EAI Endorsed Transactions on Internet of Things 17(9): e3

Research Article

Maps for Easy Paths (MEP): Accessible Paths Tracking and Reconstruction

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  • @ARTICLE{10.4108/eai.31-8-2017.153050,
        author={S. Comai and E. De Bernardi and M. Matteucci and F. Salice},
        title={Maps for Easy Paths (MEP): Accessible Paths Tracking and Reconstruction},
        journal={EAI Endorsed Transactions on Internet of Things},
        volume={17},
        number={9},
        publisher={EAI},
        journal_a={IOT},
        year={2017},
        month={8},
        keywords={City accessibility, path reconstruction, motor impairments, mobile application.},
        doi={10.4108/eai.31-8-2017.153050}
    }
    
  • S. Comai
    E. De Bernardi
    M. Matteucci
    F. Salice
    Year: 2017
    Maps for Easy Paths (MEP): Accessible Paths Tracking and Reconstruction
    IOT
    EAI
    DOI: 10.4108/eai.31-8-2017.153050
S. Comai1,*, E. De Bernardi1, M. Matteucci1, F. Salice1
  • 1: Dipartimento di Elettronica Informazione e Bioingegneria, Politecnico di Milano – Piazza L. da Vinci 32, 20133 Milano, Italy
*Contact email: sara.comai@polimi.it

Abstract

MEP (Maps for Easy Paths) is a project for the enrichment of geographical maps with information about accessibility of urban pedestrian pathways, targeted at people with mobility problems. In this paper, we describe the tools developed to collect data along the paths travelled by target people and the algorithms for a good quality reconstruction of the path developed to overcome the intrinsic limitation of the sensors available on mobile devices. Experimental results show the feasibility of the approach.