34,106 research outputs found

    Citizen-Centric Data Services for Smarter Cities

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    Smart Cities use Information and Communication Technologies (ICT) to manage more efficiently the resources and services offered by a city and to make them more approachable to all its stakeholders (citizens, companies and public administration). In contrast to the view of big corporations promoting holistic “smart city in a box” solutions, this work proposes that smarter cities can be achieved by combining already available infrastructure, i.e., Open Government Data and sensor networks deployed in cities, with the citizens’ active contributions towards city knowledge by means of their smartphones and the apps executed in them. In addition, this work introduces the main characteristics of the IES Cities platform, whose goal is to ease the generation of citizen-centric apps that exploit urban data in different domains. The proposed vision is achieved by providing a common access mechanism to the heterogeneous data sources offered by the city, which reduces the complexity of accessing the city’s data whilst bringing citizens closely to a prosumer (double consumer and producer) role and allowing to integrate legacy data into the cities’ data ecosystem.The European Union’s Competitiveness and Innovation Framework Programme has supported this work under grant agreement No. 325097

    SMART CITY MANAGEMENT USING MACHINE LEARNING TECHNIQUES

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    In response to the growing urban population, smart cities are designed to improve people\u27s quality of life by implementing cutting-edge technologies. The concept of a smart city refers to an effort to enhance a city\u27s residents\u27 economic and environmental well-being via implementing a centralized management system. With the use of sensors and actuators, smart cities can collect massive amounts of data, which can improve people\u27s quality of life and design cities\u27 services. Although smart cities contain vast amounts of data, only a percentage is used due to the noise and variety of the data sources. Information and communication technology (ICT) and the Internet of Things (IoT) play a far more prominent role in developing smart cities when it comes to making choices, designing policies, and executing different methods. Smart city applications have made great strides thanks to recent advances in artificial intelligence (AI), especially machine learning (ML) and deep learning (DL). The applications of ML and DL have significantly increased the accuracy aspect of decision-making in smart cities, especially in analyzing the captured data using IoT-based devices and sensors. Smart cities employ algorithms that use unlabeled and labeled data to manage resources and deliver individualized services effectively. It has instantaneous practical use in many crucial areas, including smart health, smart environment, smart transportation system, energy management, and smart water distribution system in a smart city. Hence, ML and DL have become hot research topics in AI techniques in recent years and are proving to be accurate optimization techniques in smart cities. In addition, artificial intelligence algorithms enable the processing massive datasets and identify patterns and characteristics that would otherwise go unnoticed. Despite these advantages, researchers\u27 skepticism of AI\u27s sometimes mysterious inner workings has prevented it from being widely used for smart cities. This thesis\u27s primary intent is to explore the value of employing diverse AI and ML techniques in developing smart city-centric domains and investigate the efficacy of these proposed approaches in four different aspects of the smart city such as smart energy, smart transportation system, smart water distribution system and smart environment. In addition, we use these machine learning approaches to make a data analytics and visualization unit module for the smart city testbed. Internet-of-Things-based machine learning approaches in diverse aspects have repeatedly demonstrated greater accuracy, sensitivity, cost-effectiveness, and productivity, used in the built-in Virginia Commonwealth University\u27s real-time testbed

    Smart mobility: opportunity or threat to innovate places and cities

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    The concept of the “smart mobility” has become something of a buzz phrase in the planning and transport fields in the last decade. After a fervent first phase in which information technology and digital data were considered the answer for making mobility more efficient, more attractive and for increasing the quality of travel, some disappointing has grown around this concept: the distance between the visionarypotentialthatsmartness is providingis too far from the reality of urban mobility in cities. We argue in particular that two main aspects of smart mobility should be eluded: the first refers to the merely application to technology on mobility system, what we called the techo-centric aspect; the second feature is the consumer-centric aspect of smart mobility, that consider transport users only as potential consumers of a service. Starting from this, the study critics the smart mobility approach and applications and argues on a“smarter mobility” approach, in which technologies are only oneaspects of a more complex system. With a view on the urgency of looking beyond technology and beyond consumer-oriented solutions, the study arguments the need for a cross-disciplinary and a more collaborative approach that could supports transition towards a“smarter mobility” for enhancing the quality of life and the development ofvibrant cities. The article does not intend to produce a radical critique of the smart mobility concept,denying a priori its utility. Our perspectiveisthat the smart mobility is sometimes used as an evocativeslogan lacking some fundamental connection with other central aspect of mobility planning and governance. Main research questions are: what is missing in the technology-oriented or in the consumers-oriented smart mobility approach? What are the main risks behind these approaches? To answer this questions the paper provides in Section 2 the rationale behind the paper;Section 3 provides a literature review that explores the evolution on smart mobility paradigm in the last decades analysing in details the “techno-centric”and the “consumer-centric” aspects. Section 4proposes an integrated innovative approach for smart mobility, providing examples and some innovative best practices in Belgium. Some conclusions are finally drawnin Section 5, based on the role of smart mobility to create not only virtual platforms but high quality urban places

    Smart Cities: Towards a New Citizenship Regime? A Discourse Analysis of the British Smart City Standard

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    Growing practice interest in smart cities has led to calls for a less technology-oriented and more citizen-centric approach. In response, this articles investigates the citizenship mode promulgated by the smart city standard of the British Standards Institution. The analysis uses the concept of citizenship regime and a mixture of quantitative and qualitative methods to discern key discursive frames defining the smart city and the particular citizenship dimensions brought into play. The results confirm an explicit citizenship rationale guiding the smart city (standard), although this displays some substantive shortcomings and contradictions. The article concludes with recommendations for both further theory and practice development

    Named data networking for efficient IoT-based disaster management in a smart campus

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    Disasters are uncertain occasions that can impose a drastic impact on human life and building infrastructures. Information and Communication Technology (ICT) plays a vital role in coping with such situations by enabling and integrating multiple technological resources to develop Disaster Management Systems (DMSs). In this context, a majority of the existing DMSs use networking architectures based upon the Internet Protocol (IP) focusing on location-dependent communications. However, IP-based communications face the limitations of inefficient bandwidth utilization, high processing, data security, and excessive memory intake. To address these issues, Named Data Networking (NDN) has emerged as a promising communication paradigm, which is based on the Information-Centric Networking (ICN) architecture. An NDN is among the self-organizing communication networks that reduces the complexity of networking systems in addition to provide content security. Given this, many NDN-based DMSs have been proposed. The problem with the existing NDN-based DMS is that they use a PULL-based mechanism that ultimately results in higher delay and more energy consumption. In order to cater for time-critical scenarios, emergence-driven network engineering communication and computation models are required. In this paper, a novel DMS is proposed, i.e., Named Data Networking Disaster Management (NDN-DM), where a producer forwards a fire alert message to neighbouring consumers. This makes the nodes converge according to the disaster situation in a more efficient and secure way. Furthermore, we consider a fire scenario in a university campus and mobile nodes in the campus collaborate with each other to manage the fire situation. The proposed framework has been mathematically modeled and formally proved using timed automata-based transition systems and a real-time model checker, respectively. Additionally, the evaluation of the proposed NDM-DM has been performed using NS2. The results prove that the proposed scheme has reduced the end-to-end delay up from 2% to 10% and minimized up to 20% energy consumption, as energy improved from 3% to 20% compared with a state-of-the-art NDN-based DMS

    The role of urban living labs in a smart city

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    In a rapidly changing socio-technical environment cities are increasingly seen as main drivers for change. Against this backdrop, this paper studies the emerging Urban Living Lab and Smart City concepts from a project based perspective, by assessing a series of five Smart City initiatives within one local city ecosystem. A conceptual and analytical framework is used to analyse the architecture, nature and outcomes of the Smart City Ghent and the role of Urban Living Labs. The results of our analysis highlight the potential for social value creation and urban transition. However, current Smart City initiatives face the challenge of evolving from demonstrators towards real sustainable value. Furthermore, Smart Cities often have a technological deterministic, project-based approach, which forecloses a sustainable, permanent and growing future for the project outcomes. ‘City-governed’ Urban Living Labs have an interesting potential to overcome some of the identified challenges

    Fog-enabled Edge Learning for Cognitive Content-Centric Networking in 5G

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    By caching content at network edges close to the users, the content-centric networking (CCN) has been considered to enforce efficient content retrieval and distribution in the fifth generation (5G) networks. Due to the volume, velocity, and variety of data generated by various 5G users, an urgent and strategic issue is how to elevate the cognitive ability of the CCN to realize context-awareness, timely response, and traffic offloading for 5G applications. In this article, we envision that the fundamental work of designing a cognitive CCN (C-CCN) for the upcoming 5G is exploiting the fog computing to associatively learn and control the states of edge devices (such as phones, vehicles, and base stations) and in-network resources (computing, networking, and caching). Moreover, we propose a fog-enabled edge learning (FEL) framework for C-CCN in 5G, which can aggregate the idle computing resources of the neighbouring edge devices into virtual fogs to afford the heavy delay-sensitive learning tasks. By leveraging artificial intelligence (AI) to jointly processing sensed environmental data, dealing with the massive content statistics, and enforcing the mobility control at network edges, the FEL makes it possible for mobile users to cognitively share their data over the C-CCN in 5G. To validate the feasibility of proposed framework, we design two FEL-advanced cognitive services for C-CCN in 5G: 1) personalized network acceleration, 2) enhanced mobility management. Simultaneously, we present the simulations to show the FEL's efficiency on serving for the mobile users' delay-sensitive content retrieval and distribution in 5G.Comment: Submitted to IEEE Communications Magzine, under review, Feb. 09, 201
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