Information Package / Course Catalogue
Aı-Powered Smart Farming Technologies
Course Code: ORT135
Course Type: Required
Couse Group: Short Cycle (Associate's Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 2
Prt.: 0
Credit: 2
Lab: 0
ECTS: 2
Objectives of the Course

The aim is to inform students about how traditional farming methods are being transformed by the digitalization process; and to teach them about the impact of precision agriculture, IoT (Internet of Things), drone technologies, data analytics, and automation systems on agricultural productivity and sustainability.

Course Content

Precision farming techniques, GPS and GIS systems, sensor use in agriculture, variable rate application technologies (VRT), agricultural robots and autonomous vehicles, big data analysis, and applications of artificial intelligence in agriculture.

Name of Lecturer(s)
Learning Outcomes
1.Defines the basic components of smart farming technologies.
2.Gains theoretical knowledge about data collection tools used in precision agriculture applications.
3.Learns the concepts of smart farming, Agriculture 4.0, and precision farming, and theoretically distinguishes between these technologies and traditional farming methods.
4.Understands the logic behind the use of artificial intelligence in agricultural decision support systems.
5.Knows the working principles of automatic steering and autonomous vehicles.
Recommended or Required Reading
1.Thokchom, Rocky & Sonkar, Satyarath & dhawale, Shubham & Maurya, Durgesh & Kumar, Hemant. (2025). Artificial Intelligence in Agriculture.
Weekly Detailed Course Contents
Week 1 - Theoretical
Agriculture 4.0 and Introduction to Smart Farming: Basic Concepts
Week 2 - Theoretical
General knowledge and use of artificial intelligence
Week 3 - Theoretical
Precision Agriculture Technologies and Global Positioning Systems (GPS/GNSS)
Week 4 - Theoretical
Geographic Information Systems (GIS) and Agricultural Mapping (QUIZ)
Week 5 - Theoretical
Sensor Technologies in Agriculture: Soil, Plant and Climate Sensors
Week 6 - Theoretical
Remote Sensing: Satellite Imagery and Index Analysis (NDVI, etc.)
Week 7 - Theoretical
Applications of unmanned aerial vehicles (drones) in agriculture
Week 8 - Theoretical
Variable Rate Application Technologies (VRT): Fertilization and Pest Control (MIDTERM EXAM)
Week 9 - Theoretical
Internet of Things (IoT) and Wireless Sensor Networks in Agriculture
Week 10 - Theoretical
Smart Irrigation Systems and Automation
Week 11 - Theoretical
Autonomous Farming Vehicles (VERBAL EXAMINATION)
Week 12 - Theoretical
Big Data and Decision Support Systems in Agriculture
Week 13 - Theoretical
Smart Technologies in Animal Husbandry (Precision Animal Husbandry)
Week 14 - Theoretical
Economic and Environmental Impacts of Smart Agriculture: Future Projections
Assessment Methods and Criteria
Type of AssessmentCountPercent
Quiz1%10
Verbal Examination1%10
Midterm Examination1%20
Final Examination1%60
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory140228
Quiz1314
Midterm Examination1617
Final Examination110111
TOTAL WORKLOAD (hours)50
Contribution of Learning Outcomes to Programme Outcomes
PÇ-1
PÇ-2
PÇ-3
PÇ-4
PÇ-5
PÇ-6
PÇ-7
PÇ-8
PÇ-9
PÇ-10
PÇ-11
PÇ-12
PÇ-13
PÇ-14
PÇ-15
PÇ-16
PÇ-17
PÇ-18
OÇ-1
4
4
5
2
OÇ-2
4
4
5
2
OÇ-3
4
4
5
2
OÇ-4
4
4
5
2
OÇ-5
4
4
5
2
Adnan Menderes University - Information Package / Course Catalogue
2026