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Artificial Intelligence, Transport and the Smart City: Definitions and Dimensions of a New Mobility Era

TLDR
This work is ultimately a reference tool for researchers and city planners that provides clear and systematic definitions of the ambiguous smart mobility terms of tomorrow and describes their individual and collective roles underpinning the nexus in scope.
Abstract
Artificial intelligence (AI) is a powerful concept still in its infancy that has the potential, if utilised responsibly, to provide a vehicle for positive change that could promote sustainable transitions to a more resource-efficient livability paradigm. AI with its deep learning functions and capabilities can be employed as a tool which empowers machines to solve problems that could reform urban landscapes as we have known them for decades now and help with establishing a new era; the era of the “smart city”. One of the key areas that AI can redefine is transport. Mobility provision and its impact on urban development can be significantly improved by the employment of intelligent transport systems in general and automated transport in particular. This new breed of AI-based mobility, despite its machine-orientation, has to be a user-centred technology that “understands” and “satisfies” the human user, the markets and the society as a whole. Trust should be built, and risks should be eliminated, for this transition to take off. This paper provides a novel conceptual contribution that thoroughly discusses the scarcely studied nexus of AI, transportation and the smart city and how this will affect urban futures. It specifically covers key smart mobility initiatives referring to Connected and Autonomous Vehicles (CAVs), autonomous Personal and Unmanned Aerial Vehicles (PAVs and UAVs) and Mobility-as-a-Service (MaaS), but also interventions that may work as enabling technologies for transport, such as the Internet of Things (IoT) and Physical Internet (PI) or reflect broader transformations like Industry 4.0. This work is ultimately a reference tool for researchers and city planners that provides clear and systematic definitions of the ambiguous smart mobility terms of tomorrow and describes their individual and collective roles underpinning the nexus in scope.

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Applications of unmanned aerial vehicle (UAV) in road safety, traffic and highway infrastructure management: Recent advances and challenges.

TL;DR: Advances in computer vision algorithms to extract key features from UAV acquired videos and images are discussed along with the discussion on improvements made in traffic flow analysis methods, risk assessment and assistance in accident investigation and damage assessments for bridges and pavements.
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Can Building "Artificially Intelligent Cities" Safeguard Humanity from Natural Disasters, Pandemics, and Other Catastrophes? An Urban Scholar's Perspective.

TL;DR: The notion of an artificially intelligent city as the potential successor of the popular smart city brand is introduced—where the smartness of a city has come to be strongly associated with the use of viable technological solutions, including AI.
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The Sustainability of Artificial Intelligence: An Urbanistic Viewpoint from the Lens of Smart and Sustainable Cities

TL;DR: This viewpoint explores and questions the sustainability of AI from the lens of smart and sustainable cities, and generates insights into emerging urban artificial intelligences and the potential symbiosis between AI and a smart andustainable urbanism.
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Barriers and risks of Mobility-as-a-Service (MaaS) adoption in cities: A systematic review of the literature

TL;DR: In this paper, a systematic literature review was conducted to identify barriers and risks related to mobility-as-a-service (MaaS) adoption in cities, and the study revealed that the desired MaaS outcomes are associated with reduced vehicle kilometres travelled, increased trip awareness, reduced parking, reduced vehicle ownership, and improved social equity.
Journal ArticleDOI

Cycling in the Era of COVID-19: Lessons Learnt and Best Practice Policy Recommendations for a More Bike-Centric Future

TL;DR: The COVID-19 pandemic has affected our cities in monumental ways with no sector likely being more severely impacted than transport as mentioned in this paper, and many cities have reallocated street and public space to cyclists and introduced pro-bike interventions like pop-up cycle lanes, e-bike subsidies, free bike-share use and traffic calming measures.
References
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Journal ArticleDOI

The Internet of Things: A survey

TL;DR: This survey is directed to those who want to approach this complex discipline and contribute to its development, and finds that still major issues shall be faced by the research community.
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Internet of Things (IoT): A vision, architectural elements, and future directions

TL;DR: In this article, the authors present a cloud centric vision for worldwide implementation of Internet of Things (IoT) and present a Cloud implementation using Aneka, which is based on interaction of private and public Clouds, and conclude their IoT vision by expanding on the need for convergence of WSN, the Internet and distributed computing directed at technological research community.
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Internet of Things for Smart Cities

TL;DR: This paper will present and discuss the technical solutions and best-practice guidelines adopted in the Padova Smart City project, a proof-of-concept deployment of an IoT island in the city of Padova, Italy, performed in collaboration with the city municipality.
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Internet of Things - Technology and Value Added

TL;DR: The fields of application for IoT technologies are as numerous as they are diverse, as IoT solutions are increasingly extending to virtually all areas of everyday.
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A Cyber-Physical Systems architecture for Industry 4.0-based manufacturing systems

TL;DR: A unified 5-level architecture is proposed as a guideline for implementation of Cyber-Physical Systems (CPS), within which information from all related perspectives is closely monitored and synchronized between the physical factory floor and the cyber computational space.
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