Course code InfT6026

Credit points 3

Intelligent Technologies and Systems

Total Hours in Course81

Number of hours for lectures12

Number of hours for seminars and practical classes12

Independent study hours57

Date of course confirmation16.03.2011

Responsible UnitInstitute of Engineering and Energetics

Course developer

author Inženiertehnikas un enerģētikas institūts

Genādijs Moskvins

Dr. habil. sc. ing.

Course abstract

The aim of the course is to expand and to deepen knowledge of general principles in area of designing, analysis, construction and simulation of intelligent technologies and systems (ITS). Give new knowledge about actual problems of (ITS), practical solutions and new possibilities for development of (ITS) in agriculture, about the basic elements of (ITS), the neural networks, the fuzzy logic, about SCADA (Supervisory Control and Data Acquisition) and HMI (Human Machine Interface) data visualization and monitoring systems. (ITS) design principles, basic concepts, definitions, development, paradigm. (ITS) basic elements and specifics of agriculture. Intelligence, technology, system. Kinds of intellect. Systemic thinking. (ITS) Theory of Systems. (ITS) structural-functional schemes. (ITS) methodology. (ITS) Database, information, knowledge base. Expert systems and artificial intelligence. Artificial Neural Networks (ANN). Training algorithms. Models of Cognitive Knowledge Acquisition. Intelligent measuring devices and sensors. Chaos and antihaoss. Fuzzy logic. Genetic Algorithms. Monitoring and Visualization (HMI / SCADA/ EDrawMax. General principles of knowledge reflection. Semantic Networks. Conceptual graphs. Nanotechnologies. Nano robots. Intellectual environment. Imitation of human organs. Artificial tongue. Artificial nose. Image Recognition. Fractals. E-code and mobile application.

Learning outcomes and their assessment

1. Knowledge - about the general principles of (ITS), elaboration, action, control and application to solve the theoretical and practical tasks in field of (ITS) engineering and to improve their operation quality.
2. Skills - to choose (ITS) complex, elements and components, to analyse their work process, algorithms, operations in static and dynamic modes, to compose optimal (ITS), structure, functional and block diagrams, to evaluate quality of (ITS) operation.

3. Competence - to select an appropriate principles for (ITS) elements, components and devices, methods for elaboration, action, control and application , methods for identifying the parameters , principles of control to interpret the operation data and to perfect their quality.

Course Content(Calendar)

1. (ITS) Content, classification, tasks, basic concepts, definitions. (Lecture – 1h)
2. Intellectualization of production and technological processes. Glossary. (ITS) design principles, paradigm. (Lecture – 1h)
3. (ITS) methodology. Natural and technical intelligence. Principles of intelligence. Computing Intelligence. Systemic thinking. (Lecture - 1h)
4. Intelligent measuring systems. Electronic "nose" and electronic "tongue”. “Internet of things” (IoT); (Lecture - 1h, practical lesson - 2h); Control test №1.
5. E-Code Intelligent Technology in Production and Circulation. Mobile application. (Lecture - 1h, practical lesson - 2h)
6. (ITS) training and self-training. Artificial Neural Networks (ANN) and Training Algorithms. (Lecture – 1h)
7. Modelling of metric fractal images. Cyber-physical systems (CPS) (Lecture – 1h)
8. Chaos and antihaoss. Harmony, organization and self-organization. (Lecture – 1h)
9. (ITS) management system modelling and optimization. Fuzzy logic. Genetic algorithms. Cyber-physical systems (Lecture - 1h, practical lesson - 2h)
10. Database, information and knowledge. Interpretation of knowledge. Models of Cognitive Knowledge Acquisition. Theory of Systems (Lecture – 1h)
11. Fundamentals of Expert System (ES). (Lecture – 1h)
12. Introduction to Artificial Intelligence (AI). (Lecture – 1h)
13. Nanotechnologies and their applications (NT). (Lecture – 1h)
14. Intelligent devices for control of quality and safety. E-code in the chain of agricultural production (Lecture – 1h)
15. Modelling, monitoring and visualization systems. HMI / SCADA/ Trace Mode 6./ EDrawMax (Lecture - 1h, practical lesson - 2h), Control test №2;

16. Examples of ITS applications in agriculture, directions and possibilities for development in the future. (Lecture – 1h).

Requirements for awarding credit points

The student admitted to the examination only if the practical work is worked out, control tests №1 and №2 as well as independent work positive is evaluated.

The student prepares a report or presentation in the volume of 15-20 pages about ITS scheme with using of control schemes of and justifying engineering solutions with calculations.

Description of the organization and tasks of students’ independent work

The student prepares a 15-20 pages e-report for oral presentation on a freely chosen theme in an area of ITS including control schemes and examples of engineering-technical modelling and calculations. Independent work can be performed using computer programs EDrawMax, SCADA, TRACE MODE 6 etc.

Criteria for Evaluating Learning Outcomes

Assessment consist of the following parts – practical and homework (4), homework presentation (2), defence (2). To get 9 – 10 assessment – student can choose additional exercises. Assessment of the study course exam consists of the sum of points obtained for each answer of the theoretical examination question:
- Full comprehensive, broad answer: 4 points
- Correct answer with minor flaws or errors: 3 points
- Answer that contains only basic concepts without explanation or contains significant errors: 2 point
- There are no answers, the answer is false, and the answer is very gross material errors: 0 point.

By getting 9 points, there is an opportunity to have a conversation, which results in a mark 10 - excellent. The correct answer may have minor shortcomings or minor errors. The answer can be correct, comprehensive, and broad, to each question, correct with minor flaws or errors, correct answer that contains only basic concepts without explanation, or contains material errors. If there is no answer, the answer is wrong, there are very gross significant errors in the answer, then the exam not passed.

Compulsory reading

1. Moskvins G. Intelektuālās sistēmas un tehnoloģijas. Mācību grāmata. ISBN 978-9984-784-62-5, Jelgava: LLU, 2008. 136 lpp.
2. Moskvins.G. Automatizācija. Mācību grāmata. ISBN 978-9984-784-81-6, Jelgava: LLU, 2008. 120 lpp.
3. S. Russell and P. Norvig. Artificial Intelligence: A Modern Approach 3rd Edition 2009. ISBN-10: 0136042597, ISBN-13: 978-0136042594, 1152 p.
4. Moskvins G. Mākslīgā intelekta aktualitātes. No: Zinātnes filozofija. Jelgava: LLU, 2011. lpp. 95-106.
5. Moskvins G. Haoss, antihaoss, fraktāļi. Ieskats nanotehnoloģiju attīstībā. No: Zinātnes filozofija. Jelgava: LLU, 2011. lpp. 107-131;

6. Ertel W., Black N.T. (2018). Introduction to Artificial Intelligence, Springer, 356 p.

Further reading

1. Luger G.F. (2009). Artificial Intelligence: Structures and Strategies for Complex Problem Solving, Pearson Education, 784 p.
2. Oded Goldreich. Computational Complexity: a Conceptual Perspective. Cambridge University Press, 2008. 606 p.
3. Suematsu, Y. Itroduction to Personal Computer Based Controllers. Tokyo: Ohmsha,Ltd., 2002. 256 p.
4. Hopgood A. A. (2011). Intelligent Systems for Engineers and Scientists, CRC Press, 451 p.

5. Siliņš E. Lielo patiesību meklējumi. Rīga: Jumava, ISBN 9789984051864, 2006. 512 lpp.

Periodicals and other sources

1. Artificial Intelligence. An International Journal. ELSEVIER, ISSN: 0004-3702. http://www.journals.elsevier.com/artificial-intelligence/

2. Information Technology, List of free Information Technology magazines (http://sourcecodesworld.tradepub.com/?pt=cat&page=Info)

Notes

The study course is included in the sub-program "Applied Energetics" of the Master's Degree Program in Agricultural Engineering, full-time and part-time studies.