-FASE-2016111

Front. Agr. Sci. Eng.

2016, Vol. 3

Issue (3) : 206-221 https://doi.org/10.15302/J-FASE-2016111

REVIEW

Information fusion in aquaculture: a state-of the art review

Shahbaz Gul HASSAN^1,^2,^3,^4,⁵,Murtaza HASAN⁶,Daoliang LI^1,^2,^3,^4,⁵(

)

¹. College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
². China-EU Center for Information and Communication Technologies in Agriculture, China Agricultural University, Beijing 100083, China
³. Beijing Engineering and Technology Research Center for Internet of Things in Agriculture, Beijing 100083, China
⁴. Key Laboratory of Agricultural Information Acquisition Technology, Ministry of Agriculture, Beijing 100083, China
⁵. Beijing Engineering Center for Advanced Sensors in Agriculture, Beijing 100083, China
⁶. Department of Materials Science and Engineering, College of Engineering, Peking University, Beijing 100871, China

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Abstract

Efficient fish feeding is currently one of biggest challenges in aquaculture to enhance the production of fish quality and quantity. In this review, an information fusion approach was used to integrate multi-sensor and computer vision techniques to make fish feeding more efficient and accurate. Information fusion is a well-known technology that has been used in different fields of artificial intelligence, robotics, image processing, computer vision, sensors and wireless sensor networks. Information fusion in aquaculture is a growing field of research that is used to enhance the performance of an “industrialized” ecosystem. This review study surveys different fish feeding systems using multi-sensor data fusion, computer vision technology, and different food intake models. In addition, different fish behavior monitoring techniques are discussed, and the parameters of water, pH, dissolved oxygen, turbidity, temperature etc., necessary for the fish feeding process, are examined. Moreover, the different waste management and fish disease diagnosis techniques using different technologies, expert systems and modeling are also reviewed.

Keywords aquaculture computer vision information fusion modeling sensor

Corresponding Author(s): Daoliang LI

Just Accepted Date: 01 September 2016 Online First Date: 13 September 2016 Issue Date: 21 September 2016

Cite this article:

Shahbaz Gul HASSAN,Murtaza HASAN,Daoliang LI. Information fusion in aquaculture: a state-of the art review[J]. Front. Agr. Sci. Eng. , 2016, 3(3): 206-221.

URL:

https://academic.hep.com.cn/fase/EN/10.15302/J-FASE-2016111
https://academic.hep.com.cn/fase/EN/Y2016/V3/I3/206

Fig.1 Information fusion approach for water quality monitoring in aquaculture

Fig.2 The information fusion approach for fish feeding in aquaculture

Fig.3 Information fusion approach for fish behavior monitoring in aquaculture

Fig.4 Information fusion approach for fish disease diagnosis in aquaculture

Fig.5 Information fusion approach for waste management in aquaculture

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