Intelligent Agricultural Systems and Technologies

Objectives

• Understand the role of intelligent systems in modern agriculture.
• Learn about key technologies used in intelligent agricultural systems.
• Explore the integration of data-driven decision-making in agriculture.
• Gain insights into the future trends of agricultural technologies and their impact.

---

Introduction to Intelligent Agricultural Systems

• Overview of intelligent systems in agriculture
• Key components: Sensors, IoT, AI, and robotics
• Benefits of automation and data-driven agriculture
• Challenges in adopting intelligent systems
• Case studies of intelligent agricultural systems in practice

---

Technologies in Precision Agriculture

• GPS and GIS technologies for crop management
• Drones and remote sensing in agriculture
• Automated machinery and robotics
• Data collection and analysis techniques
• Integration of machine learning and AI in farming practices

---

Data-Driven Decision Making in Agriculture

• The role of big data in agriculture
• Collecting and analyzing agricultural data
• Decision support systems for farm management
• Predictive analytics and forecasting for crop yield
• Implementing real-time monitoring systems for farm management

---

Future Trends and Innovations in Agricultural Technologies

• The rise of smart farms and digital agriculture
• AI and robotics for autonomous farming
• Blockchain technology for food traceability
• Emerging technologies: Biotechnology, nanotechnology, and more
• Sustainable farming practices and the role of intelligent systems

DATE:

1ST BATCH:  16th–19th Mar, 2026 

2ND BATCH: 7th–10th Jul, 2026 

3RD BATCH: 3rd–6th Nov, 2026