PORTALE DELLA DIDATTICA

Ricerca CERCA
  KEYWORD

Mobile Edge Computing and augmented reality for the “augmented technician”

azienda Tesi esterna in azienda    estero Tesi all'estero


Parole chiave AUGMENTED REALITY, EDGE COMPUTING

Riferimenti PAOLO GIACCONE

Riferimenti esterni Leonardo Linguaglossa, Telecom Paris, linguaglossa@telecom-paris.fr

Gruppi di ricerca Telecommunication Networks Group

Tipo tesi EXPERIMENTAL - DEVELOPMENT

Descrizione The recent Edge computing paradigm is increasingly becoming an effective alternative to existing cloud computing technologies.
Edge systems have been initially designed under the supervision of the ETSI working group on Mobile Edge Computing (MEC) with a focus on mobile users. However, we observe nowadays that the interest has shifted towards other ICT domains. In particular, Edge computing has been identified as a potential key factor to achieve the performance and reliability offered by 5G and next generation networks. In this internship, the candidate will study the state-of-the-art of Edge systems, and implement one or more solutions for distributed computation and resource access. The target use case is the “augmented technician”: in this scenario, an operator uses an augmented reality device to obtain detailed information about their surroundings. Furthermore, they can perform some actions in real time by connecting to a remote tool. The internship can be an introductory step to enter a Ph.D.
The intern student will have to deploy an edge computing prototype within a real 5G private network, hosted by Telecom Paris lab. In parallel, they will have to work on distributed orchestration systems (e.g., Kubernetes) and computation units (e.g., containers) in a specific environment hosted by EDF, the largest electricity provider in France and Europe. Finally, they will have to deploy an existing augmented reality application by EDF to be transposed towards a containerized or VM-based application.

Vedi anche  stage_edf_2022_en.pdf 

Conoscenze richieste Excellent programming skills. Knowledge of the machine learning fundamentals.
Students with average grade higher than 27/30 are preferred.

Note The thesis will be done in the company, in collaborations with EDF and Telecom Paris.


Scadenza validita proposta 08/02/2023      PROPONI LA TUA CANDIDATURA




© Politecnico di Torino
Corso Duca degli Abruzzi, 24 - 10129 Torino, ITALY
Contatti