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  5. A Service-Oriented Approach to Crowdsensing for Accessible Smart Mobility Scenarios

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Article
English
2016

A Service-Oriented Approach to Crowdsensing for Accessible Smart Mobility Scenarios

0 Datasets

0 Files

English
2016
Mobile Information Systems
Vol 2016
DOI: 10.1155/2016/2821680

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Silvia Mirri
Silvia Mirri

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Silvia Mirri
Catia Prandi
Paola Salomoni
+3 more

Abstract

This work presents an architecture to help designing and deploying smart mobility applications. The proposed solution builds on the experience already matured by the authors in different fields: crowdsourcing and sensing done by users to gather data related to urban barriers and facilities, computation of personalized paths for users with special needs, and integration of open data provided by bus companies to identify the actual accessibility features and estimate the real arrival time of vehicles at stops. In terms of functionality, the first “monolithic” prototype fulfilled the goal of composing the aforementioned pieces of information to support citizens with reduced mobility (users with disabilities and/or elderly people) in their urban movements. In this paper, we describe a service-oriented architecture that exploits the microservices orchestration paradigm to enable the creation of new services and to make the management of the various data sources easier and more effective. The proposed platform exposes standardized interfaces to access data, implements common services to manage metadata associated with them, such as trustworthiness and provenance, and provides an orchestration language to create complex services, naturally mapping their internal workflow to code. The manuscript demonstrates the effectiveness of the approach by means of some case studies.

How to cite this publication

Silvia Mirri, Catia Prandi, Paola Salomoni, Franco Callegati, Andrea Melis, Marco Prandini (2016). A Service-Oriented Approach to Crowdsensing for Accessible Smart Mobility Scenarios. Mobile Information Systems, 2016, pp. 1-14, DOI: 10.1155/2016/2821680.

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Publication Details

Type

Article

Year

2016

Authors

6

Datasets

0

Total Files

0

Language

English

Journal

Mobile Information Systems

DOI

10.1155/2016/2821680

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