Elective major - Smart City

Campus : Dijon
Prerequisites: Instrumentation, Signal and Data stream

Objective

The ESEO Smart-City engineer knows the data cycle and its impact:

- Collection (connected instrumentation, IoT)
- Transport (urban networks, energy/environment)
- Storage (Big Data, Cloud)
- Operation (Artificial Intelligence, simulation)

They interpret and exploit urban data, design "intelligent" buildings (home automation and BIM) and are familiar with the various technologies involved.

Common Core

ESEO Dijon offers a core curriculum common to the 3 options on the Dijon campus: E-Health, Industry 4.0 and Smart City.

This theoretical and technical core covers the following areas: artificial intelligence, HMI, networks, data analysis, sensors, connected objects, cyber security, signals, images, databases, and many others.

Skills

The Smart City option trains future ESEO engineers in the development of intelligent cities and the urban solutions of tomorrow: optimising energy management, analysing city data, improving transport flows and providing solutions for new uses.

This is a fast-growing field, requiring a high level of both technical and human skills: supervision, involvement of local authorities and citizens, etc.

Teaching units

Semester 8

English: 2 ECTS – 24h
Cross-disciplinary skills: 2 ECTS – 28h
- QHSE, Green IT, Excel
Connected Instrumentation Project: 4 ECTS – 56h
- Instrumentation, IoT
Data Sciences and Artificial Intelligence: 4 ECTS – 56h
- Statistics for Data Science, Supervised and Unsupervised Classification, Deep Learning
Computer Vision: 2 ECTS – 28h
Big Data: 2 ECTS – 28h
Project: 14 ECTS – 219h

Semester 9

IS & ID: 3 ECTS – 42h
Information Systems, Distributed Infrastructures
Flow optimisation: 2 ECTS – 28h
- Genetic algorithms
Virtual, augmented and mixed reality: 2 ECTS – 28h
- Introduction to Unity, AR/VR Project
Intelligent Territories: 4 ECTS – 54h
- Hypervisor, Geographic Information Systems, Smart Grid
Smart Building: 3 ECTS – 42h
- Home automation, Building Information Modelling, B.O.S
Digital and energy transition: 2 ECTS – 28h
Final year projects: 14 ECTS – 168h
- Advanced Artificial Intelligence, Big Data