Development and Evaluation of User Interfaces for Situation Observability in Life Support Systems
Author(s) -
Hilary Taylor,
Benjamin Lee,
Jerome Jhingory,
Gregorio Drayer,
Ayanna Howard
Publication year - 2012
Publication title -
42nd international conference on environmental systems
Language(s) - English
Resource type - Conference proceedings
DOI - 10.2514/6.2012-3488
Subject(s) - observability , computer science , human–computer interaction , mathematics
©2012 by the American Institute of Aeronautics and Astronautics, Inc.Presented at the 42nd International Conference on Environmental Systems (ICES), 15-19 July 2012, San Diego, California.DOI: 10.2514/6.2012-3488Slow-changing characteristics of controlled environmental systems, the increasing availability of sensor information, and the need to avoid human error makes the manual control of these systems ever more challenging to human operators both on the ground and inflight. Automation systems are better suited to make some of these repetitive and critical tasks more reliable and less time-consuming. However, along with achieving reliable automation, it is beneficial to allow human operators to intervene if a problem occurs within the system, especially in order to take manual control upon anomalies. Ecological interface design, which focuses on the flow of information between the system and the human rather than in particular processes that constitute them, offers a solution to this problem. Such interfaces are user-centered and allow the human operators to gain situation awareness and intervene if necessary. This paper makes use of a granular multi-sensor data fusion method to develop ecological user interfaces for a small-scale life support system. The methodology is applied to the model of a small-scale aquatic habitat working as a groundbased bioregenerative life support system. Three ecological user interfaces were designed and tested on eight non-expert users. Results show the advantage of using situation-rich signals generated by the granular multi-sensor data fusion method that simplifies displays of information to allow for the future design of decision support tools
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