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Real-time automatic transport mode detection on smartphones using Recurrent Neural Networks

Valerio Arnaudo

Real-time automatic transport mode detection on smartphones using Recurrent Neural Networks.

Rel. Cristina Pronello, Giovanni Malnati. Politecnico di Torino, Corso di laurea magistrale in Ict For Smart Societies (Ict Per La Società Del Futuro), 2018

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Abstract:

Innovative transport solutions using ITS (Intelligent Transport Systems). The activity aims at defining innovative transport solutions using ITS (Intelligent Transport Systems) both at city (Compiègne) and regional level (Region Hauts de France) to maximize multimodality and improve the socio-economic development of the territory. For example, finding out new methods for collecting mobility data (and notably big data) from different sources could help in understanding the mobility patterns and propose tailored solutions at different geographical scales. Another example regards the design of “mobility as a service” where packages of services can be offered focusing also on the integrated ticketing.

Relators: Cristina Pronello, Giovanni Malnati
Academic year: 2017/18
Publication type: Electronic
Number of Pages: 61
Subjects:
Corso di laurea: Corso di laurea magistrale in Ict For Smart Societies (Ict Per La Società Del Futuro)
Classe di laurea: New organization > Master science > LM-27 - TELECOMMUNICATIONS ENGINEERING
Ente in cotutela: EURECOM - Telecom Paris Tech (FRANCIA)
Aziende collaboratrici: GRUPPO TORINESE TRASPORTI SPA
URI: http://webthesis.biblio.polito.it/id/eprint/7591
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