Real time data acquisition and energy management system using distributed computer architecture

Author(s):  
M.K.G. Pillai ◽  
V. Ramakrishna ◽  
V.K. Agrawal
2014 ◽  
Vol 519-520 ◽  
pp. 70-73 ◽  
Author(s):  
Jing Bai ◽  
Tie Cheng Pu

Aiming at storing and transmitting the real time data of energy management system in the industrial production, an online data compression technique is proposed. Firstly, the auto regression model of a group of sequence is established. Secondly, the next sampled data can be predicted by the model. If the estimated error is in the allowable range, we save the parameters of model and the beginning data. Otherwise, we save the data and repeat the method from the next sampled data. At Last, the method is applied in electricity energy data compression of a beer production. The application result verifies the effectiveness of the proposed method.


J ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 147-153
Author(s):  
Paula Morella ◽  
María Pilar Lambán ◽  
Jesús Antonio Royo ◽  
Juan Carlos Sánchez

Among the new trends in technology that have emerged through the Industry 4.0, Cyber Physical Systems (CPS) and Internet of Things (IoT) are crucial for the real-time data acquisition. This data acquisition, together with its transformation in valuable information, are indispensable for the development of real-time indicators. Moreover, real-time indicators provide companies with a competitive advantage over the competition since they enhance the calculus and speed up the decision-making and failure detection. Our research highlights the advantages of real-time data acquisition for supply chains, developing indicators that would be impossible to achieve with traditional systems, improving the accuracy of the existing ones and enhancing the real-time decision-making. Moreover, it brings out the importance of integrating technologies 4.0 in industry, in this case, CPS and IoT, and establishes the main points for a future research agenda of this topic.


2016 ◽  
Vol 6 (10) ◽  
pp. 285 ◽  
Author(s):  
Yuefei Wang ◽  
Hao Hu ◽  
Li Zhang ◽  
Nan Zhang ◽  
Xuhui Sun

1986 ◽  
Vol 17 (5) ◽  
pp. 285-296 ◽  
Author(s):  
Massimo Annunziata ◽  
Giuseppe Cima ◽  
Paola Mantica ◽  
Giacomo R. Sechi

Author(s):  
Kiran Patel ◽  
Umesh Nagora ◽  
Hem C. Joshi ◽  
Surya Pathak ◽  
Kumarpalsinh A. Jadeja ◽  
...  

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