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Towards Energy and Resource Efficient Design for Scalable mMTC with A Distributed Energy-Restricted Cluster Based Transmission Scheme 16

Towards Energy and Resource Efficient Design for Scalable mM...

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16th IEEE international Wireless Communications and Mobile computing conference (IEEE IWCMC)

作者： Chen, Hua-Min Liu, Jiaxin Su, Haoru Lin, Shaofu Zhu, JingMing Chen, Limin Beijing Univ Technol Fac Informat Technol Beijing Peoples R China Beijing Univ Technol Beijing Inst Smart City Beijing Peoples R China Oval Operat Co Ltd Beijing Natl Speed Skating Beijing Peoples R China

ISBN: (纸本)9781728131290

Massive Machine Type Communication (mMTC) is one application scenario of 5G system to provide cellular Internet of Things (IoT) service. Some work is needed to provide efficient IoT service to meet the requirement of low power consumption and coverage extension, since IoT devices are mainly battery powered and installed in a coverage hole. Especially, the power consumption and radio resources are very essential when data packets are repeatedly transmitted to compensate the coverage gap. Considering the available energy in a real system is restricted, this paper proposes a distributed energy-restricted cluster based transmission scheme for mMTC/IoT data transmission, according to the geo-locations of IoT devices to optimize the transmission efficiency. The simulation results show that the proposed transmission scheme with a cluster size limitation can reduce the power consumption at IoT devices and improve the radio resource efficiency of the system, compared with the conventional centralized scheduling algorithm.

关键词： mMTC IoT distributed cluster based geo-location coverage loss power consumption radio resource efficiency energy restriction

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Bluetooth Tracking Approach for User Assistance Based in Sequential Patterns Analysis 2nd

Bluetooth Tracking Approach for User Assistance Based in Seq...

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2nd international conference on Human Systems Engineering and Design (IHSED) - Future Trends and Applications

作者： Velasco, Aitor Arribas McGrory, John Berry, Damon Technol Univ Dublin TU Dublin Sch Elect & Elect Engn Kevin St Dublin D08 NF82 8 Ireland

ISBN: (纸本)9783030279288;9783030279271

As a civilization, we are drowning in a raging torrent of data, of our own making, that is being harvested by our collective technologies and systems (e.g. Fitbit, phones). However, data itself is of no utility unless it is converted into beneficial knowledge. Design patterns have been shown to be a pragmatic solution to control and manage information flows and provide order and meaning to data within a given context. Assisting users within their daily activities has become a key aspect for modern Artificial Intelligence Systems. Nevertheless, although the GPS technologies work well for outside location, indoor positioning is still problematic, while is a vital awareness component in ambient assistance. This paper shows a preliminary Bluetooth tracking system with a focus on the user's transition between areas of interest. Our work aims to shed light on how the term design patterns can be applied for studying human behavior patterns in the smart environment.

关键词： Bluetooth Low Energy Design patterns smart environments Presence detection

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QR Code-based Efficient Entry Method for intelligent Files of Internet of Things 4th

QR Code-based Efficient Entry Method for Intelligent Files o...

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4th EAI international conference on smart Grid and Internet of Things, SGIoT 2020

作者： Genwang, Wang School of Electronic and Information Engineering Beijing Jiaotong University Beijing China Key Laboratory of Communication and Information Systems Beijing Municipal Commission of Education Beijing China

ISBN: (纸本)9783030695132

In recent years, with the development and application of technologies such as the Internet of Things, cloud computing, and big data, file management, the originally complicated task, has become more intelligent and flexible. However, when recording files, the existing technology still uses the method of scanning one file at a time. Therefore, when massive file information needs to be recorded at the same time, additional time cost or equipment cost will be incurred. In order to shorten the time of file entry as much as possible and reduce unnecessary equipment costs, we propose to mark the key information of files with the QR code technology in the Internet of Things, and then design a special image segmentation method according to the characteristics of the file bag or file box. Thus, the segmentation and extraction of different archive information within the visual range of the input device can be realized, and the effect of simultaneously inputting multiple archive information can be achieved. The experimental results show that in an ideal situation, our method can input the information of 20 files at one time, which greatly improves the efficiency of file entry. It is expected that if this method is applied to the current file management system, it can solve the problem of time consuming and energy consuming, and realize a more intelligent file management system at the same time. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Internet of things

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Research on big data storage and compression method for dual core intelligent meter 2

Research on big data storage and compression method for dual...

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2020 2nd international conference on Electronic Engineering and Informatics, EEI 2020

作者： Ming, Wei Xiang, You Feng Qiang, Wang Xiao Feng, Shen Department of Electronic Information Applied Technology College of Soochow University Suzhou China Institute of Technology Applied Technology College of Soochow University Suzhou China

With the rapid integration and development of cloud computing, big data and smart grid, not only the type and accuracy requirements of the collected data are increasing, but also the storage depth is getting higher and higher. In hardware, the dual port RAM design is used to improve the real-time performance of reading and writing, digital filter is used for preprocessing in software, and "Equivalent Normalization (EN)"is used to improve storage depth. These schemes save hardware storage space and improve data transmission efficiency in practical application. So the advantages of dual-core intelligent power meter will be further exploited and brought into play. © Published under licence by IOP Publishing Ltd.

关键词： Big data

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Challenges of Big data Visualization in Internet-of-Things Environments 2nd

Challenges of Big Data Visualization in Internet-of-Things E...

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2nd international conference on Innovative computing and Communication, ICICC 2019

作者： Eldin, Doaa Mohey Hassanien, Aboul Ella Hassanien, Ehab E. Information Systems Department Faculty of Computers and Artificial Intelligence Cairo Egypt Information Technology Department Faculty of Computers and Artificial Intelligence Cairo Egypt

ISBN: (纸本)9789811512858

Big data infers in all processes in our life. But the analysis process of huge data is not enough, the human brain heads for detecting a pattern more efficiently when data is performed visually. data visualization and data analytics play a significant role in decision making in various sectors. It also opens new opportunities for the ideas for big data visualization domain. An essential challenge in data visualization is a huge amount of data in real time or in static form. This paper discusses the importance of data visualization. This paper illustrates the impact of big data on data visualization. It focuses on the explanation of the essential challenges of big data visualization in the real-time stream. © 2020, Springer Nature Singapore Pte Ltd.

关键词： data visualization

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Efficiency Optimization in Supply Chain Using RFID Technology 18

Efficiency Optimization in Supply Chain Using RFID Technolog...

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18th IEEE international conference on Pervasive intelligent and computing (PICom)

作者： Abdullah Stroulia, Eleni Nawaz, Faiza Univ Alberta Comp Sci Edmonton AB Canada

ISBN: (纸本)9781728166094

Radio-frequency identification (RFID) has been a very crucial element when it comes to the Internet of Things (IoT). Its low cost, small form factor, and multiple items tracking make it suitable to use in smart Supply Chain Management (SSCM). There are many limitations of traditional Supply Chain Management (SCM) such as decentralized control, slow process, a lot of manual bookkeeping, unpredictable supplies which can lead to uncertain prices and deliveries. This paper discusses how SSCM can help overcome these drawbacks, by investigating four different scenarios of SSCM where RFID plays a major role. The frameworks discussed here try to solve some parts of the SSCM and give a brief idea about how they can be incorporated into the whole process. In addition to examining different approaches, a combined framework is proposed at the end. This proposal reflects the best characteristics that can demonstrate the versatility of RFID for tracking products, inventory management, and security aspects in SSCM.

关键词： IoT smart Supply Chain Management RFID Blockchain

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9th EAI international conference on Cloud computing, CloudComp 2019 and the 4th EAI international conference on smart Grid and Innovative Frontiers in Telecommunications, smartGIFT 2019

9th EAI International Conference on Cloud Computing, CloudCo...

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9th EAI international conference on Cloud computing, CloudComp 2019 and the 4th EAI international conference on smart Grid and Innovative Frontiers in Telecommunications, smartGIFT 2019

ISBN: (纸本)9783030485122

The proceedings contain 55 papers. The special focus in this conference is on Cloud computing. The topics include: Rendering of Three-Dimensional Cloud Based on Cloud computing;distributed Stochastic Alternating Direction Method of Multipliers for Big data Classification;personalized Recommendation Algorithm Considering Time Sensitivity;cloud-Based Master data Platform for smart Manufacturing Process;a Semi-supervised Classification Method for Hyperspectral Images by Triple Classifiers with data Editing and Deep Learning;A Survey of Image Super Resolution Based on CNN;design and Development of an intelligent Semantic Recommendation System for Websites;a Lightweight Neural Network Combining Dilated Convolution and Depthwise Separable Convolution;resource Allocation Algorithms of Vehicle Networks with Stackelberg Game;research on Coordination Control Theory of Greenhouse Cluster Based on Cloud computing;a Multi-objective Computation Offloading Method in Multi-cloudlet Environment;anomalous Taxi Route Detection System Based on Cloud Services;collaborative Recommendation Method Based on Knowledge Graph for Cloud Services;efficient Multi-user Computation Scheduling Strategy Based on Clustering for Mobile-Edge computing;Grazing Trajectory Statistics and Visualization Platform Based on Cloud GIS;Cloud-Based AGV Control System;a Parallel Drone Image Mosaic Method Based on Apache Spark;cycleSafe: Safe Route Planning for Urban Cyclists;prediction of Future Appearances via Convolutional Recurrent Neural Networks Based on Image Time Series in Cloud computing;video Knowledge Discovery Based on Convolutional Neural Network;time-Varying Water Quality Analysis with Semantical Mining Technology;a Survey of QoS Optimization and Energy Saving in Cloud, Edge and IoT;data-Driven Fast Real-Time Flood Forecasting Model for Processing Concept Drift;intelligent System Security Event Description Method.

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Application and challenges of Blockchain technology for real-time operation in a water distribution system 24

Application and challenges of Blockchain technology for real...

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24th international conference on System Theory, Control and computing (ICSTCC)

作者： Pahontu, Bogdan Arsene, Diana Predescu, Alexandru Mocanu, Mariana Univ Politehn Bucuresti Automat Control & Comp Bucharest Romania

ISBN: (数字)9781728198095

ISBN: (纸本)9781728198095

The demand for water continues to increase day by day and therefore measures must be established to be able to manage water resources more efficiently. Recently, various intelligent systems have been developed with the common goal of ensuring efficient water management and integrating modern technologies such as Internet of Things, Blockchain, Decision Support Systems and Artificial Intelligence. Nowadays, technological advancements allow collecting, processing and analyzing data from water distribution networks to optimize resources and improve decision making for all parties involved. This article presents a complex architecture, in the form of an integrated platform for real-time control and monitoring for residential networks, with secure data management based on Blockchain technology. A Blockchain network based on Hyperledger Fabric was developed in order to evaluate the possibilities of storing the real-time data into a distributed ledger.

关键词： Water Distribution System Blockchain Hyperledger IoT smart Meters Decision Support System

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Safety production process hazard situation analysis system based on large-scale data real-time processing 20

Safety production process hazard situation analysis system b...

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3rd international conference on Software Engineering and Information Management, ICSIM 2020 - and its Workshop 2020 the 3rd international conference on Big data and smart computing, ICBDSC 2020

作者： Du, Wenchi Zhang, Niansong Aimin, Wang Nanjing University of Science and Technology 200 Xiaolingwei Street Nanjing Jiangsu Province China Beijing Institute of Technology No. 5 Zhongguancun South Street Haidian District Beijing China

ISBN: (纸本)9781450376907

In order to give full play to the effects of big data in production safety monitoring and to meet the purpose of upgrading the safety management of enterprises, reducing personnel and increasing efficiency, this paper designs and implements a dangerous situation analysis system for production safety based on real-time processing of large-scale data. The platform adopts a layered architecture design method, and is constructed based on security parameter monitoring and monitoring technology, large-scale real-time data processing technology, dangerous situation assessment system, knowledge base, and SPC process analysis and early warning technology. The platform mainly covers three types of data source systems: People, things, and environment. It has basic information management, dynamic monitoring, big data analysis, and intelligent early warning. The results show that the platform can collect and share a large amount of data on safe production, summarize the rules of accidents through a big data analysis model, and finally achieve fine management of the safety of dangerous goods production. © 2020 Association for computing Machinery.

关键词： Big data

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Predictive analytics on open big data for supporting smart transportation services 24

Predictive analytics on open big data for supporting smart t...

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24th KES international conference on Knowledge-Based and intelligent Information and Engineering Systems, KES 2020

作者： Balbin, Paul Patrick F. Barker, Jackson C.R. Leung, Carson K. Tran, Marvin Wall, Riley P. Cuzzocrea, Alfredo University of Manitoba WinnipegMB Canada University of Calabria Rende Italy

In the current era of big data, huge quantities of valuable data, which may be of different levels of veracity, are being generated at a rapid rate. Embedded into these big data are implicit, previously unknown and potentially useful information and valuable knowledge that can be discovered by data science solutions, which apply techniques like data mining. There has been a trend that more and more collections of these big data have been made openly available in science, government and non-profit organizations so that people could collaboratively study and analysis these open big data. In this article, we focus on open big data for public transit because public transit (e.g., bus) as a means of transportation is a vital part of many people's lives. As time is a precious resource, bus delays could negatively affect commuters' plans. Unfortunately, they are inevitable. Hence, many existing works focused on predicting bus delays. However, predicting on-time or early buses is also important. For instance, commuters who come to a bus stop on time may still miss their buses if the buses leave early. So, in this article, we examine open big data about bus performance (e.g., early, on-time, and late stops). We analyze the data with frequent pattern mining and make predictions with decision-tree based classification. For illustration, we perform predictive analytics on real-life open big data available on Winnipeg Open data Portal, about bus performance from Winnipeg Transit. It shows the benefits of predictive analytics on open big data for supporting smart transportation services. © 2020 The Authors. Published by Elsevier B.V.

关键词： Predictive analytics

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