An Interactive Real-Time SCADA Platform With Customizable Virtual Instruments for Cloud Control Systems

2018 ◽  
Vol 141 (4) ◽  
Author(s):  
Haoran Tan ◽  
Zhiwu Huang ◽  
Min Wu
Keyword(s):  
Real Time ◽  
Transmission Control Protocol ◽  
Data Communication ◽  
Virtual Instruments ◽  
Time Data ◽  
Online Simulation ◽  
Network Delays ◽  
Communication Scheme ◽  
Simulation And Experiment ◽  
Cloud Control System

This paper studies the design and implementation of an interactive real-time cloud supervisory control and data acquisition (SCADA) platform. The platform relying on C# and client/server architecture provides full support for data supervision of the cloud control system (CCS). Users are allowed to design supervisory interfaces by dynamically creating and customizing virtual instruments, which are seamlessly integrated into the platform by reconstructing it. Both the scalar and matrix data from different cloud nodes are supported for supervising simultaneously in real-time through receiving data asynchronously. The user can tune the parameters of the CCS online via duplex channels based on the transmission control protocol/internet protocol (IP). To overcome the disturbance of network delays to data display, a stable data and real-time data communication scheme are proposed. All the supervised data can be stored in separate files for further analysis. Finally, the online simulation and experiment are provided to demonstrate the feasibility of the designed SCADA platform.

scholarly journals Komunikasi Data Berbasis Protokol UDP pada Sistem Ubiquitous Mobile Sensing Kualitas Sumber Air

2016 ◽  
Vol 10 (2) ◽  
pp. 219
Author(s):  
Yuning Widiarti Darsono ◽  
Adianto Adianto ◽  
Mirna Apriani
Keyword(s):  
Water Quality ◽  
Real Time ◽  
Mobile Phones ◽  
Data Communication ◽  
Mobile Sensing ◽  
Time Data ◽  
Climate Change And Variability ◽  
Rapid Spread ◽  
Types Of Information ◽  
Water Quality Sensors

The need for monitoring, effective and efficient control and evaluation of water quality in regional waters Surabaya become a demand for population growth, climate change and variability in the current era of urbanization. The traditional method is done by collecting water samples, test and analyze water in the laboratory has been relatively expensive and do not have the ability to capture real-time data, analysis and information delivery fast in making decisions. On the other hand, the rapid spread in the use of mobile phones in developing countries has increased mobile data management applications. A variety of mobile applications has also increased in recent years. This is because mobile phones cheap, easy to use and can transmit multiple types of information including images and GPS data remotely. In this paper, the author describes a data communication system of  water quality resources based on UDP protocol. This system is called ubiquitous mobile sensing consisting of microcontroller Arduino, water quality sensors, and Android smartphones. It has the ability to detect temperature, dissolved oxygen (DO), pH and electrical conductivity (EC) in real time. By using this monitoring system, the data result is expected more accurate, faster and cheaper.

scholarly journals Fossel: Efficient Latency Reduction in Approximating Streaming Sensor Data

2020 ◽  
Vol 12 (23) ◽  
pp. 10175
Author(s):  
Fatima Abdullah ◽  
Limei Peng ◽  
Byungchul Tak
Keyword(s):  
Real Time ◽  
Data Analytics ◽  
Streaming Data ◽  
Sensor Data ◽  
Simple Type ◽  
Data Sampling ◽  
Time Data ◽  
Latency Reduction ◽  
Network Delays ◽  
Real Time Data

The volume of streaming sensor data from various environmental sensors continues to increase rapidly due to wider deployments of IoT devices at much greater scales than ever before. This, in turn, causes massive increase in the fog, cloud network traffic which leads to heavily delayed network operations. In streaming data analytics, the ability to obtain real time data insight is crucial for computational sustainability for many IoT enabled applications such as environmental monitors, pollution and climate surveillance, traffic control or even E-commerce applications. However, such network delays prevent us from achieving high quality real-time data analytics of environmental information. In order to address this challenge, we propose the Fog Sampling Node Selector (Fossel) technique that can significantly reduce the IoT network and processing delays by algorithmically selecting an optimal subset of fog nodes to perform the sensor data sampling. In addition, our technique performs a simple type of query executions within the fog nodes in order to further reduce the network delays by processing the data near the data producing devices. Our extensive evaluations show that Fossel technique outperforms the state-of-the-art in terms of latency reduction as well as in bandwidth consumption, network usage and energy consumption.

New Real-Time Data Communication System Enhances Coiled-Tubing Operations

2010 ◽  
Author(s):  
Michael John Taggart ◽  
Niall Atholl Murray ◽  
Trevor Sturgeon ◽  
William McNeil
Keyword(s):  
Real Time ◽  
Communication System ◽  
Data Communication ◽  
Time Data ◽  
Coiled Tubing ◽  
Real Time Data

scholarly journals Research on CarMaker and Cloud Computing Platform Co-Simulation Based on APO

2021 ◽  
Vol 2065 (1) ◽  
pp. 012020
Author(s):  
Nver Ren ◽  
Rong Jiang ◽  
Dongze Zhang
Keyword(s):  
Cloud Computing ◽  
Real Time ◽  
Data Communication ◽  
Autonomous Driving ◽  
Data Sampling ◽  
Cloud Platform ◽  
Time Data ◽  
Automated Driving ◽  
Computing Platform ◽  
Cloud Computing Platform

Abstract An cloud computing platform based on B/S architecture and docker container technology for autonomous driving simulation has been established in this paper. The map editor module of the cloud platform lets users design 3D scenes for simulating and testing automated driving systems. When the customized roadway scene for simulation created, it would be saved as OpenDrive format both for the server of cloud platform and CarMaker’s TestRun which all parameters of the virtual environment (vehicle, road, tires, etc.) are sufficiently defined. Then, based on the application online (APO) communication protocol of CarMaker, the local APO agent service was created. When the 27 parameters of vehicle dynamics received from CarMaker server, they were sent to the cloud platform in real time through UPD protocol. The process of data communication is completed by APO agent. Through the work above, a co-simulation between cloud platform and CarMaker could be successfully established for autonomous driving with seventeen-degree-of-freedom. Through the co-simulation experiment, it is found that the real-time data sampling frequency of the co-simulation is 70Hz, which completes the synchronous simulation of carmaker and cloud platform.

scholarly journals Design of smart agriculture based on big data and Internet of things

2020 ◽  
Vol 16 (5) ◽  
pp. 155014772091706 ◽  
Author(s):  
Chunling Li ◽  
Ben Niu
Keyword(s):  
Data Mining ◽  
Information Processing ◽  
Internet Of Things ◽  
Real Time ◽  
Data Communication ◽  
Large Data ◽  
Time Data ◽  
Real Time Data ◽  
Smart Agriculture ◽  
Internet Of Things Technology

With the wide application of Internet of things technology and era of large data in agriculture, smart agricultural design based on Internet of things technology can efficiently realize the function of real-time data communication and information processing and improve the development of smart agriculture. In the process of analyzing and processing a large amount of planting and environmental data, how to extract effective information from these massive agricultural data, that is, how to analyze and mine the needs of these large amounts of data, is a pressing problem to be solved. According to the needs of agricultural owners, this article studies and optimizes the data storage, data processing, and data mining of large data generated in the agricultural production process, and it uses the k-means algorithm based on the maximum distance to study the data mining. The crop growth curve is simulated and compared with improved K-means algorithm and the original k-means algorithm in the experimental analysis. The experimental results show that the improved K-means clustering method has an average reduction of 0.23 s in total time and an average increase of 7.67% in the F metric value. The algorithm in this article can realize the functions of real-time data communication and information processing more efficiently, and has a significant role in promoting agricultural informatization and improving the level of agricultural modernization.

Real-Time Communication Method over Switched Ethernet

2013 ◽  
Vol 411-414 ◽  
pp. 840-843
Author(s):  
A Li Mu Jiang Yiming ◽  
Re Zi Wan Maimaiti ◽  
Aisikaer Kadier
Keyword(s):  
Real Time ◽  
Data Communication ◽  
Network Protocol ◽  
Control Network ◽  
Time Data ◽  
Industrial Control ◽  
Switched Ethernet ◽  
Communication Method ◽  
Real Time Data ◽  
Real Time Applications

This paper presents a method to support real-time data communication over switched Ethernet. The work without modifications in the Ethernet hardware and coexists with TCP/IP suites. Experiment results shows that compared with conventional real-time network protocol, the proposed work has better real-time performances and meets the requirements for industrial control network real-time applications.

Data communication and intelligence in traffic simulation environments: Simulation time and performance experiments

2021 ◽  
pp. 1-8
Author(s):  
Joonho Ko ◽  
Hyun Woong Cho ◽  
Jung In Kim ◽  
Hyunmyung Kim ◽  
Young-Joo Lee ◽  
...  
Keyword(s):  
Real Time ◽  
Traffic Simulation ◽  
Data Communication ◽  
Simulation Models ◽  
Traffic Information ◽  
Time Data ◽  
Simulation Performance ◽  
Communication Methods ◽  
Simulation Time ◽  
Simulation Environments

Transportation system management and traveler information systems evolve with the development of data communications and intelligence of traffic simulations. Variety of roadside and mobile sensing platforms will be deployed to allow communication between vehicles with Dedicated Short Range Communications (DSRC). Traffic data received from moving vehicles will be transmitted to each individual vehicle and traffic management center to provide real time traffic information. Microscopic traffic simulation models will be used for generating intelligence from real time data in the form of traffic analysis and prediction, since they have the highest detailed level of prediction such as vehicle / driver characteristics and have the capability to capture dynamically changing traffic conditions through the simulation. In this study, three communication methods for data communication and intelligence in traffic simulation environments are used including Ethernet, off-the-shelf wireless network, and one commercial network provider for data communication. Simulation time is measured and statistically analyzed using three different communication methods and one non-communication case. Also, traffic simulation performance is investigated to demonstrate the intelligence of traffic simulation tools in modeling traffic congestion.

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