78205 - Laboratory of Sensor Networks for Energy and Environment

Course Unit Page

SDGs

This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.

Affordable and clean energy Industry, innovation and infrastructure

Academic Year 2018/2019

Learning outcomes

The course gives elements for the analysis and design of wireless sensors for environmental monitoring. The analysis and design of signal processing and communication techniques are carried out through the development of Matlab code, while the design of wireless sensors is based on experiments on a real software defined radio (SDR) platform. The course starts with a review of basic knowledge of digital signal processing and data transmission and then provides solutions to transmit data from sensors with hands-on sensor networks. The laboratory exercises allow the student to practise with software tools (like the Matlab platform) as well as hardware (SDR platform).

Course contents

Introduction to wireless sensor networks (WSNs) and their applications with particular emphasis on environmental monitoring. Review of A-to-D and D-to-A conversion. Implementation of basic signal processing algorithms for acquisition and transmission of information. Practical implementation of algorithms on a software defined radio (SDR) platform.

Readings/Bibliography

A. V. Oppenheim, R. W. Schafer, Elaborazione Numerica dei Segnali, Franco Angeli, 1996.

V. K. Ingle, J. G. Proakis, Digital Signal Processing using MATLAB, Brooks/Cole, 2000.

J. G. Proakis, M. Salehi, Contemporary Communication Systems using MATLAB, Brooks/Cole, 2000.

L. Calandrino, M. Chiani, Lezioni di Comunicazioni Elettriche, Pitagora Editrice, Bologna, 2013.

Teaching methods

The course, partly as lectures and partly as laboratory sessions, follows a basic methodology that consists in problem formulation, problem solution, laboratory simulation (Matlab) to assess the solution, and experimentation (with the SDR platform).

Assessment methods

During the course, students are divided into groups to carry out some laboratory exercises and write short reports. The final exam consists of a laboratory test and questions to assess the acquired theoretical aspects. In the laboratory test students are requested to write Matlab code to solve signal processing and data transmission problems.

Teaching tools

The course consists of laboratory exercises to learn basic aspects of signal processing and data transmission by writing Matlab code. There are also several experiments on a real SDR platform.

Links to further information

http://sites.google.com/site/andrewgiorgetti/home

Office hours

See the website of Andrea Giorgetti