Course code InfT3051

Credit points 3

Digital Solutions in Agriculture

Total Hours in Course81

Number of hours for lectures16

Number of hours for seminars and practical classes16

Independent study hours49

Date of course confirmation15.03.2023

Responsible UnitInstitute of Computer Systems and Data Science

Course developers

author Datoru sistēmu un datu zinātnes institūts

Vitālijs Komašilovs

Dr. sc. ing.

author Datoru sistēmu un datu zinātnes institūts

Laima Bērziņa

Dr. sc.ing.

author Datoru sistēmu un datu zinātnes institūts

Aleksejs Zacepins

Dr. sc. ing.

author Datoru sistēmu un datu zinātnes institūts

Jurijs Hoļms

Ph.D.

author prof.

Irina Arhipova

Dr. sc. ing.

author prof.

Gatis Vītols

Dr. sc. ing.

Course abstract

The aim of the course is to view computational models, methods and tools to support various disciplines in decision support and development of more effective policies for sustainable development.
In this course students will identify common problems and computational solutions that can provide support for solving agriculture digitalization challenges and support precision agriculture. Course introduces solutions that include analysis of interdisciplinary systems design principles, data visualisation, topics on human-computer interaction as well as importance of algorithm design and modelling in processes of digitalization.

Learning outcomes and their assessment

Knowledge about importance of digitalization, system accessibility, state of art approaches, algorithmization and modelling methods when developing digitalization solutions. Knowledge about computational methods and tools for application in decision support processes. As well as knowledge about assessment methods of the ecosystem services and methodology for determining the monetary value of ecosystem services. (Completed practical assignments).
Skills: Ability to analyse interdisciplinary field and find solutions using information technologies. Ability to define, describe and apply appropriate approaches for solving certain digitalization tasks. Can individually calculate and interpret acquired results as well as compile, visualize and present data from various fields, in this case data acquired in precision agriculture processes and spatial data. (Completed practical assignments).
Competences Individually can retrieve required data from certain domain, perform analysis and choose appropriate information technology solution based on proper data interpretation. (Defended practical assignments, discussions during lectures).

Course Content(Calendar)

1. Digitization, digital solutions and sustainability, introductory lecture (lectures – 1h).
Module: Availability and usability of solutions for digital solutions (lectures - 3h, practical assignments - 3h)
2. The definition of sustainability and the role of digitization. Interdisciplinarity of digitization and solved issues. Algorithmization and modeling approaches for the development of digital solutions (1h lectures, 1h practical assignments).
3. Human-computer interaction methods as a basis for digital solutions. Development of human-computer interaction strategies for systems of various levels (1h lectures, 1h practical assignments).
4. Availability of information technology and systems. Access to groups of people and technology. Accessibility guidelines for different groups of people. Development of information systems in a cross-cultural context. Globalization and localization strategies. Methods for developing cross-cultural systems (1h lectures, 1h practical assignments).

Module: Ecosystem services and spatial data (lectures - 4h, practical assignments - 4h)
5. Ecosystem concept and services. Quantifying and Valuing Ecosystem Services (2 lectures, 2h practical assignments).
6. Latvian open data portal (1h lectures, 1h practical assignments)
7. Introduction to Geospatial Information Infrastructure (1h lectures, 1h practical assignments)

Module: Spatial data visualization and analysis. (lectures - 4h, practical assignments - 4h)
8. Importance of preparation and use of digital maps in agriculture (1h lectures, 1h practical assignments).
9. GIS solutions for map preparation and spatial information analysis (2h lectures, 2h practical assignments
10. Interactive presentation of spatial information (1h lectures, 1h practical assignments).

Module: Sensors and ICT in agriculture. (lectures – 4h, practical assignments – 4h)
11. Agriculture 4.0. Components of precision agriculture. Trends in the development of precision technologies. Possibilities of robotization in agriculture. (1h lectures, 1h practical assignments).
12. Precision agriculture and forestry systems. Precision farming, animal husbandry, beekeeping solutions (1h lectures, 1h practical assignments).
13. Computer vision and artificial intelligence solutions (2h lectures, 2h practical assignments)

Requirements for awarding credit points

To receive credit point’s students require to successfully, develop and defend practical assignments.
For each module, based on the evaluations of the practical work, a rating is received, maximum 2-4 points. The maximum score for all modules is 10 points.
Delayed assignments must be submitted and completed according to procedure described in LBTU Study regulations.

Description of the organization and tasks of students’ independent work

The organization of independent work during the semester is independently studying literature, using academic staff member consultations.

Criteria for Evaluating Learning Outcomes

The passing grade depends on the cumulative grade of the semester: Module 1 (2 points), Module 2 (4 points), Module 3 (2 points), Module 4 (2 points). 10 points make up 10 points of the test mark.

Compulsory reading

1.LIFE Ekosistēmu pakalpojumi. Ekosistēmu pakalpojumu novērtēšanas metodes [tiešsaiste]. [Skatīts 23.02.2024.]. Pieejams: https://ekosistemas.daba.gov.lv/public/lat/ekosistemu_pakalpojumi11/ekosistemu_pakalpojumu_novertesanas_metodes/
2.Krug S. Don't make me think, revisited: a common sense approach to Web usability. Berkeley, California: New Riders, 2014. , 200 p.
3. Gay G. Professional Web Accessibility Auditing Made Easy. Essential Skills for Web Developers, Content Creators, and Designers. Digital Education Strategies, the Chang School [tiešsaiste]. Ryerson University, 2018. , 233 p. [Skatīts 30.01.2023.]. Pieejams: https://openlibrary-repo.ecampusontario.ca/jspui/bitstream/123456789/563/5/Professional-Web-Accessibility-Auditing-Made-Easy-1574869307%20%281%29.pdf
4. Thiele L.P. Sustainability. Key Concepts. Polity Press, 2015. 348 p. 65 Bridge Street, Cambridge. CB2 1UR, UK.-234 p.
5. Campbell J., Shin M. Essentials of Geographic Information Systems [tiešsaiste]. Saylor Foundation, 2011. 259 p. [Skatīts 30.01.2023.]. Pieejams: https://digitalcommons.liberty.edu/cgi/viewcontent.cgi?article=1001&context=textbooks
6. TEEB , The Economics of Ecosystems and Biodiversity Ecological and Economic Foundations. TEEB Valuation Database Manual 2010 [tiešsaiste]. Edited by Pushpam Kumar. Earthscan: London and Washington. [Skatīts 30.01.2023.]. Pieejams: https://teebweb.org/publications/teeb-for/research-and-academia/
7. McVittie A., Hussain S. The Economics of Ecosystems and Biodiversity. TEEB Valuation Database Manual 2013 [tiešsaiste]. The Economics of Ecosystems and Biodiversity (TEEB): Geneva, 2013. [Skatīts 30.01.2023.]. Pieejams: http://www.teebweb.org/publications/other/teeb-valuation-database

Further reading

1. Precision agriculture for sustainability and environmental protection. M. Oliver, T. Bishop, B. Marchant eds. New York, Routledge, 2013. 304 p.
2. Langdon P., Lazar J., Heylighen A, Dong H. Inclusive Designing: Joining Usability, Accessibility, and Inclusion [tiešsaiste]. London: Springer, 2014. , 275 p. [Skatīts 23.02.2023.]. Pieejams: https://link-springer-com.ezproxy.llu.lv/content/pdf/10.1007/978-3-319-05095-9.pdf
3. Esri: GIS Mapping Software, Location Intelligence & Spatial Analysis [tiešsaiste] [skatīts 30.01.2023.]. Pieejams: https://www.esri.com/en-us/home

Notes

For students of the LF professional bachelor's study program "Agriculture". The study course can also be studied in English.