Research and Application of Key Technologies on Cloud DTS based Intelligent Instructor System: Architecture and Functions
With the further deployment of the regulation cloud technology, it has become a trend to migrate DTS to the cloud platform, so as to give full play to the advantages of the cloud platform in resource sharing, efficient computation, etc. However, with insufficient intelligence and automation, dispatc...
Saved in:
Published in | 2022 4th International Academic Exchange Conference on Science and Technology Innovation (IAECST) pp. 909 - 913 |
---|---|
Main Authors | , , , , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
09.12.2022
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | With the further deployment of the regulation cloud technology, it has become a trend to migrate DTS to the cloud platform, so as to give full play to the advantages of the cloud platform in resource sharing, efficient computation, etc. However, with insufficient intelligence and automation, dispatching training on cloud DTS still requires the participation of real instructors throughout the process, which seriously restricts the application efficiency and effect. Therefore, this paper firstly analyzed shortcomings of existing DTS and proposed the architecture of the cloud DTS based intelligent instructor system (IIS) integrating with the adaptive learning model in order to meet the personalized and intelligent training needs for random concurrency of multiple dispatchers under cloud training mode. Then the application scenarios and functions of the IIS was described in detail, mainly from three aspects as automatic preparation of training cases before training, intelligent interaction and control of drill process during training and comprehensive evaluation for adaptive recommendation after training. Once fully developed, the IIS can provide continuous support for cloud DTS to become the daily and autonomous training tool for dispatchers at anytime and anywhere. |
---|---|
DOI: | 10.1109/IAECST57965.2022.10062129 |