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Industry 4.0 Applications in Agriculture: Cyber-Physical Agricultural Systems (CPASs)

Industry 4.0 Applications in Agriculture: Cyber-Physical Agr...

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international conference on Advances in Mechanical Engineering, ICAME 2020

作者： Sharma, Rohit Parhi, Shreyanshu Shishodia, Anjali Mumbai India Mumbai India Mumbai India

ISBN: (纸本)9789811536380

The increase in the demand of agricultural food products that includes processed food, meat, dairy and fish will put the current food production and supply systems under pressure. The high demand for food resources needs high agricultural productivity. Industry 4.0 technologies such as cyber-physical systems (CPSs), Internet of Services (IoS), Internet of things (IoT), cloud computing (CC) and big data promise huge potential in the field of agricultural supply chains through digitalization. This article proposes a framework for cyber-physical agricultural systems (CPASs) which is an intelligent integration of CPS, IoT, CC and big data with agricultural systems. CPAS can be applied in leveraging agricultural supply chains and boosting productivity. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Agricultural productivity Cyber-physical agricultural systems (CPASs) Cyber-smart farming systems Food security Industry 4.0

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A Risk Assessment Method of smart Grid in Cloud computing Environment Based on Game Theory 5

A Risk Assessment Method of Smart Grid in Cloud Computing En...

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5th IEEE international conference on Cloud computing and Big data analytics, ICCCBDA 2020

作者： Li, Qimeng Lv, Pengpeng Wang, Mengqiang Zhang, Zhizhi Wang, Shaoyin Fang, Pengbo Gao, Lifang State Grid Hebei Information Telecommunication Branch Shijiazhuang China State Grid Information Telecommunication Group Co. Beijing China

ISBN: (纸本)9781728160245

With the development of cloud computing technology, future smart Grid (SG) is expected to have efficient, reliable, secure and cost-effective power management. However, the use of emerging technologies such as virtualization makes existing SG networks face new threats, which have not been considered in traditional network environments. Therefore, in combination with the characteristics of cloud computing, conducting a reasonable and effective security risk assessment of cloud-based SG is of great significance for solving the security issues of SG. Aiming at the problem of constructing the security risk assessment of cloud-based SG, this paper proposes a security game assessment model based on dynamic games from the aspects of confidentiality, integrity and availability of the system using differential game models. The game process between security defense and malicious attackers in cloud-based SG is analyzed. By solving the equilibrium solution of the model, the optimal defense strategy of the SG is analyzed, and the security risk value of the system is obtained. The simulation showed that game model and framework proposed can make risk assessment of nodes more accurate and optimize the defense strategy. © 2020 IEEE.

关键词： Game theory

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3rd international conference on Advanced computing and intelligent Engineering, ICACIE 2018

3rd International Conference on Advanced Computing and Intel...

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3rd international conference on Advanced computing and intelligent Engineering, ICACIE 2018

ISBN: (纸本)9789811514821

The proceedings contain 54 papers. The special focus in this conference is on Advanced computing and intelligent Engineering. The topics include: Multi-verse Optimizer for Dynamic Stability Analysis Using STATCOM and Power System Stabilizer;Performance Analysis of a Coordinated PID- and UPFC-Based Stabilizer for Stability Improvement;design of Low Power Reduced Complexity Wallace Tree Multiplier Using Positive Feedback Adiabatic Logic;Low-Power 8-Bit Adiabatic Barrel Shifter for DSP Applications;high-Speed Loop Unrolled Grain Architecture in Reconfigurable Hardware;automated Red Lesion Detection: An Overview;enhanced Performance of Android Application Using RecyclerView;personalized Web Search;cooperative Game Theory-Based Request Distribution Model in Federated Cloud Environment;Current Control of a CHB Multilevel Inverter Using PR and Adaptive Fuzzy PI Controller: A Comparison;a Monarch Butterfly Optimization Approach to Dynamic Task Scheduling;automation of Traffic Violation Detection and Penalization;secure Big data Deduplication with Dynamic Ownership Management in Cloud computing;characterization of Range for smart Home Sensors Using Tsallis’ Entropy Framework;call data analytics Using Big data;lightweight, Scalable and Secure Middleware for Service-Centric Context-Aware Applications;security Issues in IoT and their Countermeasures in smart City Applications;an Efficient Approach for Running Multimedia Applications Using Mobile Cloud computing;a Comparative Study of Task Scheduling Algorithm in Cloud computing;offer Based Auction Mechanism for Virtual Machine Allocation in Cloud Environment;Pyramid Entropy Source for True Random Number Generator on FPGA;ioT-Based Cardiac Arrest Prediction Through Heart Variability Analysis;application of Group Mobility Model for Ad Hoc Network;vulnerability Analysis of Real-Time Operating Systems for Wireless Sensor Networks.

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On-Board Unit Big data: Short-term Traffic Forecasting in Urban Transportation Networks 7

On-Board Unit Big Data: Short-term Traffic Forecasting in Ur...

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7th IEEE international conference on data Science and Advanced analytics (DSAA)

作者： Buroni, Giovanni Le Borgne, Yann-Ael Bontempi, Gianluca Raimondi, Daniele Determe, Karl Univ Libre Bruxelles Machine Learning Grp Comp Sci Dept Brussels Belgium Katholieke Univ Leuven Dept Elect Engn ESAT Leuven Belgium Bruxelles Mobilite Brussels Belgium

ISBN: (纸本)9781728182063

Short-term traffic prediction in transportation network is a hot topic for next generation smart cities. Despite several research efforts, there is still a lack of consensus about the most effective way to predict traffic network-wide. Also, the majority of existing studies rely on either small data sets or limited portions of the transportation network. This paper presents the results of a forecasting study related to on-board units data of heavy-goods vehicles in the Brussels-Capital Region. The analysis, enabled by deployment of a big data infrastructure, concerns the short horizon (one hour ahead) forecasting of trucks flow (vehicles/hour) and mean speed (km/hour) over Brussels Capital Region's network. Both parametric and non-parametric (notably machine learning) models are designed and assessed along with different strategies (simple and linear forecasts combination, individual model selection). The paper shows the potential of large amounts of real-time data obtained from moving sensors where forecasting techniques are applied network-wide. In particular, simple combination schemes (notably the simple median combination forecasts) appear to outperform the other methods in terms of prediction accuracy.

关键词： intelligent transportation systems big data traffic forecasting

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An Overview of Recommender Systems in the Context of smart Cities 5

An Overview of Recommender Systems in the Context of Smart C...

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5th international conference on Cloud computing and Artificial Intelligence - Technologies and Applications (CloudTech)

作者： Madani, Rabie Ez-Zahout, Abderrahmane Idrissi, Abdellah Mohammed V Univ Comp Sci Dept Fac Sci Intelligent Proc & Secur Syst Team Rabat Morocco

ISBN: (纸本)9781728161754

The concept of smart city appeared following technological, societal and organizational changes. A smart city uses huge number of equipments connected to internet, to gather data and use it to effectively manage resources and enhance urban services quality. The use of Recommender Systems(RS) in smart cities plays take a leading part to guid citizens in the process of finding services that match with their preferences. Recommendations provided allow users to satisfy their needs in an efficient and easy way and make their daily lifes less complicated. This paper introduces an overview of Recommender Systems in smart Cities, also presents real-world application of RS in IoT and in smart Cities.

关键词： smart Cities Recommender Systems Internet of Things

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Diagnosis of chronic disease in a predictive model using machine learning algorithm

Diagnosis of chronic disease in a predictive model using mac...

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2020 international conference on smart Technologies in computing, Electrical and Electronics, ICSTCEE 2020

作者： Preethi, I. Dharmarajan, K. VISTAS School of Computing Sciences Chennai India VISTAS Department of Information Technology Chennai India

ISBN: (纸本)9781728172132

Today, digitization in healthcare industry takes the advantage on advancements in clinical healthcare services. The extensive growth in data for monitoring and analyzing the patients outcomes in predicting and diagnosis of chronic diseases lacks in traditional methods and are replaced by technologies to gather the most relevant insights from the medical data by using predictive analytics with very useful tool of machine learning. The importance of using machine learning algorithms in the model for diagnosis, shows its ability in high classification accuracy rate in reduced computational time. In this paper, a study of various machine learning techniques are used in classification of chronic diseases like heart, kidney, diabetes and cancer from multiple dataset by reducing the dimensionality using feature selection. Feature selection plays a significant role in machine learning by selecting the critical features for diagnosing chronic diseases. The performance of the classifiers are evaluated based on several metrics like classification accuracy, sensitivity, specificity, precision, F1- measure, AUC (the area under the receiver operating characteristic (ROC) curve) criterion, and processing time. © 2020 IEEE.

关键词： Predictive analytics

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smart agricultural big data preprocessing method based on adaptive compression algorithm

Smart agricultural big data preprocessing method based on ad...

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international conference on Applications and Techniques in Cyber Intelligence, ATCI 2020

作者： Zhang, Yijing Xian, Yue Zhang, Jie Jilin Agricultural Science and Technology University JilinJilin China

ISBN: (纸本)9783030539795

The application of agricultural Internet of Things technology is to install a variety of sensor parts and control actuators in the greenhouse, which compose the dropper system, temperature change system, humidification system and ventilation system, etc. The data transmission is completed through wireless network sensors to conduct real-time remote monitoring of crop environmental parameters. However, the network transmission of wireless sensor network is quite energy consuming, which easily leads to the premature death of nodes. The main purpose of this paper is to reduce the amount of data transmitted by wireless sensors to decrease the energy consumption of nodes, thus put forward smart agricultural big data preprocessing method based on adaptive compression algorithm. Firstly, the increase or decrease of sampling frequency is judged by calculating the average variation of collected data in a period of time in the historical data. Then, the optimal solution of sampling is searched by heuristic algorithm. By building a big data platform and adjusting the sampling frequency adaptatively, the purpose of reducing the amount of data in the processing process and not losing the information is achieved. This method can alleviate the burden of network and information processing system and reduce the time of data cleaning and prediction in later stage. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.

关键词： Heuristic algorithms

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intelligent city construction based on big data in the era of sustainable development

Intelligent city construction based on big data in the era o...

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1st international conference on Big data analytics for Cyber-Physical System in smart City, BDCPS 2019

作者： Chen, Lepeng Wang, Chengjiang College of Electricity and New Energy Three Gorges University YichangHubei443002 China

ISBN: (纸本)9789811525674

At present, with the rapid development of computer technology and related network technology as the symbol of the application of the era of big data, and combined with the strategy of sustainable development era, the concept of intelligent city emerges as the times require. From theory to practice, wisdom city has gradually won the attention of the world. Informatization, networking and technicalization will become the inevitable trend of intelligent City Construction Based on big data in the era of sustainable development. Taking the construction of intelligent city based on big data in the era of sustainable development as the research object, this paper starts with the introduction of the importance, significance and achievements of intelligent city, expounds the relationship between intelligent city and big data in the era of sustainable development, and studies the construction of intelligent city based on big data in the appropriate era of sustainable development. This paper tries to analyze the predicament and analysis of the construction model of intelligent City Based on big data in the era of sustainable development from the evaluation index system of intelligent city, and then tries to put forward the construction model and construction of intelligent City Based on big data in the era of sustainable development. Discussion measures. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Big data

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The application of blockchain technology in the early warning and monitoring of infectious diseases 5

The application of blockchain technology in the early warnin...

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5th international conference on intelligent Informatics and Biomedical Sciences (ICIIBMS)

作者： Tian Yu Yu Wan-jun Zhang Miao Zhang Min Tang Jun-yi Shanghai Inst Technol SIT Shanghai Peoples R China

ISBN: (纸本)9781728180229

In order to improve the efficiency of emergency management and decision-making and command of infectious diseases, infectious disease early warning technologies and systems can be used to monitor the trend of abnormal outbreaks and provide timely and accurate warnings. However, the current infectious disease early warning system still has problems such as insufficient intelligence, poor circulation of key information, and difficulty in distributed collaborative decision-making. Based on the blockchain distributed computing architecture, combined with emerging information technologies such as artificial intelligence, big data, and smart contracts, an infectious disease monitoring and early warning technology and its implementation framework are proposed. The technology can efficiently concentrate multi-party monitoring forces, flexibly integrate multiple early warning methods, build a knowledge integration and smart interconnected distributed collaborative monitoring environment under the premise of security and privacy protection, and use smart contracts as open, fair, software-defined monitoring The agent integrates decision-making, monitoring infectious diseases and automatic early warning in real time, so as to take into account the requirements of early warning accuracy and timeliness, and avoid isolated evidence and decision bias.

关键词： Blockchain smart contract artificial intelligence infectious disease monitoring distributed collaboration

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A Comprehensive Review on the Emerging IoT-Cloud based Technologies for smart Healthcare 6

A Comprehensive Review on the Emerging IoT-Cloud based Techn...

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6th international conference on Advanced computing and Communication Systems (ICACCS)

作者： Darcini, Vidya Priya S. Isravel, Deva Priya Silas, Salaja Karunya Inst Technol & Sci Dept Comp Sci & Engn Coimbatore Tamil Nadu India

ISBN: (纸本)9781728151977;9781728151960

Internet of Things (IoT) has redefined the operation of next-generation technologies by offering an intelligent framework. Cloud and IoT based system has been widely used in numerous applications for providing automated solutions and services. One of the areas in which the IoT and cloud have been widely used in the healthcare industry. To strengthen the healthcare system many initiatives are undertaken using advanced technologies such as IoT and cloud. So in this paper, a comprehensive review of the different IoT health model that are available are presented. The paper focuses on the various deployment strategies for building a cloud and IoT based system for smart home and smart hospital environment for handling different health-related issues. The paper highlights the various benefits that the IoT offers and also presents the challenges that are most prevalent in realizing the full automation of the healthcare system. The paper also discusses the integration of machine learning techniques for processing health data in the cloud to provide quality healthcare and modernize the healthcare system.

关键词： Cloud IoT Healthcare Machine Learning

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