Authors:
Marc Pous
;
Daniel Villatoro
;
F. Xavier Mercadal
and
Arol Viñolas
Affiliation:
Barcelona Digital Technology Center, Spain
Keyword(s):
Smartcities, Public Transportation Network, Crowdsensing.
Related
Ontology
Subjects/Areas/Topics:
Aggregation, Classification and Tracking
;
Applications and Uses
;
Artificial Intelligence
;
Data Communication Networking
;
Data Manipulation
;
Data Mining
;
Databases and Information Systems Integration
;
Enterprise Information Systems
;
Internet of Things
;
Multi-Sensor Data Processing
;
Sensor Networks
;
Signal Processing
;
Smart Buildings and Smart Cities
;
Soft Computing
;
Software Agents and Internet Computing
;
Software and Architectures
;
Telecommunications
Abstract:
Recently, and with the ever-increasing interest in Smart-city paradigm, urban mobility optimization is becoming an active research area. We are specially focused on the real-time optimization of the Public Transportation Networks, and the passenger flows. In order to achieve such task, it becomes essential to know the state of the network and its load of passengers in real-time. To the best of our knowledge, no existing infrastructure is able to keep track of the amount of public transportation users (and their position) in real time. In this paper we propose a framework architecture that transforms the passengers in active sensors and profit from the information they provide to estimate the actual usage of the network. In order to create an engaging experience for passengers (and incentivize the activation of the mobility sensor) we have implemented a higher level layer which offers users with a trivia-like game, where users compete against other users in real-time, while providing
their position on the network.
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