Research and Design of Robot Application System Security Protection in Electric Power Business Hall based on Artificial Intelligence

Author(s):  
Ke Qiao ◽  
Hong Yan ◽  
Xi Jiang ◽  
Xuesong Dong ◽  
Yunfeng Zou ◽  
...  
Author(s):  
Utku Köse

Objective of this chapter is to introduce an Augmented Reality based intelligent mobile application (M-Learning application) to support courses of Computer Education. In the study, it was aimed to provide an alternative way of improving M-Learning experiences by employing both Augmented Reality and Artificial Intelligence based approaches in a common environment. Briefly, the application is able to use an intelligent mechanism evaluating students' several dynamic learning parameters to match them with the most appropriate course materials provided over the system. So, each student can encounter with appropriate course materials matching with their states over the application system. The related course materials include both AR based ones and standard ones as uploaded by teachers. An evaluation based flow has been run in the study by using the developed application through courses of Computer Education and the obtained results have shown that the application is effective and successful enough at improving students' learning experiences and achieving a good Open Computer Education.


EDPACS ◽  
1974 ◽  
Vol 2 (3) ◽  
pp. 9-12
Author(s):  
Stephen D. Harlan ◽  
George H. Rittersbach

Energies ◽  
2020 ◽  
Vol 13 (12) ◽  
pp. 3110
Author(s):  
Konstantinos V. Blazakis ◽  
Theodoros N. Kapetanakis ◽  
George S. Stavrakakis

Electric power grids are a crucial infrastructure for the proper operation of any country and must be preserved from various threats. Detection of illegal electricity power consumption is a crucial issue for distribution system operators (DSOs). Minimizing non-technical losses is a challenging task for the smooth operation of electrical power system in order to increase electricity provider’s and nation’s revenue and to enhance the reliability of electrical power grid. The widespread popularity of smart meters enables a large volume of electricity consumption data to be collected and new artificial intelligence technologies could be applied to take advantage of these data to solve the problem of power theft more efficiently. In this study, a robust artificial intelligence algorithm adaptive neuro fuzzy inference system (ANFIS)—with many applications in many various areas—is presented in brief and applied to achieve more effective detection of electric power theft. To the best of our knowledge, there are no studies yet that involve the application of ANFIS for the detection of power theft. The proposed technique is shown that if applied properly it could achieve very high success rates in various cases of fraudulent activities originating from unauthorized energy usage.


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