scholarly journals Research on Security Framework of Mobile Application in Dispatch and Control Domain of Power Grid

2018 ◽  
Vol 173 ◽  
pp. 02029
Author(s):  
XU Jiahui ◽  
YU Hongyuan ◽  
WANG Gang ◽  
WANG Zi ◽  
BAI Jingjie ◽  
...  
Keyword(s):  
Real Time ◽  
Mobile Application ◽  
Power Grid ◽  
Rapid Development ◽  
Mobile Internet ◽  
Internet Technology ◽  
Security Framework ◽  
Time Data ◽  
Real Time Data ◽  
And Control

The rapid development of mobile Internet technology and the wide spread of smart terminals have brought opportunities for the transformation of power grid business model. Compared to the non-real-time information, the real-time and running data of dispatch and control domain is easy to be intercepted and cracked. To solve this problem, this paper presents a new approach to mobile application security framework for the power grid control field. It is to realize secondary encryption by using the method of MD5+AES mixed encryption algorithm and combining the time stamp in real-time data transmission process. At the same time it is to prevent cross-border operations and brute force by using Token authentication and Session technology. China EPRI safety test results show that the application of the framework significantly improves the integrity, safety and reliability of real-time data in power grid control.

Next Generation of Real Time Data Acquisition, Calibration and Control System for the RatCAP Scanner

2007 ◽  
Author(s):  
Sachin S Junnarkar ◽  
Jack Fried ◽  
Sudeepti Southekal ◽  
Jean-Francois Pratte ◽  
Paul O'Connor ◽  
...  
Keyword(s):  
Control System ◽  
Data Acquisition ◽  
Real Time ◽  
Next Generation ◽  
Time Data ◽  
Real Time Data ◽  
And Control

scholarly journals Internet of Things based Customer Relationship Management – A Research Perspective

2018 ◽  
Vol 7 (2.7) ◽  
pp. 444 ◽  
Author(s):  
Samir Yerpude ◽  
Dr Tarun Kumar Singhal
Keyword(s):  
Internet Of Things ◽  
Real Time ◽  
Customer Relationship Management ◽  
Relationship Management ◽  
Mobile Internet ◽  
Customer Relationship ◽  
Time Data ◽  
Crm System ◽  
Real Time Data ◽  
The Impact

Objectives: To study the impact of Internet of things (IoT) on the Customer Relationship Management process and evaluate the benefits in terms of customer satisfaction and customer retention. Methods: An extensive literature review was conducting wherein the constructs of CRM and IoT are studied. Various preliminary information on IoT and CRM system along with the components of Digital enablers have been evaluated. References from research papers, journals, Internet sites, statistical data sites and books were used to collate the relevant content on the subject. The study of all the relevant scenarios where there is a possible impact of IoT origin real time data on CRM was undertaken. Findings: Customer demands are continuously evolving and it is very relevant for all the organizations to align and keep pace with the change. Organizations need to be customer centric and agile to the changing market scenarios. Evaluation of the trends in mobile internet vs desktop internet was also conducted to validate the findings. Application: The usage of real time data emerging out of the IoT landscape has become a reality with the data transmitted over the Internet and consumed by the CRM system. It improves the control on the customer relationship function helping the organizations to operate within healthy and sustained profit  

A hardware/software environment for real-time data acquisition and control

2000 ◽  
Vol 47 (2) ◽  
pp. 132-135 ◽  
Author(s):  
A.L. Veiga ◽  
M.A. Mayosky ◽  
N. Martinez
Keyword(s):  
Data Acquisition ◽  
Real Time ◽  
Time Data ◽  
Software Environment ◽  
Real Time Data ◽  
And Control

scholarly journals Artificial Intelligence assisted Prediction of COVID-19 Hotspots in Third Wave using EHTERAZ

2021 ◽  
Author(s):  
Mustafa Ahmed ◽  
Mohammed Houkan ◽  
Kishor Kumar Sadasivuni
Keyword(s):  
Artificial Intelligence ◽  
Real Time ◽  
Mobile Technology ◽  
Hot Spots ◽  
Mobile Application ◽  
Local State ◽  
Third Wave ◽  
Time Data ◽  
Policy Makers ◽  
Real Time Data

The present study conceptualizes fusion of artificial intelligence and contract tracking mobile application for predicting the COVID-19 hot spots. The findings suggest that mobile technology can be used to provide real-time data on the national and local state of the pandemic, enabling policy makers to make informed decisions in a quickly moving pandemic.

scholarly journals Investigation of the Potential to Use Real-Time Data in Production Planning and Control of Make to Order (MTO) Manufacturing Companies

2021 ◽  
pp. 165-185
Author(s):  
Manuel Woschank ◽  
Patrick Dallasega ◽  
Johannes A. Kapeller
Keyword(s):  
Real Time ◽  
Production Planning ◽  
Production Systems ◽  
Lead Times ◽  
Production Planning And Control ◽  
Time Data ◽  
Planning And Control ◽  
Make To Order ◽  
Real Time Data ◽  
And Control

AbstractThe integrated planning and control of logistics processes can be seen as one of the basic prerequisites for the successful implementation of smart production systems and smart and lean supply chains, as well. Therefore, modern Industry 4.0 approaches are mainly focusing on (1) the principles of decentralization and (2) the usage of real-time data to improve the overall logistics performance in terms of promised delivery dates, work in progress, capacity utilization, and lead-times. In this context, this chapter systematically evaluates the application of decentralized production planning and control strategies, e.g., KANBAN and CONWIP, in comparison with traditional approaches, like MRP. Moreover, the impact of real-time data usage in production planning and control systems on lead-times and work in progress is investigated using a discrete event simulation based on primary data from a make to order manufacturer. The results of this industrial case study research confirm the significant potential that lies in smart production systems and smart and lean supply chains and, therefore, in the introduction of Industry 4.0 technologies and technological concepts in production and logistics systems.

A Data-Driven Simulation-Based Optimisation Approach for Adaptive Scheduling and Control of Dynamic Manufacturing Systems

2016 ◽  
Vol 1140 ◽  
pp. 449-456 ◽  
Author(s):  
Mirko Kück ◽  
Jens Ehm ◽  
Michael Freitag ◽  
Enzo M. Frazzon ◽  
Ricardo Pimentel
Keyword(s):  
Simulation Model ◽  
Real Time ◽  
Flexible Manufacturing ◽  
Manufacturing Systems ◽  
Shop Floor ◽  
Time Data ◽  
Rush Order ◽  
Real Time Data ◽  
High Flexibility ◽  
And Control

The increasing customisation of products, which leads to higher numbers of product variants with smaller lot sizes, requires a high flexibility of manufacturing systems. These systems are subject to dynamic influences and need increasing effort for the generation of the production schedules and for the control of the processes. This paper presents an approach that addresses these challenges. First, scheduling is done by coupling an optimisation heuristic with a simulation model to handle complex and stochastic manufacturing systems. Second, the simulation model is continuously adapted by real-time data from the shop floor. If, e.g., a machine breakdown or a rush order appears, the simulation model and consequently the scheduling model is updated and the optimisation heuristic adjusts an existing schedule or generates a new one. This approach uses real-time data provided by future cyber-physical systems to integrate scheduling and control and to manage the dynamics of highly flexible manufacturing systems.

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