Introduction of Intelligent Agriculture
Objective
The rapid development of artificial intelligence and big data technology have allowed the Internet of Things, sensors, and intelligent machines to operate and collect a large amount of data in fields. Agriculture has entered the era of intelligent agriculture. Revolution has swept the agriculture industry in the aspects of production, protection, and consumption. This introductory course offers a comprehensive and interdisciplinary perspective on intelligent agriculture. Students are expected to learn about the sensing and monitoring of agricultural resources, the growth of animals and plants, and food processing; data concerning agricultural conditions such as climate, animal welfare, insect pests, weed control; the subtle remote control of field production, such as precise fertilization and pesticide spraying through robots and intelligent machines; the remote control of agricultural product transportation, such as controlling the environmental conditions during transportation to trace agricultural products and improve their quality; and thus how the agriculture industry is more closely linked to the health industry, changing the consumption patterns and the agricultural business models. The course introduces students to the core knowledge of intelligent agriculture by integrating professional resources from bio-industrial departments.
Syllabus
Week 1 Introduction to the future trends of intelligent agriculture
Week 2 Intelligent technology 1: machine learning, big data analysis, and data visualization
Week 3 Intelligent technology 2: machine vision and image recognition
Week 4 Intelligent technology 3: Space telemetry and meteorological big data
Week 5 Intelligent technology 4: intelligent agricultural machinery and agricultural robots
Week 6 Intelligent technology 5: Internet of Things and wireless network
Week 7 Intelligent technology 6: blockchain
Week 8 Intelligent technology 7: food safety and cold chain
Week 9 Midterms
Week 10 Intelligent agriculture application 1: livestock and poultry raising and intelligent barns
Week 11 Intelligent agriculture application 2: Establishment and application of crop growth model
Week 12 Intelligent agriculture application 3: precision farming
Week 13 Intelligent agriculture application 4: unmanned aerial vehicles (UAV) and fertilizer management
Week 14 Intelligent agriculture application 5: pest management
Week 15 Precision marketing
Week 16 New agriculture retail
Week 17 Social responsibility in intelligent agriculture
Week 18 Finals
Evaluation: Midterms 50%, Finals 50%
References
1. Digitising the Industry, Peter Friess, River Publishers series in communications,2016.
2. Intelligent Agrifood Chains and Networks, Edited by Michael Bourlakis, BlackwellPublishing Ltd., 2011.
3. Lecture Notes.