Preprint Concept Paper Version 3 This version is not peer-reviewed

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

Version 1 : Received: 18 October 2018 / Approved: 18 October 2018 / Online: 18 October 2018 (11:04:28 CEST)
Version 2 : Received: 5 November 2018 / Approved: 6 November 2018 / Online: 6 November 2018 (09:19:35 CET)
Version 3 : Received: 15 November 2018 / Approved: 16 November 2018 / Online: 16 November 2018 (11:34:47 CET)

A peer-reviewed article of this Preprint also exists.

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. 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.

Journal reference: Sensors 2018, 18, 4094
DOI: 10.3390/s18124094

Abstract

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 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 behaviour 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 in order to build a system that makes the complete control of the UPTS a tangible reality.

Subject Areas

urban public transport system; smart city; natural computing; collective computation; ant colony optimization

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