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Open AccessConcept Paper

Natural Computing Applied to the Underground System: A Synergistic Approach for Smart Cities

ETSI Sistemas Informáticos, Universidad Politécnica de Madrid, Madrid 28031, Spain
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Current address: ETSISI, Calle Alan Turing s/n, 28031 Madrid, Spain.
Sensors 2018, 18(12), 4094; https://doi.org/10.3390/s18124094
Received: 16 October 2018 / Revised: 15 November 2018 / Accepted: 19 November 2018 / Published: 22 November 2018
(This article belongs to the Special Issue Algorithm and Distributed Computing for the Internet of Things)
The management and proper use of the Urban Public Transport Systems (UPTS) constitutes a critical field that has not been investigated in accordance to its relevance and urgent idiosyncrasy within the Smart Cities realm. Swarm Intelligence is a very promising paradigm to deal with such complex and dynamic systems. It presents robust, scalable, and self-organized behavior to deal with dynamic and fast changing systems. The intelligence of cities can be modelled as a swarm of digital telecommunication networks (the nerves), ubiquitously embedded intelligence, sensors and tags, and software. In this paper, a new approach based on the use of the Natural Computing paradigm and Collective Computation is shown, more concretely taking advantage of an Ant Colony Optimization algorithm variation and Fireworks algorithms to build a system that makes the complete control of the UPTS a tangible reality. View Full-Text
Keywords: urban public transport system; smart city; natural computing; collective computation urban public transport system; smart city; natural computing; collective computation
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Morales Lucas, C.; De Mingo López, L.F.; Gómez Blas, N. Natural Computing Applied to the Underground System: A Synergistic Approach for Smart Cities. Sensors 2018, 18, 4094.

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