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Glossary
Semester (Sem)
1First Semester
2Second Semester
AAnnual course
Educational activities
CSimilar or integrative activities
BIdentifying activities
Language
Course completely offered in italian
Course completely offered in english
--Not available
Innovative teaching
The credits shown next to this symbol indicate the part of the course CFUs provided with Innovative teaching.
These CFUs include:
  • Subject taught jointly with companies or organizations
  • Blended Learning & Flipped Classroom
  • Massive Open Online Courses (MOOC)
  • Soft Skills
Course Details
Context
Academic Year 2022/2023
School School of Industrial and Information Engineering
Name (Master of Science degree)(ord. 270) - BV (479) Management Engineering
Track IND - INDUSTRIAL MANAGEMENT
Programme Year 2

Course Details
ID Code 057498
Course Title DATA ANALYTICS FOR SMART AGRICULTURE
Course Type Integrated Course
Credits (CFU / ECTS) 5.0
Semester First Semester
Course Description The course goal is to present a practical overview of data gathering, managing, and exploitation in Climate-Smart Agriculture (CSA). The concept of Climate-Smart Agriculture has been defined by the Food and Agriculture Organization of the United Nations as "a strategy to address the challenges of climate change and food security by sustainably increasing productivity, bolstering resilience, reducing GHG emissions, and enhancing the achievement of national security and development goals" [1]. CSA is the implementation of the ""Zero hunger"" Sustainable Development Goals of the United Nations. The advent of digital technologies in agriculture has shaped the CSA concept giving birth to new terms like Smart Agriculture, Digital Agriculture, and Agriculture 4.0. Digital technologies like Artificial Intelligence (AI), Robotics, and the Internet of Things are expected to be game-changers in achieving the CSA objectives. Digital technologies allow for detailed real-time analysis of data from smart sensors, ground vehicles, aerial drones, or satellites. This big amount of data is analyzed by machine learning techniques to produce information upon which farmers can make decisions instead of entirely relying on their personal beliefs. These technologies allow increasing productivity while decreasing costs and being more environmentally friendly. In the course, we will approach the whole value chain of data in Agriculture 4.0 starting from the means to acquire information via IoT sensors, aerial imaging, remote sensing, and auxiliary sources such as agrometeo and field surveys, then we will discuss the most common techniques for data processing and the tools to perform such processing and finally we will present how data can be turned into an actionable source of information discussing the way it can impact the agri-food value chain. This course is intended as a Master Level class on data analytics; basic notions of mathematics, statistics, databases, and (object-oriented) programming are assumed as pre-requirement for a successful attendance of the course. [1] A. Chandra, K. E. McNamara, and P. Dargusch, "Climate-smart agriculture: Perspectives and framings," Climate Policy, vol. 18, no. 4, pp. 526-541, 2018.
Scientific-Disciplinary Sector (SSD)
Educational activities SSD Code SSD Description CFU
C
ING-INF/05
INFORMATION PROCESSING SYSTEMS
3.0
B,C
ING-IND/17
INDUSTRIAL MECHANICAL SYSTEMS ENGINEERING
2.0

Schedule, add and removeAlphabetical groupCodeModule DescriptionLecturer(s)CFUSem.LanguageTeaching Assignment Details
From (included)To (excluded)
---AZZZZ057497DATA ANALYTICS FOR SMART AGRICULTURE - MODULE 2Matteucci Matteo3.01
057496DATA ANALYTICS FOR SMART AGRICULTURE - MODULE 1Renga Filippo Maria2.01---
manifesti v. 3.7.7 / 3.7.7
Area Servizi ICT
16/02/2025