Assistant: Stefano Scanzio
www: https://www.skenz.it/ss
email: stefano.scanzio [ AT_SYMBOL ] unimib.it

• [2024/04/07]: Preliminary material uploaded on the website of the course

• [2024/06/05] from 14:30 to 16:30 (room LAB908)
• [2024/06/05] from 10:30 to 12:30 (room U4-04)
• [2024/05/29] from 14:30 to 16:30 (room LAB908)
• [2024/05/29] from 10:30 to 12:30 (room U4-04)
• [2024/05/22] from 14:30 to 16:30 (room LAB908)
• [2024/05/22] from 10:30 to 12:30 (room U4-04)
• [2024/05/15] from 14:30 to 16:30 (room LAB908)
• [2024/05/15] from 10:30 to 12:30 (room U4-04)
• [2024/04/24] from 14:30 to 16:30 (room LAB908)
• [2024/04/24] from 10:30 to 12:30 (room U4-04)

• Slide: upload in next few week

Example of packets captured through Wireshark:

• MQTT subscriber MQTT_subscriber.pcap
• Examples of POST and GET requests in Flask: FLASK_POST_GET.pcap

Example did in classroom:

For the course, you need to install python and a programming environment such as Visual Studio Code. Please, follow this guideline: video guide

Thesis about the use of artificial neural networks for the prediction of the quality of a wireless channel (see the video)
.

Thesis about reducing communication latency in TSCH wireless sensor networks by using black and white listening techniques (see the video)
.

Thesis proposals can be downloaded here: https://www.skenz.it/ss/theses
If interested, for informations, contact: stefano.scanzio [ AT_SYMBOL ] polito.it (tel. 011 090 5438) www: https://www.skenz.it/ss