| Course Code | Course Title | Credits | Type |
|---|---|---|---|
| Agricultural Informatics and Artificial Intelligence (AI) | 3 | (2+1) |
Course Objectives (COs)
| CO No. | Description | Bloom’s Level |
|---|---|---|
| CO1 | Understand the fundamental concepts of computers, operating systems, internet technologies, and IT tools relevant to agriculture. |
(L2) |
| CO2 | Apply data processing tools such as MS-Office, databases, and basic programming concepts to solve agricultural information needs. |
(L3) |
| CO3 | Analyze the role of e-Agriculture, ICT tools, crop simulation models, geospatial technology, and decision-support systems in modern farming. |
(L4) |
| CO4 | Evaluate Artificial Intelligence (AI), IoT, and Big Data applications for smart and sustainable agricultural practices. |
(L5) |
Course Learning Outcomes (CLOs)
| CLO No. | Description | Bloom’s Level |
|---|---|---|
| CLO1 | Explain the basic concepts of computers, operating systems, memory, internet, and their relevance in agricultural informatics. |
(L1 – Remember/Understand) |
| CLO2 | Use MS-Office, databases, internet tools, and basic programming concepts to manage and analyze agricultural data. |
(L3 – Apply) |
| CLO3 | Examine ICT applications, e-Agriculture platforms, crop simulation models, geospatial tools, and DSS for farm-level decision-making. |
(L4 – Analyze) |
| CLO4 | Assess the role of AI, IoT, Big Data, and smart devices in precision agriculture, crop/livestock management, and food systems. |
(L5 – Evaluate) |
CO–PO Mapping Table
Scale: 3 = Strong, 2 = Moderate, 1 = Slight, “–” = No Contribution
| CO / PO | PO1 | PO2 | PO3 | PO4 | PO5 | PO6 | PO7 | PO8 | PO9 | PO10 | PO11 | PO12 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| CO1 | 3 | 3 | 2 | – | 2 | 1 | – | – | – | – | – | – |
| CO2 | 3 | 3 | 3 | 2 | 3 | – | – | 1 | 1 | – | – | – |
| CO3 | 2 | 3 | 3 | 3 | 3 | 2 | 2 | 2 | – | – | – | – |
| CO4 | 2 | 3 | 3 | 3 | 3 | 2 | 2 | 3 | 2 | – | – | – |
Bloom’s Taxonomy Levels Used
- L1 – Remember
- L2 – Understand
- L3 – Apply
- L4 – Analyze
- L5 – Evaluate
- L6 – Create
📘 COURSE SYLLABUS (THEORY)
🔷 MODULE 1: Fundamentals of Computers and Basic IT Tools
| Unit | Topic |
|---|---|
| 1.1 | Introduction to Computers – Definition and characteristics of computers – Applications of computers in agriculture |
| 1.2 | Anatomy of Computers – Hardware components – Input/output devices – Peripheral devices |
| 1.3 | Memory Concepts – Primary and secondary memory – Units: bit, byte, KB, MB, GB, TB |
| 1.4 | Operating Systems – Definition and functions – Types: Windows, Linux, Android |
| 1.5 | MS Office Applications – Creating, editing, formatting documents (MS Word) – Data presentation & scientific documentation (PowerPoint) – Spreadsheet analysis, graphs, formulas (Excel) |
🔷 MODULE 2: Database Management, Internet & Programming Basics
| Unit | Topic |
|---|---|
| 2.1 | Database Concepts – Database definition and types – Creating databases – DBMS in agriculture – Agricultural information systems |
| 2.2 | Internet and WWW – Concepts & components – Browsers, search engines – Web applications in agriculture |
| 2.3 | Basics of Computer Programming – Logic, algorithms, flowcharts – Standard input/output operations – Relevance in agricultural data analysis |
🔷 MODULE 3: ICTs, e-Agriculture, Crop Models, Geospatial & Decision Tools
| Unit | Topic |
|---|---|
| 3.1 | e-Agriculture – Concepts, design & development – ICT tools – Mobile advisory systems |
| 3.2 | Crop & Climate Models – Statistical, weather, crop models – Calibration, validation – Nutrient/irrigation computing tools |
| 3.3 | Automated and Smart Devices – Sensors & automation – Precision agriculture tools |
| 3.4 | Smartphone Applications – Farm advisory apps – Market & post-harvest apps |
| 3.5 | Geospatial Technologies – GIS, GPS, Remote sensing – Applications in agriculture |
| 3.6 | Decision Support & Expert Systems – Soil information systems – Crop calendar planning |
| 3.7 | Digital Agriculture Initiatives – Digital India, AgriTech missions – IDEA framework & policies |
🔷 MODULE 4: Artificial Intelligence, IoT & Smart Agriculture
| Unit | Topic |
|---|---|
| 4.1 | Introduction to AI – Definition, background, Turing test – BFS, DFS, Best-first, A* |
| 4.2 | IoT & Big Data in Agriculture – Sensors, IoT devices, Cloud platforms |
| 4.3 | AI Applications in Agriculture – Crop & livestock monitoring – Precision mapping & analytics – Automated weeding/harvesting |
| 4.4 | Smart Agriculture Concepts – Smart farming systems – Future technologies in digital agriculture |
| Practical Syllabus | |
| Unit | Practical Title & Description |
|---|---|
| P1 | Introduction to computer hardware components, input/output devices, and basic troubleshooting. |
| P2 | Hands-on working with the Windows/Linux operating system: File management, system settings, and OS utilities. |
| P3 | Working with MS-Word: Formatting, tables, charts, mail merge, and documentation. |
| P4 | Microsoft Excel for agricultural calculations: Data entry, formulas, sorting, filtering, and basic statistical analysis. |
| P5 | Spreadsheet-based demonstration of crop yield estimation, cost-benefit analysis, and farm record digitization. |
| P6 | Internet tools in Agriculture: Email creation, research databases, government portals, and e-Agriculture platforms. |
| P7 | Database management practical: Creating tables, forms, and queries using MS-Access or LibreOffice Base. |
| P8 | Introduction to programming using Python: Variables, operators, loops, input/output operations. |
| P9 | Simple Python script for agricultural applications: Rainfall trend analysis, pest-alert threshold demonstration. |
| P10 | Demonstration of crop simulation models, GIS, and geospatial tools used in precision agriculture. |
Theory Session Plan
| Session No. | Module | Topic | Sub-Topics Covered |
|---|---|---|---|
| Module 1: Fundamentals of Computers and Basic IT Tools (Sessions 1–6) | |||
| 1 | Module 1 | Introduction to Computers | Definition, Characteristics, Role in Agriculture |
| 2 | Module 1 | Anatomy of Computers | Hardware, Input/Output Devices, Peripheral Devices |
| 3 | Module 1 | Memory Concepts | Primary & Secondary Memory, Units (Bit, Byte, KB, MB, GB, TB) |
| 4 | Module 1 | Operating Systems | Definition, Functions, Windows/Linux/Android |
| 5 | Module 1 | MS Word | Document Creation, Editing, Formatting |
| 6 | Module 1 | MS Excel & PowerPoint | Graphs, Tables, Data Presentation, Statistical Analysis |
| Module 2: Database Management, Internet & Programming Basics (Sessions 7–12) | |||
| 7 | Module 2 | Database Concepts | Definition, Types, Creating Databases, Agri DBMS |
| 8 | Module 2 | Agricultural Information Systems | Types, Applications in Agriculture |
| 9 | Module 2 | Internet & WWW | Internet Concepts, Browsers, Web Applications in Agri |
| 10 | Module 2 | Search Engines & Web Services | Online Agriculture Tools |
| 11 | Module 2 | Basics of Programming | Logic, Variables, Input/Output |
| 12 | Module 2 | Algorithms & Flowcharts | Steps, Decision Making, Problem Solving |
| Module 3: ICTs, e-Agriculture, Crop Models, Geospatial & Decision Tools (Sessions 13–23) | |||
| 13 | Module 3 | e-Agriculture Concepts | ICT Tools, Mobile Advisory Systems |
| 14 | Module 3 | Computer Models in Agriculture | Statistical, Weather, Crop Simulation, Input/Output, Calibration, Validation |
| 15 | Module 3 | Automated & Smart Devices | Sensors, Automated Irrigation, Precision Tools |
| 16 | Module 3 | Smartphone Applications | Farm Advisory Apps, Market & Post-Harvest Tools |
| 17 | Module 3 | Geospatial Technologies | GIS, GPS, Remote Sensing, Agri Information Generation |
| 18 | Module 3 | Decision Support & Expert Systems | Soil Information Systems, Crop Calendar, Contingent Planning |
| 19 | Module 3 | Digital Agriculture Initiatives | Digital India, Agritech Missions, IDEA Framework |
| Module 4: Artificial Intelligence, IoT & Smart Agriculture (Sessions 24–30) | |||
| 24 | Module 4 | Introduction to AI | Definition, Background, Turing Test, Search Strategies (BFS, DFS, Best-first, A*) |
| 25 | Module 4 | IoT & Big Data in Agriculture | IoT Devices, Sensors, Cloud Platforms, Data Collection |
| 26 | Module 4 | AI Applications in Agriculture – Part 1 | Autonomous Crop Management, Livestock Health Monitoring |
| 27 | Module 4 | AI Applications in Agriculture – Part 2 | Precision Yield Mapping, Predictive Analytics, Automated Weeding & Harvesting |
| 28 | Module 4 | AI Applications in Agriculture – Part 3 | Sorting & Classification in Food Processing |
| 29 | Module 4 | Smart Agriculture Concepts – Part 1 | Smart Farming Systems, AI in Food Science |
| 30 | Module 4 | Smart Agriculture Concepts – Part 2 | Future Trends in AI-driven Digital Agriculture |
Practical Session Plan – Agricultural Informatics & Artificial Intelligence
| Practical No. | Title / Experiment | Activities / Tasks | Expected Outcome |
|---|---|---|---|
| P1 | Computer System Familiarization | Identify parts, boot process | Understand computer hardware |
| P2 | Hands-on with OS | File management, settings, utilities | Operate OS confidently |
| P3 | MS Word | Create agri reports, tables | Prepare documentation |
| P4 | MS Excel – Data Entry | Create spreadsheets | Handle agricultural data |
| P5 | MS Excel – Formulas | SUM, AVG, IF, VLOOKUP, charts | Analyze datasets |
| P6 | MS PowerPoint | Scientific slide preparation | Develop presentations |
| P7 | Internet Tools | Searching, downloading reports | Efficient information retrieval |
| P8 | Agriculture Web Platforms | mKisan, eNAM, AP agrisites | Use ICT platforms |
| P9 | DBMS – Creating Tables | Create simple DB for soil/crop | Construct basic databases |
| P10 | DBMS – Queries | SELECT commands, filters | Retrieve agricultural data |
| P11 | Algorithm Activity | Flowchart creation | Understand programming logic |
| P12 | ICT Tools | Use DSS, crop calendars | Apply ICT apps |
| P13 | Crop Simulation Tools | Try sample model outputs | Understand model functioning |
| P14 | Geospatial Tools | GPS/RS demo, mapping | Interpret spatial data |
| P15 | AI & IoT Demo | Sensor reading, simple ML demo | Understand smart farming tools |
📚 Suggested Readings
| S.No. | Title | Author(s) / Publisher |
|---|---|---|
| 1 | Concepts and Techniques of Programming in C | Dhabal Prasad Sethi & Manoranjan, Wiley India |
| 2 | Fundamentals of Computer | V. Rajaraman |
| 3 | Introduction to Information Technology | Pearson |
| 4 | Introduction to Database Management System | C. J. Date |
| 5 | Introductory Agri-Informatics | Mahapatra, Subrat K. et al., Jain Brothers Publication |