Information Package / Course Catalogue
Smart Greenhouse and Plant Monitoring Systems
Course Code: DJTA112
Course Type: Required
Couse Group: Short Cycle (Associate's Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 2
Prt.: 1
Credit: 3
Lab: 0
ECTS: 4
Objectives of the Course

The aim is to provide knowledge and skills on the use of digital monitoring and automation systems in greenhouses.

Course Content

Greenhouse automation systems, climate control, sensors, yield monitoring and digital decision support systems are discussed.

Name of Lecturer(s)
Learning Outcomes
1.Defines the basic automation systems used in smart greenhouses.
2.Explains digital systems for temperature, humidity, light, and CO² control.
3.Uses and interprets sensors monitoring plant growth.
4.Develops strategies to increase energy efficiency in greenhouses.
5.Optimizes plant cultivation through digital monitoring data.
Recommended or Required Reading
1.Yıldız, M. (2018). Automation and Control Technologies in Greenhouses.
2.Shamshiri, R.R. et al. (2018). Research and Education in Greenhouse Engineering. Elsevier.
Weekly Detailed Course Contents
Week 1 - Theoretical
Importance of greenhouse cultivation and basic concepts
Week 1 - Practice
Investigation of greenhouse climate parameters
Week 2 - Theoretical
Environmental factors in greenhouse: temperature, humidity, light, CO²
Week 2 - Practice
Introduction to temperature and humidity sensors
Week 3 - Theoretical
Introduction to smart greenhouse systems and historical development
Week 3 - Practice
Sensor installation and data reading exercises
Week 4 - Theoretical
Relationship between plant growth and environmental conditions
Week 4 - Practice
Controlling automatic ventilation systems
Week 5 - Theoretical
Sensor technologies and data collection principles
Week 5 - Practice
Light sensor analysis for photosynthesis efficiency
Week 6 - Theoretical
Automatic control systems: ventilation, heating, irrigation
Week 6 - Practice
CO² sensor usage for respiration analysis
Week 7 - Theoretical
Monitoring plant health through imaging technologies
Week 7 - Practice
Leaf health scanning with imaging devices
Week 8 - Theoretical
Monitoring plant health through imaging technologies
Week 8 - Practice
Collecting plant growth data
Week 9 - Theoretical
Remote monitoring and real-time intervention
Week 9 - Practice
Testing real-time warning systems
Week 10 - Theoretical
AI-based data processing approaches
Week 10 - Practice
AI-supported stress analysis applications
Week 11 - Theoretical
Energy efficiency and sustainable greenhouse management
Week 11 - Practice
Measuring and evaluating energy consumption
Week 12 - Theoretical
Use of decision support systems in greenhouse applications
Week 12 - Practice
Simulation studies with decision support panels
Week 13 - Theoretical
Sample smart greenhouse projects and field applications
Week 13 - Practice
Analyzing and interpreting sample greenhouse data
Week 14 - Theoretical
General review and project presentations
Week 14 - Practice
Project presentations
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
Lecture - Practice140114
Land Work40312
Reading70428
Individual Work50315
Midterm Examination1022
Final Examination1022
TOTAL WORKLOAD (hours)101
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
PÇ-19
PÇ-20
OÇ-1
4
2
OÇ-2
3
2
OÇ-3
3
OÇ-4
OÇ-5
Adnan Menderes University - Information Package / Course Catalogue
2026