الفهرس 
AbstractOnly 14 pages are availabe for public view
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Abstract
The smart city concept integrates information and communication technology (ICT), and various physical devices connected to the network (the Internet of things or IoT) to optimize the efficiency of city operations and services and connect to citizens. The Smart City model typically integrates the economic, social and environmental components of the city in a way that sustainably maximizes the efficiency of the city’s primary systems .The Service Oriented Architecture (SOA) are used to integrate and manage the city services through a standard framework that has the capacity to develop, deploy and managed the functions that support the components of the city infrastructure.The objective of SOA implementation is to employ sophisticated IT processes that produce continuous, rapid business change outcomes. The aim is to present current research of the emergence of SOAs in light of the trends in urbanization along with the evolution of technology and ubiquitous computing.We will explore current trends in development and utilization of Service Oriented Architectures (SOAs) in Smart Cities and propose an SOA framework that will address the challenges of urban planning and development. We propose a personalized Ubiquitous Smart Learning framework that leverages Internet of Things, big data, supercomputing, and smart learning to provide enhanced development, management, and delivery of teaching and learning in smart cities. Advantages of the SOA if we used it for a Smart City Application can be described as the following: Integrate the physical infrastructures of the city such as the transportation sector, utilities, land, and city services, Flexibility, Scalability and Business agility, Easier Testing and Debugging, Reusability, Platform independence, Increased Productivity, SOA enables business decisions to be translated rapidly into technology The Parallel Particle Swarm Optimization (PPSO) algorithm described in is a population-based artificial intelligence mechanism, which is inspired by social behavior of a swarm of birds. PSO is a bio-inspired optimization technique that has been adapted to handle the continuous arrival of learners’ data from the learning analytics platform. It is an iterative algorithm. It employs swarms of particles, where every particle is responsible for tracking the fitness of each other particle. It results in an assessment that not only identifies the strengths and weakness of a learner but also provides feedback to learners and teachers a comparative analysis of growth of competences among learners.Learners could be clustered based on domain-specific competences or meta-competences or confidence measures. Each learner could belong to a number of clusters and new clusters emerge as data arrives continuously. One could also analyze the distance between clusters as a means to guide learners towards better performance. The education business around the world is experiencing real changes. Associations, for example, Courses are progressing new plans of action for education. Various real enterprises have dropped degrees from the employment prerequisites. While the financial aspects of advanced education organizations are under danger in a proceeding with miserable worldwide economy, computerized and long lasting students are progressively requesting new instructing and taking in ideal models from instructive establishments. There is an earnest need to change educating and learning scene with a specific end goal to drive worldwide monetary development. The utilization of separation learning what’s more, smart-Learning (STL) is on the ascent among advanced locals close by our development toward smart cities. The Smart Learning frameworks today do not have the essential refinement because of a few difficulties including information investigation and administration, student framework intelligence, framework cognizance, asset arranging, nimbleness, and adaptability. This thesis proposes a customized Ubiquitous smart Teaching and smart-Learning system that use Internet of Things, big data, supercomputing, and profound figuring out how to give improved advancement, administration, and conveyance of instructing and learning in smart society settings. A proof of idea is that framework has been created in light of the structure. A detailed gritty outline, execution, and assessment of the smart learning framework, including its five parts, are given utilizing 11 generally utilized datasets.