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Vehicular data analysis based on Deep Learning

azienda Thesis in external company    


keywords CONTRASTIVE LEARNING, DEEP LEARNING, GRAPH NEURAL NETWORKS, MACHINE LEARNING

Reference persons LUCA CAGLIERO, FRANCESCO VACCARINO, LUCA VASSIO

Research Groups DAUIN - GR-04 - DATABASE AND DATA MINING GROUP - DBDM

Thesis type APPLIED RESEARCH

Description Research collaboration between PoliTo and Tierra Spa -- multinational telematics service provider (https://www.tierratelematics.com/)

Objectives:
- Profiling of fleets of industrial vechicles based the analysis on geo-spatial and CAN Bus Data (i.e., IOT signals monitoring engine and vehicle status)
- Definition, identification, and characterization of Points-Of-Interests (e.g., job sites, deposits, filling stations)
- Design, development and testing of machine learning models for smart vehicle management (based upon domain experts' indications)

Techniques:
- Clustering
- Contrastive learning
- Graph Neural Networks

Required skills Fundamentals of Python, Databases, Data Mining and Machine Learning


Deadline 31/08/2024      PROPONI LA TUA CANDIDATURA




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