87,503 research outputs found

    Building an intelligent edge environment to provide essential services in smart cities

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    Smart Cities will cause major societal change because they will provide a comprehensive set of key services including seamless communication, intelligent transport systems, advanced healthcare platforms, urban and infrastructure management, and digital services for local and regional government. Thus, a new service and networking environment which will provide low latency and sustainable high bandwidth is needed to build new applications and services for smart cities. In this system services will be managed from the edge of the Internet and not from the centre as they currently are. This represents a new computing paradigm which is called the Intelligent Edge Environment. This paper looks at how to build this new ecosystem. Firstly, a new framework which comprises seven layers is unveiled, showing the functions that must be supported to realise this brave new world. New mechanisms are then introduced and a small prototype is developed to support storage in highly mobile environments. The results show that this approach could be used to build smart city digital platforms. The paper ends by discussing the development of a Distributed Operating System for smart cities

    Service-Oriented Reference Architecture for Smart Cities

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    The trend towards turning existing cities into smart cities is growing. Facilitated by advances in computing such as Cloud services and Internet of Things (IoT), smart cities propose to bring integrated, autonomous systems together to improve quality of life for their inhabitants. Systems such as autonomous vehicles, smart grids and intelligent traffic management are in the initial stages of development. However, as of yet there, is no holistic architecture on which to integrate these systems into a smart city. Additionally, the existing systems and infrastructure of cities is extensive and critical to their operation. We cannot simply replace these systems with smarter versions, instead the system intelligence must augment the existing systems. In this paper we propose a service oriented reference architecture for smart cities which can tackle these problems and identify some related open research questions. The abstract architecture encapsulates the way in which different aspects of the service oriented approach span through the layers of existing city infrastructure. Additionally, the extensible provision of services by individual systems allows for the organic growth of the smart city as required

    Exploring Success Factor for Mobile based Smart Regency Service using TRUTAUT Model Approach

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    Currently, almost every country struggles to apply city management to the concept of intelligent cities. Several previous studies have modeled the success, maturity, and success of information systems to use smart city principles. However, there are significant differences between city and district definition in terms of governance frameworks, regional size, livelihood differences, population, socio-economic, and socio-cultural dimensions. Therefore, work on the Smart District IT assessment requires new and unique studies that can differ substantially from smart cities. This study aims to explore the determinants of the success of Smart Regency services with mobile technology. The model and approach are the TRUTAUT model, which combines the concepts for the TRI and the UTAUT model. Two hundred eighty-nine participants could collect data with a smart cellular district service system - data processing using the SmartPLS v.3.2.8 software. Recent findings indicate that the variables proposed in the TRUTAUT model are a positive and essential relation. This study helps to determine the success of the application of intelligent mobile regional services applications. This study confirms that policymakers pay more considerable attention to critical questions that affect the district's smart cellular services' success

    Big Data in Smart-Cities: Current Research and Challenges

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    Smart-cities are an emerging paradigm containing heterogeneous network infrastructure, ubiquitous sensing devices, big-data processing and intelligent control systems. Their primary aim is to improve the quality of life of the citizens by providing intelligent services in a wide variety of aspects like transportation, healthcare, entertainment, environment, and energy. In order to provide such services, the role of big-data and its analysis is extremely important as it enables to obtain valuable insights into the large data generated by the smart-cities.  In this article, we investigate the state-of-art research efforts directed towards big-data analytics in a smart-city context. Specifically, first we present a big-data centric taxonomy for the smart-cities to bring forth a generic overview of the importance of big-data paradigm in a smart-city environment. This is followed by the presentation of a top-level snapshot of the commonly used big-data analytical platforms. Due to the heterogeneity of data being collected by the smart-cities, often with conflicting processing requirements, suitable analytical techniques depending upon the data type are also suggested. In addition to this, a generic four-tier big-data framework comprising of the sensing hub, storage hub, processing hub and application hub is also proposed that can be applied in any smart-city context. This is complemented by providing the common big-data applications in a smart-city and presentation of ten selected case studies of smart-cities across the globe. Finally, the open challenges are highlighted in order to give future research directions

    A Review on Internet of Things Solutions for Intelligent Energy Control in Buildings for Smart City Applications

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    A smart city exploits sustainable information and communication technologies to improve the quality and the performance of urban services for citizens and government, while reducing resources consumption. Intelligent energy control in buildings is an important aspect in this. The Internet of Things can provide a solution. It aims to connect numerous heterogeneous devices through the internet, for which it needs a flexible layered architecture in which the things, the people and the cloud services are combined to facilitate an application task. Such flexible IoT hierarchical architecture model will be introduced in this paper with an overview of each key component for intelligent energy control in buildings for smart cities

    Towards a Generic Framework for Smart Cities

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    Cities are formidable drivers of economic, social and cultural development but face a rising multitude of challenges: urban sprawl, transportation problems and climate change to mention but a few. Evolving concepts such as smart cities, sustainable communities and low carbon cities have been employed to formulate initiatives to tackle these challenges. Smart cities appear to address efficiency in reducing time, cost, and energy in delivering services-smart transportation, intelligent buildings, and green infrastructure with a view to reaching low carbon city development and eventually sustainability. This article attempts to construct a general framework for smart cities. First, the overall smart city system is depicted. Second, the dynamics of urban sector drivers in smart and low carbon cities are elucidated. Third, the performance of smart cities is measured in relation to low carbon development. By applying the smart city framework to the cities of Vienna, London, New York and Tokyo, the model proved robust and flexible. The investigation is concluded with policies to realign city plan and development policies

    A Review on Internet of Things Solutions for Intelligent Energy Control in Buildings for Smart City Applications

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    © 2017 The Authors. A smart city exploits sustainable information and communication technologies to improve the quality and the performance of urban services for citizens and government, while reducing resources consumption. Intelligent energy control in buildings is an important aspect in this. The Internet of Things can provide a solution. It aims to connect numerous heterogeneous devices through the internet, for which it needs a flexible layered architecture where the things, the people and the cloud services are combined to facilitate an application task. Such flexible IoT hierarchical architecture model will be introduced in this paper with an overview of each key component for intelligent energy control in buildings for smart cities

    Intelligent Transportation System for Smart-Cities using Fuzzy Logic

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    According to United Nations population statistics 2017, the world population is 7.6 billion and is growing rapidily alomost 11 billion by end of 21 century with a 70% chance of continued growth, this rapid increasing population have created low standards of living in cities. Smart Cities are facing pressures associated with due innovations and globalization to improve their citizens life. Computational intelligence is the study of adaptive mechanism to facilitate intelligent behavior in changing and complex environments. Traffic congestion and monitoring has become one of the critical issues in big cities. The adaptive mechanism of computational intelligence in changing the behavior of complex environments of smart city is very effective. The developing framework and services for smart-city requires sound infrastructure, latest current technology adoption. A framework model with the integration of cloud-data, social network (SN) services that is collecting stream data with smart sensors in the context of smart cities is proposed. The adaptive mechanism of computational intelligence in changing thebehavior of complex environments of smart city is very effective. A radical framework that enables the analysis of big-data sets stemming from Social Networking (SN) sites. Smart cities understanding is a broad concept only city transportation sector is focused in this article. Fuzzy logic modeling techniques are used in many fields i.e. medical, engineering. business and computing related problems. To solve various traffic management issues in cities a detailed analysis of fuzzy logic system is proposed. This paper presents an analysis of the results achieved using Fuzzy Logic System (FLS) for smart cities. The results are verified using MATLAB Simulation

    Enhancing Security and Privacy on Smart City’s Collected Data: A Fog Computing Perspective

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    Smart cities use information and communication technologies to deliver services to their citizens. Use of ICT makes them to be more intelligent and efficient in usage of resources, resulting in cost and energy savings, improved service delivery and quality of life. Smart cities are expected to be the fundamental pillars of continued economic growth and improved services delivery. Smart City technology is having ability to constantly gather information about the city, sharing the data with people, devices and technologies or borrowing relevant data from elsewhere, for analysis to enable informed decision making. For instance internet of things has emerged as a technological driving force in real time service delivery in smart cities. These applications provide new abilities, enhancing monitoring, and provision of action oriented process on control and device management. Smart devices are a major source of big data in smart cities. With expected increase of billions of smart devices and sensors in smart city by the year 2020, more data will be generated which will reduce efficiency of cloud access, due to increased volume. Security and privacy of data is a challenge in smart city, negligence in data security and privacy can be amplified in folds resulting to faulty applications, services along with paralyzing the entire city through Denial of Service (DDoS) attack, Spear Phishing Attacksand Brute-Force Attacks among others.Fog computing FC is a new paradigm that is intended to extend cloud computing CC through deployment of processing and localized units into the network edge, enabling low latency, offering location awareness and latency sensitiveness. Homomorphism for encryption, authorization, authentication, and classification are performed on collected data in smart cities to improve security and privacy. In this paper assimilation and analysis, is performed with fog computing aspects of decentralization, different policies for datacenter transferstrategies being analyzed.Processing time, access time, request time, response time and cost analysis show system efficiency
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