10 research outputs found

    Delivering IoT Services in Smart Cities and Environmental Monitoring through Collective Awareness, Mobile Crowdsensing and Open Data

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    The Internet of Things (IoT) is the paradigm that allows us to interact with the real world by means of networking-enabled devices and convert physical phenomena into valuable digital knowledge. Such a rapidly evolving field leveraged the explosion of a number of technologies, standards and platforms. Consequently, different IoT ecosystems behave as closed islands and do not interoperate with each other, thus the potential of the number of connected objects in the world is far from being totally unleashed. Typically, research efforts in tackling such challenge tend to propose a new IoT platforms or standards, however, such solutions find obstacles in keeping up the pace at which the field is evolving. Our work is different, in that it originates from the following observation: in use cases that depend on common phenomena such as Smart Cities or environmental monitoring a lot of useful data for applications is already in place somewhere or devices capable of collecting such data are already deployed. For such scenarios, we propose and study the use of Collective Awareness Paradigms (CAP), which offload data collection to a crowd of participants. We bring three main contributions: we study the feasibility of using Open Data coming from heterogeneous sources, focusing particularly on crowdsourced and user-contributed data that has the drawback of being incomplete and we then propose a State-of-the-Art algorith that automatically classifies raw crowdsourced sensor data; we design a data collection framework that uses Mobile Crowdsensing (MCS) and puts the participants and the stakeholders in a coordinated interaction together with a distributed data collection algorithm that prevents the users from collecting too much or too less data; (3) we design a Service Oriented Architecture that constitutes a unique interface to the raw data collected through CAPs through their aggregation into ad-hoc services, moreover, we provide a prototype implementation

    A Survey on Mobile Crowdsensing Systems: Challenges, Solutions, and Opportunities

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    Mobile crowdsensing (MCS) has gained significant attention in recent years and has become an appealing paradigm for urban sensing. For data collection, MCS systems rely on contribution from mobile devices of a large number of participants or a crowd. Smartphones, tablets, and wearable devices are deployed widely and already equipped with a rich set of sensors, making them an excellent source of information. Mobility and intelligence of humans guarantee higher coverage and better context awareness if compared to traditional sensor networks. At the same time, individuals may be reluctant to share data for privacy concerns. For this reason, MCS frameworks are specifically designed to include incentive mechanisms and address privacy concerns. Despite the growing interest in the research community, MCS solutions need a deeper investigation and categorization on many aspects that span from sensing and communication to system management and data storage. In this paper, we take the research on MCS a step further by presenting a survey on existing works in the domain and propose a detailed taxonomy to shed light on the current landscape and classify applications, methodologies, and architectures. Our objective is not only to analyze and consolidate past research but also to outline potential future research directions and synergies with other research areas

    Edge Intelligence : Empowering Intelligence to the Edge of Network

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    Edge intelligence refers to a set of connected systems and devices for data collection, caching, processing, and analysis proximity to where data are captured based on artificial intelligence. Edge intelligence aims at enhancing data processing and protects the privacy and security of the data and users. Although recently emerged, spanning the period from 2011 to now, this field of research has shown explosive growth over the past five years. In this article, we present a thorough and comprehensive survey of the literature surrounding edge intelligence. We first identify four fundamental components of edge intelligence, i.e., edge caching, edge training, edge inference, and edge offloading based on theoretical and practical results pertaining to proposed and deployed systems. We then aim for a systematic classification of the state of the solutions by examining research results and observations for each of the four components and present a taxonomy that includes practical problems, adopted techniques, and application goals. For each category, we elaborate, compare, and analyze the literature from the perspectives of adopted techniques, objectives, performance, advantages and drawbacks, and so on. This article provides a comprehensive survey of edge intelligence and its application areas. In addition, we summarize the development of the emerging research fields and the current state of the art and discuss the important open issues and possible theoretical and technical directions.Peer reviewe

    Edge Intelligence : Empowering Intelligence to the Edge of Network

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    Edge intelligence refers to a set of connected systems and devices for data collection, caching, processing, and analysis proximity to where data are captured based on artificial intelligence. Edge intelligence aims at enhancing data processing and protects the privacy and security of the data and users. Although recently emerged, spanning the period from 2011 to now, this field of research has shown explosive growth over the past five years. In this article, we present a thorough and comprehensive survey of the literature surrounding edge intelligence. We first identify four fundamental components of edge intelligence, i.e., edge caching, edge training, edge inference, and edge offloading based on theoretical and practical results pertaining to proposed and deployed systems. We then aim for a systematic classification of the state of the solutions by examining research results and observations for each of the four components and present a taxonomy that includes practical problems, adopted techniques, and application goals. For each category, we elaborate, compare, and analyze the literature from the perspectives of adopted techniques, objectives, performance, advantages and drawbacks, and so on. This article provides a comprehensive survey of edge intelligence and its application areas. In addition, we summarize the development of the emerging research fields and the current state of the art and discuss the important open issues and possible theoretical and technical directions.Peer reviewe

    Air Force Institute of Technology Research Report 2018

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    This Research Report presents the FY18 research statistics and contributions of the Graduate School of Engineering and Management (EN) at AFIT. AFIT research interests and faculty expertise cover a broad spectrum of technical areas related to USAF needs, as reflected by the range of topics addressed in the faculty and student publications listed in this report. In most cases, the research work reported herein is directly sponsored by one or more USAF or DOD agencies. AFIT welcomes the opportunity to conduct research on additional topics of interest to the USAF, DOD, and other federal organizations when adequate manpower and financial resources are available and/or provided by a sponsor. In addition, AFIT provides research collaboration and technology transfer benefits to the public through Cooperative Research and Development Agreements (CRADAs). Interested individuals may discuss ideas for new research collaborations, potential CRADAs, or research proposals with individual faculty using the contact information in this document

    Bioinspired metaheuristic algorithms for global optimization

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    This paper presents concise comparison study of newly developed bioinspired algorithms for global optimization problems. Three different metaheuristic techniques, namely Accelerated Particle Swarm Optimization (APSO), Firefly Algorithm (FA), and Grey Wolf Optimizer (GWO) are investigated and implemented in Matlab environment. These methods are compared on four unimodal and multimodal nonlinear functions in order to find global optimum values. Computational results indicate that GWO outperforms other intelligent techniques, and that all aforementioned algorithms can be successfully used for optimization of continuous functions

    Experimental Evaluation of Growing and Pruning Hyper Basis Function Neural Networks Trained with Extended Information Filter

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    In this paper we test Extended Information Filter (EIF) for sequential training of Hyper Basis Function Neural Networks with growing and pruning ability (HBF-GP). The HBF neuron allows different scaling of input dimensions to provide better generalization property when dealing with complex nonlinear problems in engineering practice. The main intuition behind HBF is in generalization of Gaussian type of neuron that applies Mahalanobis-like distance as a distance metrics between input training sample and prototype vector. We exploit concept of neuronā€™s significance and allow growing and pruning of HBF neurons during sequential learning process. From engineerā€™s perspective, EIF is attractive for training of neural networks because it allows a designer to have scarce initial knowledge of the system/problem. Extensive experimental study shows that HBF neural network trained with EIF achieves same prediction error and compactness of network topology when compared to EKF, but without the need to know initial state uncertainty, which is its main advantage over EKF

    UMSL Bulletin 2020-2021

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    The 2020-2021 Bulletin and Course Catalog for the University of Missouri St. Louis.https://irl.umsl.edu/bulletin/1084/thumbnail.jp

    Toward an integrated smart sustainable urbanism framework in the historic centre of Baghdad. (Old Rusafa as a case study)

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    According to Batty ā€œDespite a century of effort, our understanding of how cities evolve is still woefully inadequateā€ (Batty, 2008). The form of the city has been changing as the complexity of its systems has increased. Its varied aspects and methods have included ICT, smart transport systems, and the Intelligent Community Forum (ICF) for example. In the pursuit of smart sustainable urban form in heritage cities such as Baghdad, the research will analyse the concept of ā€˜smart sustainable cityā€™, taking into account urban conservation, use, and reuse of historic places, buildings and cultural environments. The capital, Baghdad, is the largest city in Iraq. The population of Baghdad as of 2017 is approximately 8,000,000, making it the second largest city in the Arab world after Cairo, Egypt. There are four historic areas of the modern city of Baghdad: Rusafa, Karkh, Adhamiya and Kadhimiya. The area of Old Rusafa represents the main historic centre of Baghdad. Its unique urban fabric defines this area and is surrounded by modern urban pattern and by modern roads, which replaced its walls. Generally speaking, in most of the traditional areas in Baghdad city and especially the area of Old Rusafa, due to the lack of standard infrastructures, the deteriorating built environment and rundown houses, air pollution and a lack of modern facilities, the younger generation is abandoning these areas (Al-Akkam, 2012a). Nowadays, most residents are low-income families who cannot afford to live in better sectors with higher rent. Such problems have brought into focus the extent to which a smart and sustainable urban design framework can be able to provide appropriate solutions to regenerate the traditional urban fabric regarding urban form, land use, transportation, and create a new vision to deal with the social and economic processes. However, the significant features in the historic part of Baghdad such as narrow alleys, natural shading, the hierarchy between public and private space, mixed-use, human scale pattern, high density/low rise living, a walkable and zero carbon environment are providing an extraordinary base to implement smart and sustainable standards. Unfortunately, there is a tremendous amount of evidence of a decline in the social function of historic urban fabric and traditional Iraqi houses of Old Rusafa (Al-Akkam, 2013b). Thus, this research will illustrate how ICT and smart sustainable design might transform the historic urban environment in the traditional area of Rusafa to be both smart and sustainable. This research first offers a review of the process of urban transformation in the context of city change through utilising urban morphology to explain how Baghdad transformed from a geometric city to an organic form and then from a traditional city to the modern metropolis. Then it will assess the physical and social conditions of the old area of Rusafa as a case study by using quantitative and qualitative methods, which are both essential for evaluating the situation in the traditional urban fabric. The research then will present the criteria for smart and sustainable urban design processes, as its primary contribution, to propose a method to fill a gap related to the use of ā€˜Smart and Sustainable Cityā€™ in a historic environment and furthermore, to determine the positive and negative aspects (opportunities and constraints) to the historic centre of Baghdad. In the final stage, this research will produce a smart and sustainable urban design framework for Old Rusafa and will introduce some guidance for future development to highlight opportunities and control constraints. The results lead us to state that, the different demands of such an area (Old Rusafa) present unique challenges for which sustainability and digital techniques potentially provide new methods of regeneration. It also helps to find the positive and negative aspects that can serve as a platform to resolve the conflicting values of traditional urban form and modern design models. The findings of this research provide insights into the cases that urban designers, policy-makers, technology companies and governments should consider in devising regeneration solutions and endeavours dealing with historic cities, aiming to integrate traditional principles with contemporary needs and provide a new vision for rethinking the way cities are designed, built, and managed. The primary implications will be summarised in two outcomes, the implementation of smart and sustainable urban design in a historic environment and the degree of amenability of the historic centre (Old Rusafa) for smart and sustainable regeneration
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