This book highlights the fundamental association between aquaculture and engineering in classifying fish hunger behaviour by means of machine learning techniques. Understanding the underlying factors that affect fish growth is essential, since they have implications for higher productivity in fish farms. Computer vision and machine learning techniques make it possible to quantify the subjective perception of hunger behaviour and so allow food to be provided as necessary. The book analyses the conceptual framework of motion tracking, feeding schedule and prediction classifiers in order to classify the hunger state, and proposes a system comprising an automated feeder system, image-processing module, as well as machine learning classifiers. Furthermore, the system substitutes conventional, complex modelling techniques with a robust, artificial intelligence approach. The findings presented are of interest to researchers, fish farmers, and aquaculture technologist wanting to gain insights into the productivity of fish and fish behaviour.

Autorentext

Dr. Mohd Hafiz Arzmi graduated with a Bachelor of Science (Microbiology) with honours from the University of Malaya, Malaysia. He obtained a Master's in Dental Science (MDSc.) from the Faculty of Dentistry, University of Malaya. He then received his PhD in Oral Microbiology and Immunology from Melbourne Dental School, the University of Melbourne, Australia. He is currently an Associate Professor at the Department of Fundamental Dental and Medical Sciences, Kulliyyah of Dentistry, International Islamic University Malaysia (IIUM). He is the Head of Cluster of Cancer Research Initiative IIUM (COCRII) and the coordinator for Oral Microbiology and Immunology, Kulliyyah of Dentistry, IIUM. Dr. Hafiz is a professional technologist (PTech), registered with the Malaysia Board of Technologists (MBOT), an executive member of the International Association of Dental Research (IADR), Malaysian Section and the executive member of the Malaysian Society for Oral Microbiologists and Oral Immunologists (MySOMOI). His research interests are oral cancer, polymicrobial interactions, probiotics, and biofilms. Dr Anwar P. P. Abdul Majeed graduated with a first-class honours B.Eng. in Mechanical Engineering from Universiti Teknologi MARA (UiTM), Malaysia. He obtained an MSc. in Nuclear Engineering from Imperial College London, United Kingdom. He then received his PhD in Rehabilitation Robotics from the Universiti Malaysia Pahang (UMP). He is currently serving as an Associate Professor at the School of Robotics, XJTLU. Prior to joining XJTLU, he was a Senior Lecturer (Assistant Professor) and the Head of Programme (Bachelor of Manufacturing Engineering Technology (Industrial Automation)) at the Faculty of Manufacturing and Mechatronics Engineering Technology, UMP. He is also currently serving as an adjunct lecturer at UCSI University, Malaysia. Dr Anwar is also a Visiting Research Fellow at EUREKA Robotics Centre, Cardiff Metropolitan University, UK. Dr Anwar is a CharteredEngineer, registered with the Institution of Mechanical Engineers (IMechE), UK, a Member of the Institution of Engineering and Technology (IET), UK, as well as a Senior Member of the Institute of Electrical and Electronics Engineers (IEEE). He is an active research member at the Innovative Manufacturing, Mechatronics and Sports Laboratory (iMAMS), UMP. His research interest includes rehabilitation robotics, computational mechanics, applied mechanics, sports engineering, renewable and nuclear energy, sports performance analysis, machine vision as well as machine learning. He has authored over 60 papers in different journals, conference proceedings as well as books. He serves as a reviewer in a number of prolific journals, such as IEEE Access, Frontiers in Bioengineering and Biotechnology, SN Applied Sciences, PeerJ Computer Science, and Applied Computing and Informatics, amongst others. He has also served as a Guest Editor for SN Applied Sciences, MDPI, Frontiers, as well as an Editor for several Springer book series. He is currently serving as an Academic Editor for PLOS ONE, a Review Editor for Frontiers in Robotics and AI, an Associate Editor for Frontiers in Rehabilitation Sciences and a section editor for Mekatronika (UMP Press). Dr Anwar is also a member of the Young Scientists Network of the Academy of Sciences Malaysia (YSN - ASM). With regards to learned/civil society activities, he is an active member of the IET Malaysia Local Network as well as acting as a Liaison Officer for the Imperial College Alumni Association Malaysia. Dr. Rabiu Muazu Musa holds a PhD degree in Sports Science from Universiti Sultan Zainal Abidin (UniSZA), Malaysia. He obtained his MSc in Sports Science from UniSZA and his BSc in Physical and Health Education at Bayero University Kano, Nigeria. His research activity focused on the development of multivariate and machine learning models for athletic performance. His research interests include sports performance analysis, healthpromotion

Inhalt
1 Introduction.- 2 Monitoring and feeding integration of demand feeder systems.- 3 Image processing features extraction on fish behaviour.- 4 Time-series identification of fish feeding behaviour.