B.Tech. Agricultural Engineering · Semester 1

Agricultural Informatics and Artificial Intelligence

VAC-II Value-Added Course

Syllabus lecture plan

1. 01Module 1: Introduction to Computers and Basic Applications
2. 02Anatomy of Computers: Hardware, software, input/output devices
3. 03Memory Concepts and Units of Memory
4. 04Operating Systems: Definition, types, functions, and applications
5. 05MS Office Applications (MS Word, Excel, PowerPoint): Document creation, editing, formatting, graphing, and data presentation
6. 06Database Management Systems (DBMS): Introduction, types, and applications in agriculture
7. 07Introduction to the Internet and WWW: Concepts, components, and uses in agriculture
8. 08Computer Programming Basics: Introduction to Visual Basic, Java
9. 10ICT Applications in Agriculture: Role of IT in farming and rural development
10. 11Computer Models in Agriculture: Statistical models, weather analysis, and crop simulation models
11. 12Computer-Controlled Devices: Automated systems for Agri-input management
12. 13IT Applications for Crop Water and Nutrient Requirements
13. 14Smartphone Applications in Agriculture: Market price tracking, farm advice, postharvest management
14. 15Geospatial Technology in Agriculture: Concepts, techniques, and applications
15. 16Decision Support Systems (DSS): Concepts, components, and applications
16. 17Agriculture Expert Systems: Soil Information Systems for farm decision support
17. 18Preparation of Crop Calendars Using IT Tools
18. 19Introduction to Artificial Intelligence: Definition, background, and applications
19. 20Turing Test and Control Strategies
20. 21Search Strategies in AI: Breadth-first search, depth-first search
21. 22Heuristic Search Techniques: Best-first search, A* algorithm
22. 23Big Data and IoT in Agriculture: Use cases and benefits
23. 24AI-Based Autonomous Crop and Livestock Management
24. 25AI in Crop Health Monitoring and Intelligent Pesticide Application
25. 26AI in Precision Agriculture: Yield mapping and predictive analysis
26. 27Automatic Weeding and Harvesting Systems Using AI
27. 28AI in Sorting and Food Processing Applications
28. 30Digital India and Initiatives for Agricultural Digitalization
29. 31India Digital Ecosystem of Agriculture (IDEA) and Future
30. 32Case Studies and Industry Trends in Agricultural Informatics & AI

Part of the B.Tech. Agricultural Engineering curriculum (ICAR recommendations). Upload or find notes, previous-year papers and quick-revision reels for each lecture on theciae.