Recommender systems for smart cities

Quijano-Sánchez, Lara; Cantador, Iván; Cortés-Cediel, María E.; Gil, Olga

doi:10.1016/j.is.2020.101545

Cited by 97 publications

(71 citation statements)

References 110 publications

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“…In short, it represents an overlap between the fields of technology and modern urban design [21]. The concept has matured over the years and now represents a dynamic line of research that has been generating an increasing number of publications, as reflected in [5].…”

Section: Background and Motivationmentioning

confidence: 99%

“…A literature review reveals the scientific community's major interest in developing efficient and sustainable models for cities. Some studies provide an overview of smart city projects and describe different case studies [5,22]. However, most research focuses on specific smart city domains, such as security and data protection [23][24][25], networking [26], detection of anomalies [27,28], transport [29][30][31], energy consumption [32][33][34], business [35] or government [36][37][38].…”

Section: Background and Motivationmentioning

confidence: 99%

“…Nevertheless, the sheer breadth of smart city projects means that the development process is highly complex. Countless imponderables arise, frequently leaving existing initiatives by the wayside or, at best, leading to humbler redefinitions of these initiatives; so much so, in fact, that very often, all that is left of the smart city is its name, or the intention behind its conception [5,6].…”

Section: Introductionmentioning

confidence: 99%

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Modelling and Implementing Smart Universities: An IT Conceptual Framework

2021

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The smart city concept has been gaining momentum in the scientific community because of its potentially huge impact on citizens’ quality of life. However, expectations have not yet been met in practice. This is firstly due to the sheer breadth of such projects and secondly to the lack of methodologies available to guide the development of flexible and sustainable platforms over time. In this work, we propose to address these issues by using a university campus as a less complex mock-up version of a city. Despite differences between them, we find services that are common to both, and a medium-sized city’s population is comparable to that of a university community. We propose an IT conceptual framework to model and implement smart university projects, which supports the design of a platform that is both in line with the strategic plans of universities and is flexible, sustainable, stable, and sufficiently modular to support the addition of different value-added services over the years. Our framework is based on a service provision model materialised in an IT architecture and managed following a methodology to integrate IT components that ensure the insertion of new, smart initiatives of value to the community, aligned with the university’s needs, via a value-added service planning process. The results are presented in the University of Alicante case study and the SmartUA project.

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Section: Background and Motivationmentioning

confidence: 99%

Section: Background and Motivationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Modelling and Implementing Smart Universities: An IT Conceptual Framework

2021

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“…Smart cities [1][2][3] usually apply modern network infrastructures and information techniques to improve the citizens' living quality and make cities run more efficiently. Recently, there have been some cities committed to building smart cities in the world, including Chicago, Milton Keynes, Busan, and Shanghai.…”

Section: Introductionmentioning

confidence: 99%

High-Performance Server-Based Live Streaming Transmission Optimization for Sports Events in Smart Cities

Chen

Zhao

2021

Mobile Information Systems

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Smart cities allow cities to run more efficiently and have been approved by a lot of cities. During the process of building smart cities, a large amount of data is generated. Particularly, live sports events have been regarded as the inalienable part of smart cities. However, with the improvement in the quality of life, people tend to obtain better watching experience in terms of sports events. For such purpose, this paper proposes the live streaming transmission optimization method based on high-performance server, called HPTO, including two main modules, that is, high-performance server optimization and transmission optimization. Specifically, for the server optimization, this paper devises a distributed storage strategy to avoid producing the internal disk fragments and improve the writing efficiency of sports videos. For the transmission optimization, this paper devises a deep-learning-based video compression strategy to save the storage space of server and accelerate the transmission of sports videos. In addition, this paper makes simulation experiments based on PyCharm. The experimental results show that HPTO has higher storage efficiency, smaller transmission time, and lower packet loss rate than benchmarks, which indicates that the proposed two aspects of optimization strategies (server optimization and transmission optimization) are efficient.

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“…e mobile Internet and Internet of ings (IoT) have been developed in recent years [1] especially during the process of building the smart cities [2], which has been generating the billions of Internet traffic due to the sharp increasing number of mobile devices (such as smart phone and wearable monitors). For example, the Cisco Annual Internet Report (CAIR) [3] shows that the total number of global mobile devices will grow from 5.1 billion (66 percent of population) in 2018 to 5.7 billion (71 percent of population) by 2023.…”

Section: Introductionmentioning

confidence: 99%

DRL-Based Edge Computing Model to Offload the FIFA World Cup Traffic

Che

2020

Mobile Information Systems

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In recent years, the volume of global video traffic has been increasing rapidly and it is considerably significant to offload the traffic during the process of video transmission and improve the experience of users. In this paper, we propose a novel traffic offloading strategy to provide a feasible and efficient reference for the following 2022 FIFA World Cup held in Qatar. At first, we present the system framework based on the Mobile Edge Computing (MEC) paradigm, which supports transferring the FIFA World Cup traffic to the mobile edge servers. Then, the Deep Reinforcement Learning (DRL) is used to provide the traffic scheduling method and minimize the scheduling time of application programs. Meanwhile, the task scheduling operation is regarded as the process of Markov decision, and the proximal policy optimization method is used to train the Deep Neural Network in the DRL. For the proposed traffic offloading strategy, we do the simulation based on two real datasets, and the experimental results show that it has smaller scheduling time, higher bandwidth utilization, and better experience of user than two baselines.

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Recommender systems for smart cities

Cited by 97 publications

References 110 publications

Modelling and Implementing Smart Universities: An IT Conceptual Framework

Modelling and Implementing Smart Universities: An IT Conceptual Framework

High-Performance Server-Based Live Streaming Transmission Optimization for Sports Events in Smart Cities

DRL-Based Edge Computing Model to Offload the FIFA World Cup Traffic

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