84237 - Wireless Networks for the Internet of Things (2nd cycle)

Academic Year 2018/2019

  • Docente: Davide Dardari
  • Credits: 6
  • SSD: ING-INF/03
  • Language: Italian

Learning outcomes

Skills in the design of wireless sensor networks applied to Internet of things scenarios and, more in general, to cyber-physical systems devoted to monitor and control physical processes. In particular, knowledge of the main short-range low-complexity wireless technologies, and mastery of efficient methods to acquire, diffuse and process data in wireless sensor networks.

Course contents

  • Introduction to the requirements and technologies for the Internet of Things, with particular reference to wireless sensor networks.
  • Short-range communication techniques - connectivity models - energy efficient routing and synchronization protocols.
  • Distributed detection and estimation of physical entities.
  • Bayesian methods for optimal estimation and tracking (Bayesian filters, Kalman filter).
  • Case study examples and laboratory activity on the design of wireless networks.

Readings/Bibliography

The slides adopted during the frontal lesson will be made available to students through Internet.

The acquisition of dedicated books is not required.

 

Bibliography for further deepening:

R. Verdone, D. Dardari, G. Mazzini, A. Conti "Wireless sensor and actuator networks: technologies, analysis and design", Ed. Elsevier, 2008.

Teaching methods

The course consists of 6 CFU of which 3 CFU of frontal lessons and 3 CFU (30 hours), of laboratory group experiences on projects identified by the students.

The laboratory is equipped with 5 development kits for wireless sensor networks.

The objective of practical activity is twofold:

- acquire confidence with typical development tools for wireless networks;

- acquire the skills to carry out individual and team design activities.

 

Assessment methods

A comprehensive oral exam will assess skills acquired during the course and during the group laboratory activity. 

Optionally, students have the faculty to prepare and discuss a simulation project, previously agreed with the supervisor.

Teaching tools

The slides adopted during the frontal lesson will be made available to students through Internet.

Matlab environment.

Laboratory equipped with 5 development kits for wireless sensor networks.

Office hours

See the website of Davide Dardari