Timetable & learning outcomes
Throughout this summer school, renowned and dynamic speakers will share their insight on the latest advances and applications of the Internet of Things technology as a driver for innovative digital infrastructures.
Mornings will be dedicated to theoretical sessions that include an introduction and applied lecture on each of the following topics:
› Radio
communications
› Communication
techniques
› Data
processing
› Machine
learning
› Deep
learning
During these presentations, various methodologies adapted to each stage of project development will also be presented, thus supplementing the practical sessions taking place each afternoon.
These practical sessions will start with an introduction to the technology that will then be implemented during the hands-on workshops. Participants will work in groups with complementary skillsets and will be assisted by tutors in the development of a connected object. Each group will imagine and design an object and will programme an Arduino, connect it to the Cloud, design the 3D object and deploy it in order to process its data.
Tentative programme
Please note: the schedule is presented in
Central European Summer Time (CEST). This programme may be subject to change.
|
Monday September 18th |
Tuesday September 19th |
Wednesday September 20th |
Thursday September 21st |
Friday September 22nd |
09.00 – 10.00 |
09.00 – 10.30 Lecture How to choose a communication technique? Marwane Rezzouki |
09.00 - 10.30 Lecture Streams Algorithms for Internet of Things and big data Nicolas Hanusse |
09.00 – 10.30 Lecture From embedded devices to the cloud: choosing the right Internet of Things technologies Pierre-Marie Ancele |
09.00 – 10.30 Lecture Learning and deep learning Akka Zemmari |
|
10.00 – 10.30 Welcome and introduction Guillaume Ferré |
||||
|
10.30 –
11.00 Coffee break |
10.30 – 11.00 Coffee break |
10.30 – 11.00 Coffee break |
10.30 – 11.00 Coffee break |
10.30 – 11.00 Coffee break |
|
11.00 – 12.00 Lecture Introduction to radio communications François Rivet |
11.00 – 12.00 Tutorial From object to cloud: establishing communication, data framing and display Marwane Rezzouki |
11.00 – 12.00 Lecture Learning in the IoT framework Jérémie Bigot |
11.00 – 12.00 Lecture Cybersecurity for the IoT Romain Deniéport |
11.00 – 12.00 Lecture Deep learning for big data in the Internet of Things Akka Zemmari |
|
12.00 –
13.30 Lunch |
12.00 – 13.30 Lunch |
12.00 – 13.30 Lunch |
12.00 – 13.30 Lunch |
12.00 – 13.30 Lunch |
|
13.30 – 15.00 Tutorial Introduction to programming on Arduino Christophe Jégo |
13.30 – 15.00 Tutorial From object to cloud: establishing communication, data framing and display Marwane Rezzouki |
13.30 – 15.00 Tutorial Outliers processing Pierrick Legrand |
13.30 – 15.00 Tutorial From rapid prototyping to maker culture Julien Allali |
13.30 – 15.00 Tutorial From raw data to learning and deep learning Romain Giot |
|
15.00 –
15.15 Coffee break |
15.00 – 15.15 Coffee break |
15.00 – 15.15 Coffee break |
15.00 – 15.15 Coffee break |
15.00 – 15.15 Coffee break |
|
15.15 – 17.00 Tutored workshop Arduino programming Christophe Jégo |
15.15 – 17.00 Tutored workshop Arduino programming Marwane Rezzouki |
15.15 – 17.00 |
15.15 – 17.00 Tutored workshop Design a connected device based on 3D printing Julien Allali |
15.15 – 17.00 Tutored workshop From raw data to learning and deep learning Romain Giot |
|
17.00 – 18.00 Lecture Challenges in the design of integrated systems for Internet of Things Muhammad Tahir Abbas |
17.00 – 18.00 Lecture The grey side of the Internet of Things Thibault Pirson |
17.00 – 18.00 Lecture Energy harvesting Philippe Laurent |
17.00 – 18.00 Lecture Safety and Security of Connected Vehicles Mohamed Mosbah |
|
18.00 – 21.00 |
18.00 – 21.00 |
Expertise upon completion
The summer school offers a unique opportunity to develop strong knowledge of the Internet of things within a programme covering the principles of digital radio communications; programming techniques on an Arduino type microcontroller; LPWAN (Low Power Wide Area Network) communication technologies; 3D printing and laser cutting; big data, learning and deep learning.
A certificate of participation will be awarded to students upon completion of the course.
Programme may be subject to change.