Information Package / Course Catalogue
Smart Farming Technologies
Course Code: DJTA024
Course Type: Area Elective
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 objective of this course is to provide students with theoretical knowledge and practical skills in smart agriculture technologies, precision agriculture applications, sensor technologies, geographic information systems, internet of things, artificial intelligence, and data analytics. Students are expected to recognize current technologies used in agricultural production processes, understand their integration, and develop strategies for sustainable agricultural practices.

Course Content

Introduction to smart agriculture technologies and basic concepts. Principles and applications of precision agriculture. Agricultural sensor technologies and data collection. Geographic information systems and global positioning systems. Internet of things applications and sensor networks. Data analytics and artificial intelligence. Agricultural robotics, automation, and autonomous systems. Unmanned aerial vehicles and remote sensing. Smart irrigation systems. Crop health monitoring and disease detection. Decision support systems and digital farm management.

Name of Lecturer(s)
Learning Outcomes
1.Comprehend the basic principles and components of smart agriculture technologies.
2.Know the applications of precision agriculture, sensor technologies, and geographic information systems in agricultural production.
3.Integrate internet of things, data analytics, and artificial intelligence applications into agricultural processes.
4.Know agricultural robotics, autonomous systems, and remote sensing technologies.
5.Develop smart solutions for sustainable agricultural practices.
Recommended or Required Reading
1.Precision Applied Agricultural Technology Vahit Kirişçi, M. Keskin, S.M. Say, S.G. Keskin ISBN: 975-591-066-2
2.Basic Concepts in Remote Atilla Sesören Mart Matbaacılık S.Ltd.Şti
Weekly Detailed Course Contents
Week 1 - Theoretical
Introduction to smart agriculture technologies and basic concepts
Week 2 - Theoretical
Precision agriculture: basic principles and application areas
Week 3 - Theoretical
Agricultural sensor technologies and data collection methods
Week 4 - Theoretical
Geographic information systems and global positioning systems
Week 5 - Theoretical
Remote sensing and unmanned aerial vehicle usage
Week 6 - Theoretical
Internet of things and agricultural sensor networks
Week 7 - Theoretical
Agricultural data analytics and big data management
Week 8 - Theoretical
Agricultural data visualization and reporting
Week 9 - Theoretical
Artificial intelligence and machine learning applications
Week 10 - Theoretical
Agricultural robotics, automation, and autonomous systems
Week 11 - Theoretical
Smart irrigation systems and water resource management
Week 12 - Theoretical
Crop health monitoring and disease detection
Week 13 - Theoretical
Decision support systems and digital farm management
Week 14 - Theoretical
Innovative solutions for sustainable agriculture and energy efficiency
Assessment Methods and Criteria
Type of AssessmentCountPercent
Assignment1%5
Quiz1%5
Midterm Examination1%30
Final Examination1%60
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory140228
Assignment1336
Individual Work2228
Quiz1213
Midterm Examination1011
Final Examination1011
TOTAL WORKLOAD (hours)47
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
OÇ-1
5
3
4
5
OÇ-2
4
4
3
2
5
5
OÇ-3
3
4
3
4
4
5
4
OÇ-4
2
3
4
4
5
OÇ-5
5
4
5
3
4
Adnan Menderes University - Information Package / Course Catalogue
2026