Smart Objects and Technologies for Social Good. Third International Conference, GOODTECHS 2017, Pisa, Italy, November 29-30, 2017, Proceedings

Research Article

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

Download
202 downloads
  • @INPROCEEDINGS{10.1007/978-3-319-76111-4_12,
        author={Davide Aguiari and Chiara Contoli and Giovanni Delnevo and Lorenzo Monti},
        title={Smart Mobility and Sensing: Case Studies Based on a Bike Information Gathering Architecture},
        proceedings={Smart Objects and Technologies for Social Good. Third International Conference, GOODTECHS 2017, Pisa, Italy, November 29-30, 2017, Proceedings},
        proceedings_a={GOODTECHS},
        year={2018},
        month={3},
        keywords={Smart mobility Cloud based architecture Crowdsensing Crowdsourcing Personal travel planner},
        doi={10.1007/978-3-319-76111-4_12}
    }
    
  • Davide Aguiari
    Chiara Contoli
    Giovanni Delnevo
    Lorenzo Monti
    Year: 2018
    Smart Mobility and Sensing: Case Studies Based on a Bike Information Gathering Architecture
    GOODTECHS
    Springer
    DOI: 10.1007/978-3-319-76111-4_12
Davide Aguiari1,*, Chiara Contoli1,*, Giovanni Delnevo1,*, Lorenzo Monti1,*
  • 1: Università di Bologna
*Contact email: davide.aguiari2@unibo.it, chiara.contoli@unibo.it, giovanni.delnevo2@unibo.it, lorenzo.monti20@unibo.it

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.