scholarly journals Distributed Storage and Computing Technology in New Energy Real-time on-Board Data

2020 ◽  
Vol 750 ◽  
pp. 012232
Author(s):  
Yingzi Wang ◽  
Jue Hou ◽  
Sisi Chu
Keyword(s):  
Real Time ◽  
Distributed Storage ◽  
Computing Technology ◽  
New Energy

The Design of a Wavelet-Based Neural Network Adaptive Filter

2013 ◽  
Vol 860-863 ◽  
pp. 2791-2795
Author(s):  
Qian Xiao ◽  
Yu Shan Jiang ◽  
Ru Zheng Cui
Keyword(s):  
Neural Network ◽  
Wavelet Transform ◽  
Real Time ◽  
Adaptive Filter ◽  
Adaptive Algorithm ◽  
Distributed Storage ◽  
Hopfield Neural Network ◽  
Lms Algorithm ◽  
The Neural Network ◽  
Simulation Results

Aiming at the large calculation workload of adaptive algorithm in adaptive filter based on wavelet transform, affecting the filtering speed, a wavelet-based neural network adaptive filter is constructed in this paper. Since the neural network has the ability of distributed storage and fast self-evolution, use Hopfield neural network to implement adaptive filter LMS algorithm in this filter so as to improve the speed of operation. The simulation results prove that, the new filter can achieve rapid real-time denoising.

scholarly journals Real Time Electrical Energy Monitoring and Cost Benefit Analysis using Smart Meter

2020 ◽  
Vol 8 (6S) ◽  
pp. 156-160
Keyword(s):  
Real Time ◽  
Cost Benefit Analysis ◽  
Cost Benefit ◽  
Electrical Energy ◽  
Energy Resources ◽  
Energy Utilization ◽  
Daily Lives ◽  
New Energy ◽  
The Cost ◽  
User Friendly

Energy is an essential component in supporting people’s daily lives and is a significant economical element in development of the country. The eventual depletion of conventional energy resources and their harmful impacts on environment as well as the rising energy costs and the limitations of new energy resources and technologies have pushed efficient energy management to the top of the agenda. But how the energy utilization can be managed? A simple answer to this is viable and real time metering, which enables calculation of run time energy consumption and obtaining the real-time as well as cumulative cost. In this research an Innovative hardware and IoT based solution to this problem is availed that could provide live information related to consumption of electricity by various appliances. The methodology used in this research is mainly based on a hardware tool named Elite 440 which is a meter and provides the data about various electrical parameters. This data so obtained is made visible on the dashboard in a user friendly. The data so visible includes various parameters like voltage, current, power factor etc. Also the data so obtained on the dashboard gets updated in each five minutes and simultaneously the cost gets updated which makes it real time monitoring System.

A Novel Hash Chain-Based Data Availability Monitoring Method for Off-site Disaster Recovery Architecture

2021 ◽  
pp. 2150294
Author(s):  
Neng Huang ◽  
Junxing Zhu ◽  
Chaonian Guo ◽  
Shuhan Cheng ◽  
Xiaoyong Li
Keyword(s):  
Information Systems ◽  
Real Time ◽  
Data Center ◽  
Disaster Recovery ◽  
Distributed Storage ◽  
Data Availability ◽  
Data Consistency ◽  
Real Time Monitoring ◽  
The Real ◽  
Hash Chain

With the rapid development of mobile Internet, there is a higher demand for the real-time, reliability and availability of information systems and to prevent the possible systemic risks of information systems, various business consistency standards and regulatory guidelines have been published, such as Recovery Time Object (RTO) and Recovery Point Object (RPO). Some of the current related researches focus on the standards, methods, management tools and technical frameworks of business consistency, while others study the data consistency algorithms in the cases of large data, cloud computing and distributed storage. However, few researchers have studied on how to monitor the data consistency and RPO of production-disaster recovery, and what architecture and technology should be applied in the monitoring. Moreover, in some information systems, due to the complex structures and distributions of data, it is difficult for traditional methods to quickly detect and accurately locate the first error data. Besides, due to the separation of production data center (PDC) and disaster recovery data center (DRDC), it is difficult to calculate the data difference and RPO between the two centers. This paper first discusses the architecture of remote distributed DRDCs. The architecture can make the disaster recovery (DR) system always online and the data always readable, and support the real-time monitoring of data availability, consistency as well as other related indicators, in this way to make DRDC out-of-the-box in disasters. Second, inspired by blockchain, this paper proposes a method to realize real-time monitoring of data consistency and RTO by building hash chains for PDC and DRDC. Third, this paper evaluates the hash chain operations from the algorithm time complexity, the data consistency, and the validity of RPO monitoring algorithms and since DR system is actually a kind of distributed system, the proposed approach can also be applied to the data consistency detection and data difference monitoring in other distributed systems.

Trends and Technologies in Big Data Processing

2020 ◽  
pp. 17-42
Author(s):  
Amitava Choudhury ◽  
Kalpana Rangra
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Internet Of Things ◽  
Data Processing ◽  
Real Time ◽  
Computing Technology ◽  
Time Data ◽  
Big Data Processing ◽  
Real Time Data ◽  
Real Time Data Processing

Data type and amount in human society is growing at an amazing speed, which is caused by emerging new services such as cloud computing, internet of things, and location-based services. The era of big data has arrived. As data has been a fundamental resource, how to manage and utilize big data better has attracted much attention. Especially with the development of the internet of things, how to process a large amount of real-time data has become a great challenge in research and applications. Recently, cloud computing technology has attracted much attention to high performance, but how to use cloud computing technology for large-scale real-time data processing has not been studied. In this chapter, various big data processing techniques are discussed.

A CNC Equipment Distributed Monitoring System Based on Cloud Computing Technology

2014 ◽  
Vol 1022 ◽  
pp. 392-395 ◽  
Author(s):  
Rang Yong Zhang ◽  
Geng Ma ◽  
Guang He Cheng
Keyword(s):  
Cloud Computing ◽  
Real Time ◽  
Wireless Network ◽  
Monitoring System ◽  
Communication Technology ◽  
Wide Area ◽  
Distributed Monitoring ◽  
Real Time Monitoring ◽  
Computing Technology ◽  
Remote Diagnostics

CNC equipment distributed monitoring system based on cloud computing technology provides a sable and reliable remote real time monitoring system to monitoring a mount of CNC equipment distributed in a large wide area by wireless network and GPRS communication technology which can be used to remote diagnostics and improve service respond speed.

A New Energy Control System Using Real Time Expert Systems

1990 ◽  
Vol 23 (3) ◽  
pp. 381-386 ◽  
Author(s):  
S. Nakamura ◽  
M. Yoshino ◽  
T. Yamada ◽  
T. Goto ◽  
Y. Hanji
Keyword(s):  
Control System ◽  
Expert Systems ◽  
Real Time ◽  
Energy Control ◽  
New Energy

The Design and Development of the Mobile Terminal Based on MES

2014 ◽  
Vol 962-965 ◽  
pp. 2928-2931 ◽  
Author(s):  
Wang Lei
Keyword(s):  
Information System ◽  
Mobile Computing ◽  
Real Time ◽  
Manufacturing Industry ◽  
Production Management ◽  
Rapid Development ◽  
Developed Countries ◽  
Manufacturing Execution System ◽  
Computing Technology ◽  
Real Time System

Abstract.As a pillar industry of the national economy, manufacturing is the centralized embodiment of the international competitiveness. Manufacturing industry in china has developed quickly and gotten lots of achievements in recent years. Nevertheless, compared with the developed countries, we still have great gaps, such as the improper ratio of the light and heavy industry,the lacking ability of market research and technical innovation, especially the out-dated concept of management which hinder the development of the manufacturing industry in our country seriously. Nowadays, the most widely used real-time system of management in manufacturing is the Manufacturing Execution system(MES for short). MES is a kind of production management technology and real-time information system facing manufacturing workshop,also is the management information system facing the workshop between the management system at the top and the control system at the bottom. Mobile computing is a kind of new arisen technology at the basis of the rapid development of mobile communication, the Internet, database, distributed computing technology and so on. Mobile computing technology will make the computer or other information intelligent terminal equipments transfer data and share resources in wireless environment.

scholarly journals Adoption of Cloud-based E-Health Record through the Technology, Organization and Environment Perspective

2018 ◽  
Vol 7 (4.35) ◽  
pp. 609 ◽  
Author(s):  
Hidayah Sulaiman ◽  
Asma Magaireh ◽  
Rohaini Ramli
Keyword(s):  
Cloud Computing ◽  
Real Time ◽  
Data Access ◽  
Healthcare Setting ◽  
Easy Access ◽  
Management Support ◽  
Computing Technology ◽  
Time Data ◽  
Real Time Data ◽  
The Impact

With the ever increasing cost of investing in technological innovations and the amount of patient data to be processed on daily basis, healthcare organizations are in dire need for solutions that could provide easy access and better management of real time data with lower cost.  The emerging trend of organizations optimizing cost in investing less on physical hardware has brought about the use of cloud computing technology in various industries including healthcare.  The use of cloud computing technology has brought better efficiency in providing real time data access, bigger storage capacity and reduction of cost in terms of maintenance. Although numerous benefits have been publicized for organizations to adopt the technology, nevertheless the rate of adoption is still at is infancy. Hence, this study explores factors that may affect the adoption of cloud-based technology particularly within the healthcare context. A quantitative study was conducted through the distribution of survey in Jordanian healthcare facilities. The survey was conducted to gauge the understanding of cloud-based EHR concepts identified through literature and validate the factors that could potentially provide an impact towards the cloud-based EHR adoption. The theoretical underpinnings of Technology-Organization-Environment (TOE) were investigated in studying the impact towards the adoption of cloud-based EHR. Results indicate that Technology-Organization-Environment factors such as privacy, reliability, security, top management support, organizational readiness, competition and regulatory environment are critical factors towards the adoption of cloud technology within a healthcare setting.

scholarly journals Application of Big Data Fusion Based on Cloud Storage in Green Transportation: An Application of Healthcare

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Li Qin Hu ◽  
Amit Yadav ◽  
Asif Khan ◽  
Hong Liu ◽  
Amin Ul Haq
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Data Fusion ◽  
Real Time ◽  
Strong Support ◽  
Heterogeneous Data ◽  
Continuous Growth ◽  
New Energy ◽  
The Government ◽  
Vehicle Network

In the 21st century, transportation brought great convenience to people, but at the same time, automobile transportation is the major factor causing greenhouse gas emissions and climate change. Movements of the world towards green environments, there is hike in use and production of electric vehicles (energy vehicles). However, with the continuous growth in the number of energy vehicles, it is necessary for the government to provide strong support in the construction of charging piles. Real-time and effective management has become a practical problem for the relevant departments which needs to be solved. This paper uses the information research method to fuse the huge amount of heterogeneous data generated by the charging pile resultant to the new energy electric vehicle in the vehicle network and introduces cloud computing as its storage module to facilitate the storage and related expansion of the big data. This paper proposes a system scheme of heterogeneous data fusion based on cloud computing for the acquisition, storage, and fusion of heterogeneous data in the vehicle network. After testing the results, it shows that the system is stable and effective in practical application, which can meet the design requirements of the system. What is the significance of analyzing big data of charging point? Considering from the supply side, obtaining the user’s charging behaviour data is helpful to build a digital map of the charging pile of new energy vehicles, connect the service information between the vehicle enterprises and the charging pile enterprises, and provide the most comprehensive and effective real-time charging information covering the widest range of vehicles, which can solve many problems of information asymmetry in the current charging information service.

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