Starting from the competences acquired in previous courses on Electronic Circuits and Systems, Programming and in the parallel course on Sensors and Communications, in this course they will be harmonized for learning how to design and build IoT (Internet of Things) Solutions for Agriculture. The course is organized with a theoretical introduction to Smart Systems and their application for building IoT solutions, with in parallel practical laboratories for the setup of experiments where IoTs are used for collecting data, processing them and generate the first presentation of data by user-friendly interfaces. In particular, will be analyzed and used MQTT (Message Queue Telemetry Transport) that is a lightweight, publish-subscribe, machine to machine network protocol for message queuing service, designed for connections with remote locations that have devices with resource constraints or limited network bandwidth.

Expected knowledge: - Extraction of data from sensors, with their processing and transmission - Design and implementation of smart systems for building IoT solutions Expected competences and skills: - Ability of analysing a problem and mapping it to the implementation of an IoT solution for Precision Agriculture - Ability of implementating the full AgriFood chain: data collection – processing – transmission – user interface - Necessary skills for designing an IoT system, extracting the specifications and needs from the agriculture domain

Elements of electronic circuits and systems, and programming techniques, like the ones acquired in the first semester of the AgriTech Engineering curriculum

The course is structured in theoretical aspects where the basics of IoT are explained, and a practical part with laboratories where the acquired knowledge is applied. Theoretical aspects (40 hours): - Introduction to IoT systems and their architecture - IoT and data analytics in precision agriculture: benefits and challenges - Crop management system using IoT - Smart irrigation and crop security in agriculture using IoT - The IoT in agriculture for sustainable rural development - Introduction to data-formatting for exchange of information (XML, JSON) - Python scripting for data management - Publish/subscribe communication paradigm (MQTT) - Examples of application of IoT to Agriculture. Laboratories (20 hours): - Implementation of IoT solutions getting real data from the fields where Politecnico’s researcher have their experimental setups - Hardware and Software implementation of smart systems for data analysis, processing and presentation - Development of a project for the final exam.

The course is structured merging the theoretical (30 hours) and the practical aspects (30 hours), for preparing the students to be able to implement at the end of the course a simple project of an IoT solution, that will be evaluated for the final exam grade. It is considered a visit to a production site, where the researchers of Politecnico are working, for showing in a real environment the technologies explained and used during the course. The course will be held based on slides, available on the Training Portal of Politecnico and in the Portal will be given available also the needed tools for the project development. In case of remote teaching, the theoretical lectures will be given by the standard remote teaching facilities of Politecnico, else, for the labs, will be given available to the students the needed platforms for working at home.

- Course Slides - AI, Edge and IoT-based Smart Agriculture, 1st Edition - November 10, 2021, Editors: Ajith Abraham, Sujata Dash, Joel J.P.C. Rodrigues, Biswaranjan Acharya, Subhendu Kumar Pani, Elsevier - Internet of Things (IoT) Enabled Automation in Agriculture, Rajesh Singh, Anita Gehlot, Bhupendra Singh, Sushabhan Choudhury, ISBN 9781032428741, CRC Press

Modalità di esame: Prova orale obbligatoria; Elaborato scritto prodotto in gruppo;

Exam: Compulsory oral exam; Group essay;

... The exam is based on a project where the students will develop a simple IoT solution, decided with the professor. The project is developed in groups of 2-3 people. The students will be requested to prepare a written report, that will be discussed in an oral session. The final grade will be done evaluating the written project, with the presentation and the discussion during the oral session.

Gli studenti e le studentesse con disabilità o con Disturbi Specifici di Apprendimento (DSA), oltre alla segnalazione tramite procedura informatizzata, sono invitati a comunicare anche direttamente al/la docente titolare dell'insegnamento, con un preavviso non inferiore ad una settimana dall'avvio della sessione d'esame, gli strumenti compensativi concordati con l'Unità Special Needs, al fine di permettere al/la docente la declinazione più idonea in riferimento alla specifica tipologia di esame.