International Conference on Industry 4.0, Artificial Intelligence and Communications Technology (IAICT 2021)
Artificial Intelligence algorithms for the design of smart machines
Industry 4.0 is known as the rise of new digital industrial technology. Real-time data monitoring, tracking the status and positions of products, the optimization of advanced self-driving systems are the main challenges of Industry 4.0. In order to do these tasks, a huge amount of data has to be processed by algorithms with the capability of solving industrial engineering optimization problems. On the other hand, solving optimization problems by using exhaustive search techniques is a hard task. In most cases, such problems are classified as NP-hard and have the inconvenience of huge computational costs. Therefore, the use of intelligent algorithms reduces the computational complexity and leads to an optimal solution to the problem. However, the No Free Lunch (NFL) theorem states that there is no algorithm able to solve any problem. Thus, several nature-inspired algorithms powered by neuro-fuzzy techniques have been designed. In this speech, I will illustrate the combination between evolutionary algorithms and knowledge-based systems for designing optimal smart machines.
Danilo Pelusi received the Ph.D. degree in Computational Astrophysics from the University of Teramo, Italy. He is an Associate Professor at the Department of Communication Sciences, University of Teramo. Editor of books in Springer and Elsevier, he is/was an Associate Editor of IEEE Transactions on Emerging Topics in Computational Intelligence, IEEE Access and International Journal of Machine Learning and Cybernetics. Guest editor for Elsevier, Springer and Inderscience journals and keynote speaker in several conference, he belongs to the editorial board member of many journals. Reviewer of reputed journals such as IEEE Transactions on Fuzzy Systems and IEEE Transactions on Neural Networks and Machine Leaning, his research interests include Fuzzy Logic, Neural Networks, Information Theory, Machine Learning and Evolutionary Algorithms.
Current Research on Cyber-Physical System and Artificial Intelligence for Ocean Observation and Fisheries Applications
Ocean is three-dimensional medium, extend vastly to cover two-third of our earth surface and its depth average about 3.5 kilometer. Therefore, it is not surprising that the ocean plays a major role in shaping and influencing world climate and affecting people life, directly or indirectly. To observe and predict dynamics of the ocean we need observation system in place, namely from cyber-physical system that are capable of sensing the condition of the ocean then transmit ocean data to the receiver center for further processing and analysis. Once the data is available it can then feed into the artificial intelligence algorithm to seek for pattern and trend, and make prediction. One of the major usages of the ocean resources and services is fisheries. Fisheries provides healthy source of protein for the people and also provide livelihood. Fisheries industry also relies on the best available technology to make it more profitable and efficient in business. In the case of mariculture, for example, there is strong need to develop precision mariculture, where the amount and time of feeding is known to the exact; and for fishing activities, to reduce the uncertainty and longer transit time to search for the school of fish needs a smart fishing system. Hence, in fisheries also there is ample of opportunity for cyber-physical system and artificial intelligence application. In this talk, the ongoing research on both the cyber-physical system development and the use of artificial intelligence in the field of ocean observation and fisheries application will be presented.
Prof. Dr. Ir. Indra Jaya, M.Sc., was born in Palopo, April 10, 1961. He studied elementary, middle and high school in Makassar. During high school, he participated in the student exchange program (AFS Program, 1979-80) at Taft High School, Lincoln City, Oregon, United States. Entered IPB in 1980 and graduated with a degree in fisheries from IPB in 1984. Obtained a Doctorate (PhD) degree in 1996 with a dissertation on underwater sound propagation (Sea Acoustics) from the Graduate School of Marine Studies – University of Delaware, USA.
Since completing his postgraduate education, he has pursued the field of Marine Acoustics and Instrumentation. The courses taught include: sonar systems, marine instrumentation, acoustic oceanography, numerical analysis. Scientific works that have been produced include, among others, sound propagation in water, detection of fish flocks, swimming speed of fish, migration patterns of deep sea scattering layers, classification of water bottom substrates, and measurement of marine physical parameters using a telemetry system. In addition, from the results of research product development, the author as a co-inventor, has applied for 6 (six) patents, namely: (1) fry counter (high speed and accuracy fish seed counter), (2) fish freshness measuring device, ( 3) automatic fish/shrimp feeder, (4) koi fish sex discriminatory instrument, (5) live fish sorting and counting tool, and (6) freshwater fish sampling device.
Other activities and experiences, among others, as Expert Staff of Commission IV DPR-RI in the field of Maritime Affairs and Fisheries 2006-2008. Member of Assessor of BAN-PT 2004 until now. Professional membership: IEEE Oceanic Engineering, and Instrumentation and Measurement, Indonesian Oceanographic Bachelors Association (ISOI), and Indonesian Fisheries Graduate Association (ISPIKANI). Currently the author serves as the Dean of the Faculty of Fisheries and Marine Sciences, IPB, for the period 2007-2011.
Expertise: Acoustics & Marine Instrumentation
- Acoustic Approach to Assessment of Fish Stocks and Underwater Habitats
- Fishery & Marine Instrumentation Engineering
- Marine Bio-Acoustics
- Numerical Analysis for Fisheries & Marine
- Signal Processing and Artificial Intelligence