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Telecommunication Networks Group

Theses at Politecnico

Distributed machine learning on vehicles

keywords MACHINE LEARNING, VEHICULAR NETWORKS

Reference persons CLAUDIO ETTORE CASETTI, PAOLO GIACCONE

Research Groups Telecommunication Networks Group

Thesis type DEVELOPMENT, SIMULATION

Description Given the plethora of sensors with which vehicles are equipped, today’s automated vehicles already generate large amounts of data that enable data-driven solutions for vehicle control, safety and comfort, as well as to effectively implement convenience applications.
The goal of this thesis work is to develop a custom framework on the CARLA simulator (https://carla.org/) leveraging SUMO traces of vehicles, and other transportation means. The framework would exploit the use of different technologies (i.e., camera, lidar, radar, IMU, etc.) and distributed machine learning techniques (e.g., federated learning) in order to develop object detection applications focused on crowdsensing tasks directly from the vehicles video cameras.

Required skills Background on machine learning
Linux
Excellent programming in Python


Deadline 20/12/2023      PROPONI LA TUA CANDIDATURA




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