학술논문

Real-Time Adaptation of Context-Aware Intelligent User Interfaces, for Enhanced Situational Awareness
Document Type
Periodical
Source
IEEE Access Access, IEEE. 10:23367-23393 2022
Subject
Aerospace
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Engineering Profession
Fields, Waves and Electromagnetics
General Topics for Engineers
Geoscience
Nuclear Engineering
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Adaptation models
Context modeling
Ontologies
Optimization
Cognition
Real-time systems
Adaptive systems
Adaptive user interfaces
augmented reality
context-awareness
intelligent user interfaces
ontology modeling
ontology reasoning
situational awareness
user interface optimization
Language
ISSN
2169-3536
Abstract
In this work, a novel computational approach for the dynamic adaptation of User Interfaces (UIs) is proposed, which aims at enhancing the Situational Awareness (SA) of users by leveraging the current context and providing the most useful information, in an optimal and efficient manner. By combining Ontology modeling and reasoning with Combinatorial Optimization, the system decides what information to present, when to present it, where to visualize it in the display - and how , taking into consideration contextual factors as well as placement constraints. The main objective of the proposed approach is to optimize the SA associated with the displayed UI at run-time , while avoiding information overload and induced stress. In the context of this work, we have deployed our computational approach to the use case of an Augmented Reality (AR) system for Law Enforcement Agents (LEAs). To explore the benefits and limitations of the developed system, two evaluations have been conducted. The first one was an expert-based evaluation with LEAs and User Experience (UX) experts, assessing the appropriateness of the system’s decisions. The second one was a user-based evaluation involving LEAs from different agencies, estimating the SA, the mental workload and the overall UX associated with the system, through an AR simulation. The results indicate that the system enhances SA, and while not imposing workload, it provides an overall positive UX.