CEI338 Smart Farming Syllabus:
CEI338 Smart Farming Syllabus – Anna University Regulation 2021
COURSE OBJECTIVES:
1. To know about the basics of sensing and control algorithm in farming.
2. To understand the efficiency of farming through technology.
3. To explore image processing and Machine learning for agriculture.
4. To introduce types of sensors and software to implement in field.
UNIT I INTRODUCTION
History of Precision farming- Sensing Technology- Control Algorithm- Yield Monitoring- Soil Property Sensing- Acquisition through Remote Sensing- Crop Information- Farmland DataSpatial Sensing- Temporal Sensing- Feedback Control.
UNIT II MACHINE LEARNING IN AGRICULTURE
Machine Learning in Agriculture- Deep Learning in Agriculture- Yield prediction- Weed DetectionIrrigation Management- Discrimination between Weed and Crop- Forecasting stages.
UNIT III IoT IN AGRICULTURE
Need of IoT- IoT in Agriculture- Case study: Protection of Agricultural land from ElephantsIrrigation and Water Quality Management- Monitoring- Farm- Soil- Aquaponics- Agricultural
Machinery- Disease and Pest Control- Challenges and Issues.
UNIT IV DRONES IN AGRICULTURE
Drones in Agriculture- Agricultural Drones- Types of Drones and Classifications – Definitions and Terminologies- Study of Natural Resources and Vegetation- Mapping and Monitoring.
UNIT V AGRICULTURE 5.0
Introduction to Agriculture 4.0- Remote Sensing- Application of Nanotechnology in AgricultureRole of Big data- Hurdles faced by Farmers in Adopting- Current Policy Trends and Regulation.
TOTAL: 45 PERIODS
SKILL DEVELOPMENT ACTIVITIES (Group Seminar/Mini Project/Assignment/Content Preparation / Quiz/ Surprise Test / Solving GATE questions/ etc)
1 Taking Local area to implement simple closed loop system for irrigation and water management.
2 Using Machine Learning to forecast weather and predicting yield for particular field with previous data.
3 Mapping and Monitoring of particular area.
4 Drafting a policy and protocol to adopt farmers to new technologies.
COURSE OUTCOMES:
CO1 Relate to a farming with industrial problem and solving it (L2).
CO2 Explain the process in growing a particular crop varieties and challenges associated with it. (L5)
CO3 Apply the knowledge to select suitable sensors and software for particular test case (L3).
CO4 Analyze anomaly and weather change beforehand (L4).
CO5 Build an exclusive irrigation and harvest plan for particular zone (L3).
TEXT BOOKS:
1. Latief Ahmad, Firasath Nabi, “Agriculture 5.0 – Artificial Intelligence, IoT and Machine earning”, CRC Press, 2021.
2. Qin Zhang, “Precision Agriculture Technology for Crop Farming”, CRC Press, 2016.
REFERENCES
1. Govind Singh Patel, “Smart Agriculture”, CRC Press, 2021.
2. Ajith Abraham, Sujata Dash, Joel J.P.C.Rodrigues, “AI Edge and IoT based smart agriculture”, 2021, Elsevier
3. Amitava Choudhury, Arindam Biswas, T.P.Singh, Santanu Kumar Ghosh, “Smart Agriculture Automation using Advanced Technologies”, 2021, Springer