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Introducing a Smart City Component in a Robotic Competition: A Field Report

In recent years, two fields have become more prominent in our everyday life: smart cities and service robots. In a smart city, information is collected from distributed sensors around the city into centralised data hubs and used to improve the efficiency of the city systems and provide better servic...

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Autores principales: Bardaro, Gianluca, Daga, Enrico, Carvalho, Jason, Chiatti, Agnese, Motta, Enrico
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8888918/
https://www.ncbi.nlm.nih.gov/pubmed/35252360
http://dx.doi.org/10.3389/frobt.2022.728628
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author Bardaro, Gianluca
Daga, Enrico
Carvalho, Jason
Chiatti, Agnese
Motta, Enrico
author_facet Bardaro, Gianluca
Daga, Enrico
Carvalho, Jason
Chiatti, Agnese
Motta, Enrico
author_sort Bardaro, Gianluca
collection PubMed
description In recent years, two fields have become more prominent in our everyday life: smart cities and service robots. In a smart city, information is collected from distributed sensors around the city into centralised data hubs and used to improve the efficiency of the city systems and provide better services to citizens. Exploiting major advances in Computer Vision and Machine Learning, service robots have evolved from performing simple tasks to playing the role of hotel concierges, museum guides, waiters in cafes and restaurants, home assistants, automated delivery drones, and more. As digital agents, robots can be prime members of the smart city vision. On the one hand, smart city data can be accessed by robots to gain information that is relevant to the task in hand. On the other hand, robots can act as mobile sensors and actuators on behalf of the smart city, thus contributing to the data acquisition process. However, the connection between service robots and smart cities is surprisingly under-explored. In an effort to stimulate advances on the integration between robots and smart cities, we turned to robot competitions and hosted the first Smart Cities Robotics Challenge (SciRoc). The contest included activities specifically designed to require cooperation between robots and the MK Data Hub, a Smart City data infrastructure. In this article, we report on the competition held in Milton Keynes (UK) in September 2019, focusing in particular on the role played by the MK Data Hub in simulating a Smart City Data Infrastructure for service robots. Additionally, we discuss the feedback we received from the various people involved in the SciRoc Challenge, including participants, members of the public and organisers, and summarise the lessons learnt from this experience.
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spelling pubmed-88889182022-03-03 Introducing a Smart City Component in a Robotic Competition: A Field Report Bardaro, Gianluca Daga, Enrico Carvalho, Jason Chiatti, Agnese Motta, Enrico Front Robot AI Robotics and AI In recent years, two fields have become more prominent in our everyday life: smart cities and service robots. In a smart city, information is collected from distributed sensors around the city into centralised data hubs and used to improve the efficiency of the city systems and provide better services to citizens. Exploiting major advances in Computer Vision and Machine Learning, service robots have evolved from performing simple tasks to playing the role of hotel concierges, museum guides, waiters in cafes and restaurants, home assistants, automated delivery drones, and more. As digital agents, robots can be prime members of the smart city vision. On the one hand, smart city data can be accessed by robots to gain information that is relevant to the task in hand. On the other hand, robots can act as mobile sensors and actuators on behalf of the smart city, thus contributing to the data acquisition process. However, the connection between service robots and smart cities is surprisingly under-explored. In an effort to stimulate advances on the integration between robots and smart cities, we turned to robot competitions and hosted the first Smart Cities Robotics Challenge (SciRoc). The contest included activities specifically designed to require cooperation between robots and the MK Data Hub, a Smart City data infrastructure. In this article, we report on the competition held in Milton Keynes (UK) in September 2019, focusing in particular on the role played by the MK Data Hub in simulating a Smart City Data Infrastructure for service robots. Additionally, we discuss the feedback we received from the various people involved in the SciRoc Challenge, including participants, members of the public and organisers, and summarise the lessons learnt from this experience. Frontiers Media S.A. 2022-02-16 /pmc/articles/PMC8888918/ /pubmed/35252360 http://dx.doi.org/10.3389/frobt.2022.728628 Text en Copyright © 2022 Bardaro, Daga, Carvalho, Chiatti and Motta. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Robotics and AI
Bardaro, Gianluca
Daga, Enrico
Carvalho, Jason
Chiatti, Agnese
Motta, Enrico
Introducing a Smart City Component in a Robotic Competition: A Field Report
title Introducing a Smart City Component in a Robotic Competition: A Field Report
title_full Introducing a Smart City Component in a Robotic Competition: A Field Report
title_fullStr Introducing a Smart City Component in a Robotic Competition: A Field Report
title_full_unstemmed Introducing a Smart City Component in a Robotic Competition: A Field Report
title_short Introducing a Smart City Component in a Robotic Competition: A Field Report
title_sort introducing a smart city component in a robotic competition: a field report
topic Robotics and AI
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8888918/
https://www.ncbi.nlm.nih.gov/pubmed/35252360
http://dx.doi.org/10.3389/frobt.2022.728628
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