STTR Phase II: Intelligent Instruction Systems using Augmented Reality

STTR 第二阶段：使用增强现实的智能教学系统

• 批准号: 0646587
• 负责人: Jayfus Doswell
• 金额: $ 50万
• 依托单位: Juxtopia, LLC
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-03-15 至 2012-02-29
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0646587&HistoricalAwards=false
• 关键词: STTR; Phase; II; Intelligent; Instruction

This Small Business Innovation Research (SBIR) Phase II research project investigates the creation of intelligent instruction systems that exploit adaptive software mechanisms (i.e. intelligent software agents) and augmented virtual reality (AVR) techniques. Since it is common that production-line employees are required to wear goggles, intelligent agents could transfer their instructions via goggle-like wearable computers (i.e. AVR) that overlay the actual visual field with text and computer graphics. The proposed techniques will facilitate the real-time assessment of employees undergoing training and will allow the software agents to automatically and proactively reinforce weaker areas based on these assessments. An overall assessment model of all employees can characterize the entire workforce for a particular facility. For example, this overall assessment can be used to enhance resource management triggered by absenteeism or other factors, allowing planners to use such assessments for optimizing manufacturing processes by refactoring traditional, perhaps obsolete, production processes.The broader impacts of the technology result from the use of intelligent agents to manage and direct the cross-training of employees in typical work environments where absenteeism and workforce turnover are important issues. Additionally, this technology, through workforce training broadly impacts the workforce to become more adaptive and agile with the resulting positive impact on overall product quality and productivity.

这个小企业创新研究（SBIR）第二阶段研究项目调查了利用自适应软件机制（即智能软件代理）和增强虚拟现实（AVR）技术的智能教学系统的创建。由于生产线员工通常需要戴上护目镜，智能代理可以通过类似护目镜的可穿戴计算机（即AVR）传递指令，该计算机将文本和计算机图形覆盖在实际的视野上。所提出的技术将有助于对正在接受培训的员工进行实时评估，并允许软件代理根据这些评估自动主动地加强较弱的领域。所有员工的整体评估模型可以描述特定设施的整个劳动力。例如，这种全面的评估可以用于加强由缺勤或其他因素引发的资源管理，允许计划人员通过重构传统的（可能过时的）生产过程来使用这种评估来优化制造过程。该技术的更广泛影响来自于使用智能代理来管理和指导员工在典型工作环境中的交叉培训，在这些环境中，缺勤和员工流动是重要问题。此外，该技术通过劳动力培训广泛地影响劳动力，使其更具适应性和敏捷性，从而对整体产品质量和生产力产生积极影响。