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Smart Mobility and Sensing: Case Studies Based on a Bike Information Gathering Architecture

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Abstract

Mapping services and travel planner applications are experiencing a great success in supporting people while they plan a route or while they move across the city, playing a key role in the smart mobility scenario. Nevertheless, they are based on the same algorithms, on the same elements (in terms of time, distance, means of transports, etc.), providing a limited set of personalization. To fill this gap, we propose PUMA, a Personal Urban Mobility Assistant that aims to let the user add different factors of personalization, such as sustainability, street and personal safety, wellness and health, etc. In this paper we focus on the use of smart bikes (equipped with specific sensors) as means of transports and as a mean to collect data about the urban environment. We describe a cloud based architecture, personas and travel scenario to prove the feasibility of our approach.

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Authors and Affiliations

  1. Interdepartmental Centre for Industrial ICT Research - CIRI ICT, Università di Bologna, Bologna, Italy

    Davide Aguiari, Chiara Contoli, Giovanni Delnevo & Lorenzo Monti

Authors
  1. Davide Aguiari

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  2. Chiara Contoli

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  3. Giovanni Delnevo

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  4. Lorenzo Monti

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Corresponding author

Correspondence toLorenzo Monti.

Editor information

Editors and Affiliations

  1. University of Pisa, Pisa, Italy

    Barbara Guidi

  2. University of Pisa, Pisa, Italy

    Laura Ricci

  3. Polytechnic University of Valencia, Valencia, Spain

    Carlos Calafate

  4. University of Padua, Padua, Italy

    Ombretta Gaggi

  5. University of Antwerp, Antwerp, Belgium

    Johann Marquez-Barja

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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Aguiari, D., Contoli, C., Delnevo, G., Monti, L. (2018). Smart Mobility and Sensing: Case Studies Based on a Bike Information Gathering Architecture. In: Guidi, B., Ricci, L., Calafate, C., Gaggi, O., Marquez-Barja, J. (eds) Smart Objects and Technologies for Social Good. GOODTECHS 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 233. Springer, Cham. https://doi.org/10.1007/978-3-319-76111-4_12

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