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Scheda Riassuntiva
Anno Accademico 2022/2023
Scuola Scuola di Ingegneria Industriale e dell'Informazione
Insegnamento 057498 - DATA ANALYTICS FOR SMART AGRICULTURE
Docente Matteucci Matteo , Renga Filippo Maria
Cfu 5.00 Tipo insegnamento Corso Integrato

Corso di Studi Codice Piano di Studio preventivamente approvato Da (compreso) A (escluso) Insegnamento
Arc - Urb - Cost (Mag.)(ord. 270) - MI (1095) BUILDING AND ARCHITECTURAL ENGINEERING*AZZZZ057688 - DATA ANALYTICS FOR SMART AGRICULTURE
Arc - Urb - Cost (Mag.)(ord. 270) - MI (1096) MANAGEMENT OF BUILT ENVIRONMENT - GESTIONE DEL COSTRUITO*AZZZZ057688 - DATA ANALYTICS FOR SMART AGRICULTURE
Arc - Urb - Cost (Quinq.)(ord. 270) - LC (1144) INGEGNERIA EDILE - ARCHITETTURA*AZZZZ057688 - DATA ANALYTICS FOR SMART AGRICULTURE
Ing - Civ (Mag.)(ord. 270) - MI (488) INGEGNERIA CIVILE - CIVIL ENGINEERING*AZZZZ057498 - DATA ANALYTICS FOR SMART AGRICULTURE
Ing - Civ (Mag.)(ord. 270) - MI (489) INGEGNERIA PER L'AMBIENTE E IL TERRITORIO - ENVIRONMENTAL AND LAND PLANNING ENGINEERING*AZZZZ057498 - DATA ANALYTICS FOR SMART AGRICULTURE
Ing Ind - Inf (Mag.)(ord. 270) - BV (477) ENERGY ENGINEERING - INGEGNERIA ENERGETICA*AZZZZ057498 - DATA ANALYTICS FOR SMART AGRICULTURE
Ing Ind - Inf (Mag.)(ord. 270) - BV (478) NUCLEAR ENGINEERING - INGEGNERIA NUCLEARE*AZZZZ057498 - DATA ANALYTICS FOR SMART AGRICULTURE
Ing Ind - Inf (Mag.)(ord. 270) - BV (479) MANAGEMENT ENGINEERING - INGEGNERIA GESTIONALE*AZZZZ057498 - DATA ANALYTICS FOR SMART AGRICULTURE
Ing Ind - Inf (Mag.)(ord. 270) - BV (483) MECHANICAL ENGINEERING - INGEGNERIA MECCANICA*AZZZZ057498 - DATA ANALYTICS FOR SMART AGRICULTURE
Ing Ind - Inf (Mag.)(ord. 270) - LC (485) MECHANICAL ENGINEERING - INGEGNERIA MECCANICA*AZZZZ057498 - DATA ANALYTICS FOR SMART AGRICULTURE
Ing Ind - Inf (Mag.)(ord. 270) - MI (471) BIOMEDICAL ENGINEERING - INGEGNERIA BIOMEDICA*AZZZZ057498 - DATA ANALYTICS FOR SMART AGRICULTURE
Ing Ind - Inf (Mag.)(ord. 270) - MI (473) AUTOMATION AND CONTROL ENGINEERING - INGEGNERIA DELL'AUTOMAZIONE*AZZZZ057498 - DATA ANALYTICS FOR SMART AGRICULTURE
Ing Ind - Inf (Mag.)(ord. 270) - MI (474) TELECOMMUNICATION ENGINEERING - INGEGNERIA DELLE TELECOMUNICAZIONI*AZZZZ057498 - DATA ANALYTICS FOR SMART AGRICULTURE
Ing Ind - Inf (Mag.)(ord. 270) - MI (475) ELECTRICAL ENGINEERING - INGEGNERIA ELETTRICA*AZZZZ057498 - DATA ANALYTICS FOR SMART AGRICULTURE
Ing Ind - Inf (Mag.)(ord. 270) - MI (481) COMPUTER SCIENCE AND ENGINEERING - INGEGNERIA INFORMATICA*AZZZZ057498 - DATA ANALYTICS FOR SMART AGRICULTURE
Ing Ind - Inf (Mag.)(ord. 270) - MI (491) MATERIALS ENGINEERING AND NANOTECHNOLOGY - INGEGNERIA DEI MATERIALI E DELLE NANOTECNOLOGIE*AZZZZ057498 - DATA ANALYTICS FOR SMART AGRICULTURE

Obiettivi dell'insegnamento

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”.. CSA is the implementation of the "Zero hunger" Sustainable Development Goals of the United Nations.


Risultati di apprendimento attesi

The course approach aims at providing students an understanding of the data value chain 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. Students will learn in a practical way the most common techniques for data processing and the tools to perform such processing with a focus on agricultural data. In the end, students will learn how data can be turned into an actionable source of information that can impact the agri-food value chain.


Argomenti trattati

The course lectures will cover from a theoretical perspective:

- An introduction to the recent trends in agriculture digitalization

- Strategic Developments Goal (SGD) and FoodClimate-Smart Agriculture (CSA).

- The impact of digitalization in agriculture and on the agriculture value chain.

- The data strategy and data governance in agriculture with some use cases

- Data sources in agriculture: IoT sensors, aerial imaging, remote sensing, meteo, etc.)

- Techniques for data processing: tabular data, temporal data, and spatial data In parallel to theoretical lectures, practical software laboratory activities will be dove on real data provided by agri-food companies that will also give seminar lectures presenting real life cases of digitalization in agriculture.


Prerequisiti

This course is intended as a Master Level class on data analytics. The foundations of data analysis will be provided by the course, nevertheless, basic notions of mathematics, statistics, databases, and (object-oriented) programming are assumed as pre-requirement for a successful attendance of the course.


Modalità di valutazione

The course aims to be an hands-on data analytics course thus the evaluation foresees a practical data analysis activity on real data. Students will thus be evaluated on data analysis projects and the evaluation will cover the technological aspects of their analysis as well as a proper study of its economical impact.


Bibliografia

Software utilizzato
Nessun software richiesto

Forme didattiche
Tipo Forma Didattica Ore di attività svolte in aula
(hh:mm)
Ore di studio autonome
(hh:mm)
Lezione
32:30
48:45
Esercitazione
17:30
26:15
Laboratorio Informatico
0:00
0:00
Laboratorio Sperimentale
0:00
0:00
Laboratorio Di Progetto
0:00
0:00
Totale 50:00 75:00

Informazioni in lingua inglese a supporto dell'internazionalizzazione
Insegnamento erogato in lingua Inglese
schedaincarico v. 1.8.3 / 1.8.3
Area Servizi ICT
01/03/2024