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The Internet of Renewable Energy: Big data-Driven smart Grid Management with the Reliability and Security Analysis 1st

The Internet of Renewable Energy: Big Data-Driven Smart Grid...

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1st international and 4th National conference on Reliability and Safety Engineering, INCRS 2018

作者： Vaishnavi, P. Deenadayalan, V. Department of Computer Applications Anna University Chennai—BIT Campus Tiruchirappalli India Anna University Tiruchirapalli India

ISBN: (纸本)9789811537455

Renewable energy sources as the solar and wind power are transforming the energy landscape across the world, especially in India. As the government is planning to install 80 GW of solar power generation and 50 GW of wind power generation by 2020, we are presently in an era of increasing solar and wind power generation. The solar and wind energy, along with the associated sensor devices, generate huge amount of data that our traditional warehousing system is unable to store, manage and analyze smart grid, and big data technology provides an answer. Big data is a major research and development direction which provides data storage, retrieval, real-time processing, analytical modeling and visualization. In this paper, we propose the renewable energy architecture along with the integration of big data and power grid. This integration realizes high degree of network connectivity, along with complex security vulnerabilities into the grid. These security challenges, as well as reliability of the system in terms of privacy, integrity authentication and third-party protection have also been discussed in this paper. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Big data analytics computing (IoT) High performance Renewable energy

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Sequence Mining-Based Support Vector Machine with Decision Tree Approach for Efficient Time Series data Classification 3rd

Sequence Mining-Based Support Vector Machine with Decision T...

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international conference on data Management, analytics and Innovation (ICDMAI)

作者： Senthil, D. Suseendran, G. Vels Inst Sci Technol & Adv Studies VISTAS Dept Comp Sci Chennai Tamil Nadu India Vels Inst Sci Technol & Adv Studies VISTAS Dept Informat & Technol Sch Comp Sci Chennai Tamil Nadu India

ISBN: (纸本)9789811393648;9789811393631

The growing demand for an efficient approach to classify time series data is bringing forth numerous research efforts in data mining field. Popularly known applications like business, medical and meteorology and so on, typically involves majority of data type in the form of time series. Hence, it is crucial to identify and scope out the potential of time series data owing to its importance on understanding the past trend as well as predicting about what would occur in future. To efficiently analyze the time series data, a system design based on Sliding Window Technique-Improved Association Rule Mining (SWT-IARM) with Enhanced Support Vector Machine (ESVM) has been largely adopted in the recent past. However, it does not provide a high accuracy for larger size of the dataset along with huge number of attributes. To solve this problem the proposed system designed a Sequence Mining algorithm-based Support Vector Machine with Decision Tree algorithm (SM-SVM with DT) for efficient time series analysis. In this proposed work, the larger size of the dataset is considered along with huge number of attributes. The preprocessing is performed using Kalman filtering. The hybrid segmentation method is proposed by combining a clustering technique and Particle Swarm Optimization (PSO) algorithm. Based on the sequence mining algorithm, the rule discovery is performed to reduce the computational complexity prominently by extracting the most frequent and important rules. In order to provide better time series classification results, the Support Vector Machine with Decision Tree (SVM-DT) method is utilized. Finally, the Pattern matching-based modified Spearmen's rank correlation coefficient technique is introduced to provide more similarity and classification results for the given larger time series dataset accurately. The experimental results shows that the proposed system achieves better accuracy, time complexity and rule discovery compared with the existing system.

关键词： Classification Time series Hybrid segmentation Pattern matching Accuracy

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intelligent Navigation System for the Visually Impaired - A Deep Learning Approach 4

Intelligent Navigation System for the Visually Impaired - A ...

引用

4th international conference on computing Methodologies and Communication, ICCMC 2020

作者： Yadav, Deepak Kumar Mookherji, Somsankar Gomes, Joanne Patil, Siddhant St. Francis Institute of Technology Mumbai University Department of Information Technology India

ISBN: (纸本)9781728148892

Visually impaired individuals have been gradually claiming a significant stake in the population demographics. The proposed autonomous device aims to provide a holistic solution by engineering a smart navigation system that relentlessly scans the environment, detects and classifies neighboring objects using a 4 layered Convolutional Neural Network (CNN) that has been trained on a data set containing 2513 permutations of various images of household objects that an individual may encounter in daily life. The CNN follows the 80-20 rule for testing and training the self-learning model enabling it to learn recursively from the error rate. The proposed system then calculates distances of neighboring objects from the user and provides adaptive solutions in real time to manoeuvre the user to safety by providing auditory input in a simplistic manner which considers 10-24 frames per second while drafting the kinematic response for the user. The device has achieved an unprecedented success rate of serving within a response time of less than 50 ms. The accuracy of the CNN algorithm being at 94.6%, also sets a distinguished benchmark as an object detection algorithm thereby contributing to the success in simulations of the proposed device in a constrained environment. © 2020 IEEE.

关键词： intelligent systems

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A Study on Big data Processing Frameworks: Spark and Storm 3rd

A Study on Big Data Processing Frameworks: Spark and Storm

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3rd international conference on smart computing and Informatics (SCI)

作者： Deshai, N. Venkataramana, S. Sekhar, B. V. D. S. Srinivas, K. Varma, G. P. Saradhi JNTUK SRKR Engn Coll Dept Informat Technol Bhimavaram Andhra Pradesh India

ISBN: (纸本)9789813296909;9789813296893

Today's internet world impose a trade-off between Peta-byte to Exa-byte being created in digital computer world attributable enormous volume of unstructured datasets being generating from diverse social sites, IOT, Google, Twitter, Yahoo, monitoring surroundings through sensors, etc., is big data (BD). Because second to second doubles the datasets volume size but the shortage of smooth dynamic processing, analysis and scalability techniques. Because the recent high-speed decade we applied only extant methods and common tools about the gigabyte data process and perform computations on whole world huge data. Apache open free source Hadoop is the latest BD weapon can process zetta-byte dimensions of databases by its most developed and popular components as HDFS and map reduce (MR), to get done excellent storage features magnificent and reliable processing on zetta-byte of datasets. MR likes more famous software, popular framework for handling BD existing issues with full parallel, highly distributed, and most scalable manner. Despite, Hadoop, map and reduces tasks have more limitations like poor allocating custom resources, stream way processing, shortage of latency, the deficit of efficient performance, imperfection of optimization, the real-time trend of computations and diverse logical elucidation. We significant most modern progressive features computing procedures. This examination paper shows Apache fastest spark tool, world latest and fastest tool is apache storm has efficient frameworks to conquer those limitations.

关键词： Big data Hadoop Mapreduce Yarn Spark Storm

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Evaluation of smart health technologies with hesitant fuzzy MCDM methods

Evaluation of smart health technologies with hesitant fuzzy ...

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international conference on intelligent and Fuzzy Systems, INFUS 2019

作者： Mukul, Esin Güler, Merve Büyüközkan, Gülçin Industrial Engineering Department Galatasaray University Ortaköy Istanbul34349 Turkey

ISBN: (纸本)9783030237554

smart health is applied in many cities around the world as an approach that has a significant potential to solve the problems with smart technologies. smart health technologies provide effective healthcare services such as personalization of treatments through big data, robotics in cure and care, artificial intelligence support to doctors, etc. The mixed structure of the evaluation of smart health technologies involves many various and contradictory criteria. However, when information is in an uncertain nature, it is difficult to decide on and evaluate. Therefore, hesitant fuzzy linguistic term set (HFLTS) approach is applied to overcome the uncertainty of this multi-criteria decision-making (MCDM) problem. This approach can be used to facilitate experts’ decision-making processes in complex and uncertain situations. In this study, integrated hesitant fuzzy linguistic (HFL) MCDM approach is proposed to evaluate smart health technologies. The criteria are weighted with HFL Analytic Hierarchy Process (AHP), and then, smart health technologies are evaluated with the HFL Combinative Distance-based Assessment (CODAS) method. Lastly, the potential of this approach is presented through a case study. © 2020, Springer Nature Switzerland AG.

关键词： Health

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intelligent Energy Management System along with Solar-Wind Hybrid Power Source 10

Intelligent Energy Management System along with Solar-Wind H...

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10th international conference on Cloud computing, data Science and Engineering (Confluence)

作者： Upadhyay, Prabhat Kumar Kunhi, Nadia Mohamed Gupta, Yash Ahamed, Shaik Ishraq Das, Jidhin Birla Inst Technol Dept EEE Offshore Campus UAE Ras Al Khaymah U Arab Emirates

ISBN: (纸本)9781728127910

Energy management is a vast subject of major significance and complexity. It entails in electing among the integrated set of sources to generate electrical energy that supplies to a set of loads by diminishing losses and expenses. The utilization of sources and consumption rate of loads are coherent, well-integrated and magnitude of the system, the optimal usage of sources must be performed in real-time to avoid power outage. With an increase in demands, there is an increase in improved productivity, which causes a reduction in greenhouse emissions and energy costs that are motivations for organizations to capitalize and implement new energy efficiency technologies and management strategies. This work aims to propose a system which can self-regulate a combined set of power sources namely green energy i.e., Solar-Wind Hybrid System and main grid, and loads organized as a unified group of individual systems, called micro-grid, to augment several measures such as cost-effectiveness and energy efficiency. This prototype is based on the multi-agent automated systems. These micro-grids, individually modelled as a self-directed entity, can interact and make its own decision giving the best outcome.

关键词： Arduino Solar Panel Wind Turbine IR Sensor Charge Controller smart System

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Research on the Application of Artificial Intelligence in Energy Science and Engineering Monitoring Software Engineering Technology under the Background of Big data 5

Research on the Application of Artificial Intelligence in En...

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2019 5th international conference on Environmental Science and Material Application, ESMA 2019

作者： Liu, Hongying Department of Computer Science and Engineering Guangzhou College of Technology and Business Guangzhou China

Artificial intelligence belongs to the world's leading technology and technology, which can make people's work and life become more intelligent and faster. The arrival of the era of big data accelerates the development of artificial intelligence technology, and the artificial intelligence big data platform begins to appear. Through the analysis of the relationship between big data and artificial intelligence, the AI big data platform and its application are comprehensively discussed, aiming to promote the development of artificial intelligence big data platform and improve the overall level of domestic artificial intelligence. The smart grid is artificial. One of the important application areas of intelligence, the advancement and breakthrough of the new generation of artificial intelligence technology, which is mainly represented by advanced machine learning theory, big data and cloud computing, will promote the development of smart grid. Therefore, an energy science and engineering data monitoring software is needed to realize the monitoring and analysis and unified scheduling of energy science. The article details the design and implementation of data monitoring software for power and energy intelligence. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Big data

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intelligent Water Management System: smart Approach Towards Sustainability (smart Water) 4th

Intelligent Water Management System: Smart Approach Towards ...

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4th international conference and Exhibition on smart Grids and smart Cities, ISGW 2018

作者： Saluja, Mohit Project Management Group CBRE South Asia Pvt. Ltd GurgaonHaryana India

ISBN: (纸本)9789813291188

Whenever we address India, the Initial thought one can come up with is the population of this country which is going to surpass the China’s population in 2024 and is projected to touch 1.5 Billion;said by UN Official. It is anticipated that India will be the highest populous country along with the fastest growing economy in the world but despite of economic opportunity, India’s infrastructure is very crumbling. India’s immense population makes it terribly vulnerable once it involves water shortage and scarceness. Concerning 330 million individuals within the country currently suffer from regular water shortage problems. India’s economy is basically captivated with its agriculture. Water shortage and drought not solely impact on the agricultural districts but also have a calamitous effect on inflation and economic progress. With a mission to make India smart, it requires smart Minds who actively participate in governance and Promote smart Building Management Systems through Integration, Information and Innovation. Building the foundation of smart Water is the Need of the Hour and Even the Purpose of this Paper. Analyzing Water with data Base Management System and Internet of Things to Measure Operations and Financial Controls intelligently, Zero Percent Wastage, Improve Revenue and Efficiency by means of Advance Metering Infrastructure, Automatic Distribution, Leakage Management, Disaster and Emergency Preparedness, Pressure Regulation and smart Grid analytics. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Disasters

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Design of intelligent high-resolution remote sensing satellites based on new integrated electronic system 5

Design of intelligent high-resolution remote sensing satelli...

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IET international Radar conference 2020, IET IRC 2020

作者： Liu, Zhenxing Li, Chao Gao, Yuting Wang, Dongjin University of Science and Technology of China Hefei230027 China China Aerospace Science and Technology Beijing100048 China

ISBN: (纸本)9781839535635

As the brain of intelligent satellites, the on-board integrated electronic system is the core system in the overall design of smart satellites. Based on modular integrated electronic technology, this paper innovatively adopts system engineering methods to uniformly design the information processing, control and management procedures, hardware and software equipment of intelligent satellites to realize the sharing of information resource and the optimization of the entire satellite system, which takes the lead in the research area of intelligent satellites in China. The research content mainly includes hardware architecture design and software network architecture design of intelligence satellites. In terms of hardware architecture, creative ideas of modular and open structure design are adopted, and standardized interfaces are designed for on-board hardware, realizing efficient integration and plug-and-play of satellite hardware. As for the software network architecture, the hierarchical design is inventively adopted to facilitate the reuse of software resources;through the unified deployment of on-board computing resources, the ability of autonomous management of tasks and the autonomous processing of data is improved to facilitate rapid application. The overall ingenious design has the characteristics of openness, versatility and flexibility, and meets the application requirements of intelligent satellites. © 2020 Institution of Engineering and Technology. All rights reserved.

关键词： Network architecture

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3rd international conference on data Management, analytics and Innovation, ICDMAI 2019

3rd International Conference on Data Management, Analytics a...

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3rd international conference on data Management, analytics and Innovation, ICDMAI 2019

ISBN: (纸本)9789813299481

The proceedings contain 35 papers. The special focus in this conference is on data Management, analytics and Innovation. The topics include: Automated Scheduling of Hostel Room Allocation Using Genetic Algorithm;Evaluation of ASTER TIR data-Based Lithological Indices in Parts of Madhya Pradesh and Chhattisgarh State, India;Analyzing Linear Relationships of LST with NDVI and MNDISI Using Various Resolution Levels of Landsat 8 OLI and TIRS data;automatic Robot Processing Using Speech Recognition System;banking and FinTech (Financial Technology) Embraced with IoT Device;GRNN++: A Parallel and Distributed Version of GRNN Under Apache Spark for Big data Regression;an Entropy-Based Technique for conferences Ranking;MapReduce mRMR: Random Forests-Based Email Spam Classification in Distributed Environment;the Impact of Sustainable Development Report Disclosure on Tax Planning in Thailand;ASK Approach: A Pre-migration Approach for Legacy Application Migration to Cloud;clustering and Labeling Auction Fraud data;big data Security Challenges and Preventive Solutions;role and Challenges of Unstructured Big data in Healthcare;zip Zap data—A Framework for ‘Personal data Preservation’;a Systematic Mapping Study of Cloud Large-Scale Foundation—Big data, IoT, and Real-Time analytics;studies on Radar Imageries of Thundercloud by Image Processing Technique;PURAN: Word Prediction System for Punjabi Language News;Implementation of hDE-HTS Optimized T2FPID Controller in Solar-Thermal System;Design of Sigma-Delta Converter Using 65 nm CMOS Technology for Nerves Organization in Brain Machine Interface;Performance Comparison of Machine Learning Techniques for Epilepsy Classification and Detection in EEG Signal;novel Approach for Plant Disease Detection Based on Textural Feature Analysis.

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