A Visual Analytics System with Agentic AI to Identify Usability Issues in Augmented Reality
Project Description
This project aims to enhance user experience (UX) evaluations for augmented reality (AR) applications. Identifying AR usability issues is challenging due to the complex interactions between users and dynamic real-world environments. Building on prior research of the supervisor, this project will integrate agentic AI capabilities to further automate and enhance the identification and visualization of usability issues.
Agentic AI refers to autonomous systems capable of proactively suggesting solutions and generating insights based on data-driven learning. By leveraging agentic AI, the system will analyze user behavior data, camera views, and interaction metrics to identify usability patterns and anomalies. Unlike traditional systems, this enhanced framework will provide actionable recommendations to UX evaluators, enabling more efficient and accurate detection of usability challenges.
The project involves the development of a proof-of-concept system that combines agentic AI models with visualization techniques in the context of AR to represent usability metrics. The students will receive a lot of training in this project.
Agentic AI refers to autonomous systems capable of proactively suggesting solutions and generating insights based on data-driven learning. By leveraging agentic AI, the system will analyze user behavior data, camera views, and interaction metrics to identify usability patterns and anomalies. Unlike traditional systems, this enhanced framework will provide actionable recommendations to UX evaluators, enabling more efficient and accurate detection of usability challenges.
The project involves the development of a proof-of-concept system that combines agentic AI models with visualization techniques in the context of AR to represent usability metrics. The students will receive a lot of training in this project.
Supervisor
YUAN, Linping
Quota
2
Course type
UROP1100
Applicant's Roles
The student applicants will play a key role in the development, testing, and refinement of the visual analytics system. Their responsibilities include:
1. System Development: Contributing to the integration of agentic AI algorithms into the existing visual analytics framework. This includes working on data pipelines to process user interactions, camera views, and motion data.
2. Testing and Evaluation: Designing and conducting usability tests with real or simulated user data to validate the system's effectiveness and usability.
1. System Development: Contributing to the integration of agentic AI algorithms into the existing visual analytics framework. This includes working on data pipelines to process user interactions, camera views, and motion data.
2. Testing and Evaluation: Designing and conducting usability tests with real or simulated user data to validate the system's effectiveness and usability.
Applicant's Learning Objectives
1. Agentic AI Integration: Understanding the principles of agentic AI and its application in autonomous systems for usability analysis.
2. Data Analytics for AR: Gaining expertise in processing and analyzing heterogeneous data sources, including user interaction logs, motion tracking, and camera feed data.
3. Software Development: Enhancing skills in software development, including working with machine learning libraries, data visualization tools, programming frameworks, and AR development.
4. Interdisciplinary research training: Developing the ability to work at the intersection of AI, visualization, and human-computer interaction (HCI), preparing them for future research or industry opportunities.
2. Data Analytics for AR: Gaining expertise in processing and analyzing heterogeneous data sources, including user interaction logs, motion tracking, and camera feed data.
3. Software Development: Enhancing skills in software development, including working with machine learning libraries, data visualization tools, programming frameworks, and AR development.
4. Interdisciplinary research training: Developing the ability to work at the intersection of AI, visualization, and human-computer interaction (HCI), preparing them for future research or industry opportunities.
Complexity of the project
Moderate