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Construction of smart City Needed for a Better Life Under the Background of the Times—A Perspective of Holistic Governance Theory Based on Governance and the Structure of Local Political Institutions

Construction of Smart City Needed for a Better Life Under th...

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international conference on Machine Learning and Big data analytics for IoT Security and Privacy, SPIoT 2020

作者： Li, Dan Yang, Kexin Faculty of Management Wuhan Donghu University Wuhan China

ISBN: (纸本)9783030627454

What we face now is the contradiction between unbalanced and inadequate development and the people’s ever-growing needs for a better life. Technology changes life. smart cities have a important theoretical significance and practical value in meeting and satisfying people’s needs for a better life, improving the sense of gain, happiness and security. In view of this, the article harnesses the methods of literature, logic analysis, and field-participatory observation to follow the main line of "what, why, and what", and uses Perry Hicks’s theory of overall governance as a theoretical tool. It is proposed that smart cities are oriented to meet people’s differentiated needs, with responsibility, information and technology as the core elements, and integration and coordination as the operating path as the background, and proposed that the smart city construction should be in the analysis of the city PEST and SWOT, following the concept of smart law. they followed the concept of the smart rule in order to provide reproducible and generalizable theoretical experience and operation mode for the construction of smart cities. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： smart city

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Implementation of a System for Collecting and Analyzing Public and Open Access Information from Brazilian Federal Legislative Houses 1

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12th international conference on Soft computing and Pattern Recognition, SoCPaR 2020 and 16th international conference on Information Assurance and Security, IAS 2020

作者： Fernández, Iván José Mestre de Souza Mendes, Leonardo Universidade Estadual de Campinas UNICAMP Campinas SP13083-970 Brazil

ISBN: (数字)9783030736897

ISBN: (纸本)9783030736880

The overspread of corruption in today’s world is considered one of the major global problems, one that has affected almost every country in the world, developed or underdeveloped, throughout history. The specific case of institutionalized corruption, normally associated with the political structure of a country, is particularly heinous because it can be very difficult to expose and fight. In the case of Brazil, in recent years, major corruption scandals have arisen and completely shaken the national political environment. For centuries society was left defenseless in the face of such problems;however, supported by recent legislation on government compliance and transparency, the use of data Mining and data analytics can offer important tools for society in the combat of these old and condemned practices of corruption. This article presents the implementation of an information retrieval system using Web data Mining techniques, to collect information of public interest from politicians and political processes in Brazil, using public and open access information from the Brazilian federal legislative houses. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： data mining

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Hybrid Context-Aware Method for Quality Assessment of data Streams 18th

Hybrid Context-Aware Method for Quality Assessment of Data S...

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18th international conference on Service-Oriented computing (ICSOC)

作者： Mirzaie, Mostafa Ferdowsi Univ Mashhad FUM Mashhad Razavi Khorasan Iran

ISBN: (纸本)9783030763527;9783030763510

data quality is one of the most important issues that if not taken into consideration appropriately, results in the low reliability of the knowledge extracted through big data analytics. Furthermore, the challenges with data quality management are even greater with streaming data. Most of themethods introduced in the literature for processing streaming data do not use contextual information for the purpose of addressing data quality issues, however, it is possible to improve the performance of these methods by considering the contextual information, especially those obtained from the external resources. Based on this point of view, our main objective in this thesis is to propose a hybrid multivariate context-aware approach for data quality assessment in streaming environments, such as smart city applications.

关键词： data quality assessment Context awareness Streaming data

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A safe and intelligent knowledge graph construction model suitable for smart gridaper title 6

A safe and intelligent knowledge graph construction model su...

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6th international conference on Image, Vision and computing, ICIVC 2021

作者： Chen, Hao Chen, Lin Kuang, Xiaoyun Xu, Aidong Yang, Yiwei Shenzhen Power Supply Co. Ltd. Shenzhen China Electric Power Research Institute CSG Guangzhou China

ISBN: (纸本)9781665443685

With the increasing scale of power system, power grid data presents complex and changeable characteristics: knowledge structure is complex, isomerization knowledge is increasing;knowledge changes rapidly, and update frequency is gradually shortened. In this paper, a knowledge mapping technology is proposed, which is suitable for intelligent power grid. Based on the knowledge map of power grid, the possible application and future of knowledge map in power grid are imagined. © 2021 IEEE.

关键词： smart power grids

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Harnessing AI for Effective Distance Learning: Teachers’ Perspectives on COVID-19's Impact on Education

Harnessing AI for Effective Distance Learning: Teachers’ Pe...

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intelligent computing, Communication, Networking and Services (ICCNS), international conference on

作者： Firas Tayseer Ayasrah Khaleel Alarabi Jihan Yousef Aprilla Fortuna Dony Novaliendry Hanan Nassar Aljermawi College of Education Humanities and Science Al Ain University Al Ain UAE Faculty of Engineering Universitas Negeri Padang Padang Indonesia Pendidikan Teknik Informatika Universitas Negeri Padang Padang Indonesia Educational college Taibah University Saudi Arabia

ISBN: (数字)9798350354690

ISBN: (纸本)9798350354706

The COVID-19 epidemic has caused significant modifications to the education sector, especially concerning the implementation of distance learning as an online learning modality technique, providing substantial obstacles for students and educators throughout the globe. Within these changing surroundings, implementing artificial intelligence (AI) throughout online courses of study has emerged as an achievable strategy to enhance creativity and effectiveness. powered by artificial intelligence, chat tools provide smooth interaction among educators and students, and based on artificial intelligence, analytics enable vital information into the results of student learning and progress, which enables data-driven decisions to improve instructional methods. However, notwithstanding the possible positive effects of AI for distant learning, issues remain, especially the need for educators to get additional instruction and the requirement to address biases in AI techniques. Understanding teachers' perspectives is vital for efficiently incorporating AI into distant instructional settings. At the same time, ongoing investigation into AI's implications for classroom procedures and outcomes for learners remains essential for shaping the coming years of education. In light of these considerations, this study seems to be about educators' engagement with distance learning during COVID-19-induced closures of classrooms, demonstrating obstacles to utilizing online resources and emphasizing the importance of grasping students’ perspectives to refine educational strategies during digitization.

关键词： COVID-19 Computer aided instruction Pandemics Navigation Education Learning (artificial intelligence) Grasping Stakeholders Artificial intelligence smart phones

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Integrated smart Dam Control System Using Machine Learning

Integrated Smart Dam Control System Using Machine Learning

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Advancements in computing (ICAC), international conference on

作者： L. R. S. T. Lekamge N. P. T. D. Samaranayake N. V. Weerawarna D. M. J. C. B. Dissanayake H. M. S. C. Rathnayake Nelum Amarasena Department of Software Engineering Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (数字)9798331517878

ISBN: (纸本)9798331517885

Efficient management of dams and reservoirs is essential for optimizing water resources, preventing floods, and ensuring structural reliability of the dams. In Sri Lanka, manual dam operations introduce inefficiencies and potential risks. This study aims to develop an intelligent dam control system that integrates ML (Machine Learning) and IoT (Internet of Things) for dam gate automation, flood prevention, and dam crack analysis. The system automates sluice gate operations based on water demand predictions using LightGBM, enhances flood prevention through a pre-release strategy, and employs CNNs (Convolutional Neural Networks) for accurate crack detection in dam structures. Real-time data analytics, enabled by IoT sensors and cloud-based storage, enhance the system's scalability and reliability, allowing for more responsive and adaptive management. The results indicate significant improvements in water release scheduling, flood prevention accuracy, and crack analysis precision, demonstrating the practical viability of ML and IoT integration in dam safety. This data-driven, scalable approach provides a robust solution for optimized dam management, particularly suited to regions facing similar challenges where resources and oversight are limited.

关键词： Accuracy Dams Prevention and mitigation Machine learning Logic gates Control systems Sensors Floods Reliability Internet of Things

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Guest Editorial: Softwarized Networking for Next Generation Industrial Cyber-Physical Systems

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IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2021年第8期17卷 5506-5510页

作者： Garg, Sahil Wang, Honggang Granelli, Fabrizio Li, Hongwei Univ Quebec Ecole Technol Super Montreal PQ H3C 1K3 Canada Univ Massachusetts Dartmouth N Dartmouth MA 02747 USA Univ Trento I-38122 Trento Italy Univ Elect Sci & Technol China Chengdu 610054 Peoples R China

The papers in this special section focus on softwarized networking for next generation industrial cyber-physical systems (CPSs). With the emergence of embedded and ubiquitous cyberphysical applications, the rationale of blending the physical and the virtual worlds has become ever promising. These papers examine several topics that are recently concerned in the community, including the software defined architectures and implementations, advanced machine learning and data analytics solutions, blockchain-based network services and applications, network function allocation, dependable and trustable solutions, energy efficient networks and services, and other enabling technologies for integrating softwarized networks into CPSs.

关键词： Special issues and sections Cyber-physical systems Informatics data analysis Deep learning Resource management Industrial Internet of Things Computer architecture Blockchain Real-time systems Cloud computing

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HeuristiX: Adaptive Event Processing Using Lightweight Machine Learning Approaches on Edge Devices 26th

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26th annual international conference on Advanced computing and Communications, ADCOM 2020

作者： Mishra, Sanket Arawkar, Shubham Singh, Sashikant Shibu, Ankit Hota, Chittaranjan BITS Pilani Hyderabad Campus Telangana Hyderabad India Vellore Institute of Technology Andhra Pradesh Amaravati India

ISBN: (纸本)9789811900181

Recent times have witnessed a significant proliferation of cognitive applications in smart cities. Internet of things (IoT) is instrumental in gathering data that can be processed for creating intelligent scenarios. For developing such IoT applications, heterogeneous sensors can be deployed across various regions of a city to collect voluminous data. This data needs to be processed for predictions with minimum latency so as to formulate predictions in real time. In this paper, we present HeuristiX, a framework using lightweight machine learning solutions that can be deployed at edge devices. The work employs machine learning approaches to predict congestion events in a smart city scenario. By using Openwhisk, data is processed in minimum latency on resource-constrained devices for predicting congestion events in the city of Madrid. We augment the insights generated by models deployed on edge devices with a complex event processing engine, Apache Flink that is deployed on a server (cloud). The CEP forms complex events indicating congestion in specific areas across the city. We implement forecasting approaches and clustering approaches on IoT boards for processing traffic data for enriching the capabilities of Flink, i.e., prediction of future congestion events and generation of adaptive thresholds for CEP queries. Our proposed framework, HeuristiX, depicts that processing raw IoT at the edge is efficient as it minimizes latency and also provides a distributed setup for processing of data for better management of resources. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Edge computing

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A new energy aware task consolidation scheme for geospatial big data application in mist computing environment 8

A new energy aware task consolidation scheme for geospatial ...

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8th international conference on computing for Sustainable Global Development, INDIACom 2021

作者： Barik, Rabindra K. Patra, Sudhansu Shekhar Kumari, Priva Mohanty, Sachi Nandan Hamad, Abdulsattar Abdullah School of Computer Applications KIIT Deemed University Bhubaneswar India College of Engineering Pune Dept. of Computer Engineering Pune India College of Science Tikrit University Tikrit Iraq

ISBN: (纸本)9789380544434

The Internet of Spatial Things (IoST) are expanding rapidly for geospatial big data applications in today's digital world. A large volume of geospatial data is produced between IoST and the mist assisted cloud environment. Mist computing is a leveraging technology that stands extremely nearer to the edge of the network where geospatial big data are processing and then transferring to the cloud storage system via the fog nodes. By implementing this mist assisted cloud infrastructure, it has the greatest capabilities of reducing latency and traffic, respectively. Because of this unique model, it has a high requirement in smart geospatial healthcare applications, smart cities, geospatial location analytics and intelligent transportation system. Microcomputers are used at the mist layer in the mist assisted cloud network. Task allocation to the microcomputers in the mist servers is an NP-hard problem. The present research paper suggests a new energy aware task consolidation scheme by reducing the unused microcomputers in the mist layer of mist assisted cloud computing environment. It employs the metaphor-less Rao-1 algorithm and studies the behaviour of the algorithm with earlier evolutionary algorithms. It also reveals better performance in terms of maximizing CPU utilization. © 2021 Bharati Vidyapeeth, New Delhi. Copy Right in Bulk will be transferred to IEEE by Bharati Vidyapeeth.

关键词： Big data

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Accelerating the Deployment of observant Energy Efficient Lighting System for smart Cities

Accelerating the Deployment of observant Energy Efficient Li...

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data analytics for Business and Industry: Way Towards a Sustainable Economy (ICDABI), international conference on

作者： Vinay Kumar Mishra Mayank Singh Raj Gaurang Tiwari Ajay Kumar College of Computing Sciences and Information Technology Teerthanker Mahaveer University Moradabad India Teerthanker Mahaveer University Moradabad Uttar Pradesh India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (纸本)9781665490597

It is no secret that street lighting costs a city a lot of money in terms of energy. An intelligent street lighting system can reduce municipal street lighting expenses by 50 percent to 70 percent. As the name implies, intelligent street lighting systems automatically modify their light output based on usage and occupancy, such as pedestrians, cyclists, cars and trucks being the primary users of the road. In order to reduce energy consumption, an intelligent street light management recommends installing a wireless-based system that can remotely track and control the real energy usage of the street lights. Using an IR transmitter and IR receiver combination, we present a technique for energy conservation. When the sensor detects movement, it sends the data to the microcontroller, which then turns the Light ON/OFF as needed. To reduce energy wasting and to save lives from accidents, this research’s major goal is to prevent energy wastage.

关键词： Energy consumption Road accidents smart cities Transmitters Tracking Roads Energy conservation

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