The modern mobile devices and the complete digitalization of the public and private transport networks have allowed to access useful information to understand the user’s mean of transportation. This enables a plethora of old and new applications in the fields of sustainable mobility, smart transportation, assistance, and e-health. The precise understanding of the travel means is at the basis of the development of a large range of applications. In this paper, a number of metrics has been identified to understand whether an individual on the move is stationary, walking, on a motorized private or public transport, with the aim of delivering to city users personalized assistance messages for: sustainable mobility, health, and/or for a better and enjoyable life, etc. Differently from the state-of-the-art solutions, the proposed approach has been designed to provide results, and thus collect metrics, in real operating conditions (imposed on the mobile devices as: a range of different devices kinds, operating system constraints managing Applications, active battery consumption manager, etc.). The paper reports the whole experimentations and results. The solution has been developed in the context of Sii-Mobility Km4City Research Project infrastructure and tools, GDPR compliant. The same solution has been used in Snap4City mobile Apps with experiments performed in Antwerp and Helsinki.

Classification of Users’ Transportation Modalities in Real Conditions", Proc. of the 26th International DMS Conference on Visualization and Visual Languages / Claudio Badii, Angelo Difino, Paolo Nesi, Irene Paoli, Michela Paolucci. - ELETTRONICO. - (2020), pp. 0-0. (Intervento presentato al convegno The 26th International DMS Conference on Visualization and Visual Languages) [10.18293/DMSVIVA20-016].

Classification of Users’ Transportation Modalities in Real Conditions", Proc. of the 26th International DMS Conference on Visualization and Visual Languages

Claudio Badii;Angelo Difino;Paolo Nesi
;
Irene Paoli;Michela Paolucci
2020

Abstract

The modern mobile devices and the complete digitalization of the public and private transport networks have allowed to access useful information to understand the user’s mean of transportation. This enables a plethora of old and new applications in the fields of sustainable mobility, smart transportation, assistance, and e-health. The precise understanding of the travel means is at the basis of the development of a large range of applications. In this paper, a number of metrics has been identified to understand whether an individual on the move is stationary, walking, on a motorized private or public transport, with the aim of delivering to city users personalized assistance messages for: sustainable mobility, health, and/or for a better and enjoyable life, etc. Differently from the state-of-the-art solutions, the proposed approach has been designed to provide results, and thus collect metrics, in real operating conditions (imposed on the mobile devices as: a range of different devices kinds, operating system constraints managing Applications, active battery consumption manager, etc.). The paper reports the whole experimentations and results. The solution has been developed in the context of Sii-Mobility Km4City Research Project infrastructure and tools, GDPR compliant. The same solution has been used in Snap4City mobile Apps with experiments performed in Antwerp and Helsinki.
2020
DMSVIVA 2020 - Proceedings of the 26th International DMS Conference on Visualization and Visual Languages
The 26th International DMS Conference on Visualization and Visual Languages
Goal 11: Sustainable cities and communities
Claudio Badii, Angelo Difino, Paolo Nesi, Irene Paoli, Michela Paolucci
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1199410
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