An Augmented Reality Command and Control Sand Table Visualization of the User Interface Prototyping Toolkit (UIPT)

2020 ◽  
pp. 40-53
Author(s):  
Bryan Croft ◽  
Jeffrey D. Clarkson ◽  
Eric Voncolln ◽  
Alex Campos ◽  
Scott Patten ◽  
...  
Keyword(s):  
User Interface ◽  
Augmented Reality ◽  
Command And Control ◽  
And Control

scholarly journals A Command and Control System for Air Defense Forces with Augmented Reality and Multimodal Interaction

2020 ◽  
Vol 1627 ◽  
pp. 012002
Author(s):  
Long Chen ◽  
Wei Wang ◽  
Jue Qu ◽  
Songgui Lei ◽  
Taojin Li
Keyword(s):  
Control System ◽  
Augmented Reality ◽  
Multimodal Interaction ◽  
Command And Control ◽  
Air Defense ◽  
And Control ◽  
Command And Control System

scholarly journals User interface prototype for geospatial early warning systems – a tsunami showcase

2012 ◽  
Vol 12 (3) ◽  
pp. 555-573 ◽  
Author(s):  
M. Hammitzsch ◽  
M. Lendholt ◽  
M. Á. Esbrí
Keyword(s):  
User Interface ◽  
Natural Hazards ◽  
Early Warning ◽  
Command And Control ◽  
Relevant Information ◽  
Early Warning Systems ◽  
Warning Systems ◽  
Synergy Effects ◽  
Human Operators ◽  
And Control

Abstract. The command and control unit's graphical user interface (GUI) is a central part of early warning systems (EWS) for man-made and natural hazards. The GUI combines and concentrates the relevant information of the system and offers it to human operators. It has to support operators successfully performing their tasks in complex workflows. Most notably in critical situations when operators make important decisions in a limited amount of time, the command and control unit's GUI has to work reliably and stably, providing the relevant information and functionality with the required quality and in time. The design of the GUI application is essential in the development of any EWS to manage hazards effectively. The design and development of such GUI is performed repeatedly for each EWS by various software architects and developers. Implementations differ based on their application in different domains. But similarities designing and equal approaches implementing GUIs of EWS are not quite harmonized enough with related activities and do not exploit possible synergy effects. Thus, the GUI's implementation of an EWS for tsunamis is successively introduced, providing a generic approach to be applied in each EWS for man-made and natural hazards.

Developing an Augmented Reality-based Integrated Command and Control Platform under 5G Technologies and Its Applications

2020 ◽  
Vol 21 (5) ◽  
pp. 855-864
Author(s):  
Kyuyong Shin ◽  
Wonwoo Lee ◽  
Dongwook Kim
Keyword(s):  
Augmented Reality ◽  
Command And Control ◽  
5G Technologies ◽  
And Control

User interface and display management design for multiple-robot command and control

2001 ◽  
Author(s):  
John S. Bay ◽  
Louise E. Borrelli ◽  
Kevin L. Chapman ◽  
Thomas R. Harrold
Keyword(s):  
User Interface ◽  
Command And Control ◽  
Multiple Robot ◽  
And Control

Common command-and-control user interface for current force UGS

2009 ◽  
Author(s):  
Gary H. Stolovy
Keyword(s):  
User Interface ◽  
Command And Control ◽  
And Control

Designing Displays for Command and Control Supervision: Contextualizing Alerts and “Trust-But-Verity” Automation

2000 ◽  
Vol 44 (37) ◽  
pp. 646-649
Author(s):  
Mark Johnxys ◽  
Heather M. Oonk ◽  
Glenn A. Osga
Keyword(s):  
Decision Making ◽  
User Interface ◽  
Situation Awareness ◽  
Command And Control ◽  
And Control

Supervision of command and control tasks requires monitoring and maintaining situation awareness of multiple on-going tasks performed by other agents and systems. Automation may aid the user, but realistic automation is often not totally reliable. Sophisticated users may learn to use even unreliable automation to their advantage if 1) they employ a strategy such as “trust-but-verify”, and 2) the user interface supports this strategy by integrating information about the situation with the display of what the automation is doing. The trust-but-verify strategy can be broken into two parts: 1.1) conditional trust and 1.2) qualitative verification. Conditional trust involves knowing when the situation is conducive to trusting the automation. Qualitative verification involves using the automation as a guide or input into manual decision making.

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