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共 3243 条记录，以下是161-170 订阅

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Analysis of urban street microclimate data based on ENVI-met

Analysis of urban street microclimate data based on ENVI-met

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

作者： Mao, Ning School of Architecture and Urban Planning Shenzhen University Shenzhen518060 China

ISBN: (纸本)9789811525674

Microclimate is an important factor affecting the behavior and activities of people in cities. How to analyze the influencing factors of urban microclimate through data analysis and put forward the improvement strategy is an urgent problem to be solved under the background of intelligent city construction. In this paper, the microclimate data of four streets in Majialong Industrial area of Shenzhen are analyzed by using ENVI-met data simulation software, and based on several elements of street orientation, sky view faktor and plant, the improvement strategy of microclimate in urban streets is put forward. To achieve the purpose of guiding urban design, so as to promote the construction of smart city. © Springer Nature Singapore Pte Ltd. 2020.

关键词： smart city

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NFC Mobile intelligent Campus Construction of Nanjing University of Finance and Economics

NFC Mobile Intelligent Campus Construction of Nanjing Univer...

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Behavioral, Economic and Socio-cultural computing (BESC), 2015 international conference on

作者： Wang, Xiaoqing Liu, Ning Liu, Yan Sun, Yang Nanjing Univ Finance & Econ Nanjing Jiangsu Peoples R China China Telecom Corp Nanjing Branch Beijing Peoples R China

ISBN: (纸本)9781467387835

Influenced by the fusion of Internet Plus and education, Nanjing University of Finance and Economics launches the construction of "intelligent Campus" through the application of NFC smart Campus Card. Through reviewing the functions of NFC mobile phone smart campus card, the multiple application scenes on campus are demonstrated and the advantages are indicated as multi-function, optimized user experience, efficiency and reliability, which improve the campus life of students and enhance the campus management after the renovation project have been completed.

关键词： Internet Plus Application in High Education NFC Campus Application NFC Mobile Phone smart Campus Card Campus Card Renovation

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Hybrid security analysis based on intelligent adaptive learning in Big data

Hybrid security analysis based on intelligent adaptive learn...

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international conference on Advances in computing and Communication Engineering (ICACCE)

作者： Sasubilli, Satya Murthy Dubey, Ashutosh Kumar Kumar, Abhishek Huntington Columbus OH 43287 USA Chitkara Univ Inst Engn & Technol Kalujhinda HP India

ISBN: (数字)9781728163628

ISBN: (纸本)9781728163628

Big data provides a way to handle and analyze large amount of data or complex set. It provides a systematic extraction also. In this paper a hybrid security analysis based on intelligent adaptive learning in big data has been discussed with the current trends. This paper also explores the possibility of cloud computing collaboration with big data. The advantages along with the impact for the overall platform evaluation has been discussed with the traditional trends. It has been useful in the analysis and the exploration of future research. This discussion also covers the computational variability and the connotation in terms of data reliability, availability and management in big data with data security aspects.

关键词： Big data Adaptive learning intelligent analytics data security data management

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Generalized Dynamic Multilayer Fog computing Architecture 4th

Generalized Dynamic Multilayer Fog Computing Architecture

引用

4th international conference on Internet of Things and Connected Technologies (ICIoTCT)

作者： Arjun, K. P. Bhanu, S. Mary Saira Natl Inst Technol Tiruchirappalli 620015 Tamil Nadu India

ISBN: (纸本)9783030398750;9783030398743

The concept of smart city and smart Home is a promising and challenging one which defines the future of urban infrastructure development by integrating the Internet of Things (IoT) with Cloud computing. Fog computing with its latest framework on multilayering where each layer focuses on the different aspect of the architecture has proven useful in its goal to reduce space, time and computation overhead from cloud perspectives, due to its traffic offloading and edge device proximity for computation. But, a need for platform generalization and dynamic behavior still exists as most of the smart home needs to operate in multiple environments whereas the existing system mainly works on a rigid model with single infrastructure support. In this paper, a modified version of multilayer fog architecture has been proposed with scope for generalization and dynamic operation in terms of data management and placement. The proposed system consists of five sections - the Lower Fog Layer for end device collection operation and prioritization, Dockerized Middle Layer for node-specific operations like event detection and filtered data propagation, ICFN (Interconnecting Fog Node) Layer for interconnecting fog nodes, Cloud Server for data analytics and Fog Maintenance Remote Server for platform customization. The additional platform customization and multiple service support in the proposed architecture have also made significant improvements with regards to data distribution, request bandwidth, and request failure rate.

关键词： Multilayer fog computing Dockers and Containers Cloud computing data distribution Fog generalization Fog multi-service

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Proceedings of the 2024 international conference on Innovative computing, intelligent Communication and smart Electrical Systems, ICSES 2024

Proceedings of the 2024 International Conference on Innovati...

引用

2024 international conference on Innovative computing, intelligent Communication and smart Electrical Systems, ICSES 2024

ISBN: (纸本)9798331543617

The proceedings contain 396 papers. The topics discussed include: development of an IoT enabled smart children tracking and monitoring system using map location services;HMLM: an intelligent artificial intelligence assisted strategy to identify UPI frauds based on hybrid Markov learning methodology;data-driven insights into automotive customer complaints: a machine learning approach to predictive analytics;integrating predictive analytics and deep learning for vehicle safety incident forecasting;analyzing the health status of people in rural areas using machine learning algorithms;machine learning based approach using hand gestures for mouse and video control;experimental analysis of artificial intelligence powered adaptive learning methodology using enhanced deep learning principle;a comprehensive analysis of image processing methods for agricultural product quality control;and convolutional neural network-based multi-fruit classification and quality grading with a Gradio interface.

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Distributed-Reasoning for Task Scheduling through Distributed Internet of Things Controller

Distributed-Reasoning for Task Scheduling through Distribute...

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12th international conference on Ambient Systems, Networks and Technologies (ANT) / 4th international conference on Emerging data and Industry 4.0 (EDI40)

作者： Firouzi, Ramin Rahmani, Rahim Kanter, Theo Stockholm Univ Dept Comp & Syst Sci S-16407 Stockholm Sweden

The adoption of distributed reasoning through ubiquitous instrumentation in the distributed Internet of Things (IoT) leads to outstanding improvements in real-time monitoring, optimization, fault tolerance, traffic, healthcare, etc. Using a ubiquitous controller to interconnect devices in the IoT is still in the embryonic stage. However, it has the potential to create distributed-intelligent IoT solutions that are more efficient and secure than centric intelligence. It is essential to take a new direction to design a distributed intelligent controller for task scheduling that can firstly dynamically interact with a smart environment in efficient real-time data processing and secondly respond to flexible changes. To address these issues, we outline a two-level intelligence scheme that leverages edge computing to improve distributed IoT. The edge scheme shifts the capability of streaming processing from the cloud to edge devices to alleviate latency, support better reliable streaming analytics, and improve smart IoT applications' performance. In this work, to enable better, reliable, and flexible streaming analytics and overcome the data uncertainties, we proposed an IoT gateway controller that provides low-level intelligence by using a fuzzy abductive reasoner. Numerical simulations support the feasibility of our proposed approaches. (C) 2021 The Authors. Published by Elsevier B.V.

关键词： Internet of Things (IoT) edge computing reasoning fuzzy controller abductive reasoning

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Towards Security Monitoring for Cloud Analytic Applications 4

Towards Security Monitoring for Cloud Analytic Applications

引用

4th IEEE international conference on Big data Security on Cloud (BigdataSecurity) / 4th IEEE international conference on High Performance and smart computing (HPSC) / 3rd IEEE international conference on intelligent data and Security (IDS)

作者： Elsayed, Marwa Zulkernine, Mohammad Queens Univ Sch Comp Kingston ON K7L 2N8 Canada

ISBN: (纸本)9781538643990

Cloud computing is empowering new innovations for big data. At the heart, cloud analytic applications become the most-hyped revolution. Cloud analytic applications have remarkable benefits for big data processing, making it easy, fast, scalable and cost-effective;albeit, they pose many security risks. Security breaches due to malicious, vulnerable, or misconfigured analytic applications are considered the top security risks to big data. The risk is further expanded from the coupling of data analytics with the cloud. Effective security measures, delivered by cloud analytic providers, to detect such malicious and anomalous activities are still missing. This paper presents real-time security monitoring as a service (SMaaS). SMaaS is a novel framework that aims to detect security anomalies in cloud analytical applications running on Hadoop clusters. It aims to detect vulnerable, malicious, and misconfigured applications which violate data integrity and confidentiality. Towards achieving this goal, we are motivated by leveraging big data pipeline that mixes advanced software technologies (Apache NiFi, Hive, and Zeppelin) to automate the collection, management, analysis, and visualization of log data from multiple sources, making it cohesive and comprehensive for security inspection. SMaaS monitors a candidate application by collecting log data on real-time. Then, it leverages log data analysis to model the application's execution in terms of information flow. The information flow model is crucial for profiling processing activities conducted throughout the application's execution. Such model, in turn, enriches the detection of various types of security anomalies. We evaluate the detection effectiveness and performance efficiency of our framework. The experiments are conducted over benchmark applications. The evaluation results demonstrate that our system is a viable solution, yet very efficient. Our system does not make modification in the monitored cluster, nor does it

关键词： Big data security log analysis information flow control anomaly detection

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A Scalable and Composable analytics Platform for Distributed Wide-Area Tracking 20

A Scalable and Composable Analytics Platform for Distributed...

引用

20th international conference on Distributed computing and Networking (ICDCN)

作者： Khochare, Aakash Simmhan, Yogesh Indian Inst Sci Dept Computat & Data Sci Bangalore Karnataka India

ISBN: (纸本)9781450360944

smart cities are a manifestation of the Internet of Things (IoT). The push for smart cities has led to the proliferation of video cameras in public spaces [1]. London is expected to deploy 642,000 cameras by 2020. These cameras will be used primarily for surveillance of the city for urban safety. At the same time, such smart city deployments have also seen edge and fog computing paradigms gain preference over the cloud-only computing model [2]. This is due to the network proximity of the edge and fog devices to the data sources, offering lower latency access to data and lower bandwidth requirements to push high volume data, such as video streams, to the cloud. © 2019 Association for computing Machinery.

关键词： smart city

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IoT/CPS Ecosystem for Efficient Electricity Consumption Invited Paper 10

IoT/CPS Ecosystem for Efficient Electricity Consumption Invi...

引用

10th international Green and Sustainable computing conference (IGSC)

作者： Alharthi, Saad Johnson, Princy Alharthi, Mohammad Jose, Chacko Liverpool John Moores Uni Elect & Elect Engn Liverpool Merseyside England Saudi Elect Co Maintenance Dept Mecca Saudi Arabia

ISBN: (纸本)9781728154169

Modern society relies on smart systems like internet of things (IoT) and cyber physical systems (CPS) to monitor and control physical processes. The widespread deployment of IoT and CPSs result in fast growth of sensor data as physical processes are constantly monitored by billions of IP-enabled sensors (44 zettabytes by 2020). Hence, fog nodes are deployed to make network edge rich in computing resources to enable real-time data analytics using artificial intelligence/machine learning (AI/ML) for Big data generated from IoT and CPSs. This paper proposes IoT/CPS ecosystem for smart grid (SG) utilizing industry 4.0 concept to manage and control the loads using an intelligent predictive controller based on artificial neural network (ANN). The ANN is trained to predict the loads in certain districts based on previous smart meter readings installed at consumers and substations. This is a novel approach which integrates IoT/CPSs ecosystem into electric power system to deliver energy to consumers with high efficiency, reduce the cost, optimize the energy consumption, improve the reliability and enable real-time monitoring of power consumption.

关键词： CPS IoT fog nodes AI/ML SG fog computing industry 4.0. AGC LFC

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smart Manufacturing Through Sensor Based Efficiency Monitoring System (SBEMS) 8th

Smart Manufacturing Through Sensor Based Efficiency Monitori...

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8th international conference on Soft computing and Pattern Recognition (SoCPaR) / 8th international conference on Computational Aspects of Social Networks (CASoN)

作者： Balaji, V. Venkumar, P. Sabitha, M. S. Vijayalakshmi, S. Sre, R. M. Rathikaa ZF Elect TVS India Private Ltd Madurai Tamil Nadu India Kalasalingam Univ Krishnankoil India Bharathiar Univ R&D Ctr Coimbatore Tamil Nadu India Thiagarajar Coll Engn Madurai Tamil Nadu India Mepco Schlenk Engn Coll Sivakasi India

ISBN: (纸本)9783319606187;9783319606170

The emergence of IoT (Internet of Things) fuels an incipient generation of modern applications and enhancing effectiveness. smart manufacturing is the significant aspect to meet the innovation and competitiveness in the production environment. The application of IoT avails to increment the overall understanding in the factory through connected smart objects. This paper proposes an integrated solution of sensor affixed machines, data acquisition model and data analytics. The proposed system design and implementation is pertaining to a manufacturing company to monitor the efficiency of processes in each stage in the production environment. The focus is on monitoring and inferring insights on the efficiency of machines and operators in a cloud environment. Experimental evaluation shows a drastic amendment in the shop floor visibility area by integrating sensors for data acquisition and providing insights through the analytic tool.

关键词： data acquisition

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