课题基金 / 基金详情

REU Site: Undergraduate Research Experiences in Machine Learning, Analytics, and Augmented Reality for Smart and Connected Health

REU Site: Undergraduate Research Experiences in Machine Learning, Analytics, and Augmented Reality for Smart and Connected Health
REU 网站:智能互联健康机器学习、分析和增强现实方面的本科生研究经验
批准号:
2150135
负责人:
Damian Valles Molina
金额:
$34.4万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2022
资助国家:
美国
项目状态:
已结题
起止时间:
2022-01-15 至 2024-12-31

项目摘要

项目成果

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中文摘要
翻译
该项目旨在促进本科生参与针对智能互联健康和计算机工程等新兴领域的研究。本科生将设计和开发融合人工智能(AI)和数据驱动技术的概念和应用程序,以促进国家健康、繁荣和福利。REU网站为本科生提供了一个参与多样化研究项目的独特机会,其中包括与自闭症谱系障碍(ASD)和多发性硬化症(MS)等残疾人合作,以及规划与火灾相关的智能城市应对措施。一些研究项目利用新的工程数据和网络视觉技术解决了患有自闭症儿童的行为和卫生问题。整合生物传感器、虚拟现实和机器学习等技术对于为多发性硬化症患者开发可靠和敏感的评估工具并增加对结果的信心至关重要。智慧城市消防为本科生提供了独特的温度监测学习体验,同时开发了自主数据收集方法,以突出安全官员关注的领域。此外,许多研究课题没有在传统的本科课程中涵盖,这将有助于培养新一代专业人才。这个REU网站旨在让本科生接触到智能互联社区和智能互联健康等新兴领域的研究。本科生将设计和开发针对智能健康和智能社区工程问题的概念、系统和应用程序。该项目的智能主题从设计生态评估到应用机器学习(ML)、数据分析和增强现实(AR)作为分析和发现健康相关应用的新方面的新范式。每年夏天,REU网站将为不同的本科生群体提供直接参与研究活动的机会,以发展学科知识、研究能力和团队技能。REU网站的重点是使学生能够在三个主要领域进行研究:1)针对自闭症谱系障碍(ASD)儿童的智能情绪识别和网络训练;2)残疾人的认知和身体姿势控制;以及3)智能城市火灾响应。REU的研究项目将利用ML计算模型、AR可视化和数据分析来推进生态评估的最新水平,并将由本科生进行服务于他们的社区。为期八周的深入暑期研究将增加本科生的留存时间,改善他们的职业前景,让他们参与到数据驱动的研究的下一个前沿,并激励他们进入STEM-Health研究生项目。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
This project aims to facilitate the inclusion of undergraduates in research targeting the emerging areas of smart and connected health and computer engineering. Undergraduate students will design and develop concepts and applications that integrate artificial intelligence (AI) and data-driven techniques to advance the national health, prosperity, and welfare. The REU site provides a unique opportunity for undergraduates to engage with a diverse research program that includes working with persons with disabilities such as autism spectrum disorder (ASD) and multiple sclerosis (MS) and planning for smart city fire-related responses. Some of the research projects address the behavior and hygiene of children with ASD using new engineering data and cyber visual techniques. Integrating technology such as biosensors, virtual reality, and machine learning are crucial for developing reliable and sensitive assessment tools for people with MS and increasing confidence in the results. Smart city firefighting provides a unique learning experience for undergraduates in monitoring temperatures while developing autonomous data collection methods to highlight areas of concern for safety officials. Moreover, many research topics are not covered under traditional undergraduate curricula and will help prepare a new generation of professionals.This REU site seeks to expose undergraduate students to research in the emerging fields of smart and connected communities and smart and connected health. The undergraduate students will design and develop concepts, systems, and applications that target smart-health and smart-community engineering problems. The intellectual theme of this project ranges from designing an ecological assessment to applying machine learning (ML), data analytics, and augmented reality (AR) as new paradigms to analyze and discover new aspects of health-related applications. Each summer, the REU site will provide a diverse group of undergraduate students, many from underrepresented groups, opportunities to directly participate in research activities to develop disciplinary knowledge, research abilities, and team skills. The focus of the REU site is to enable students to perform research in three main areas: 1) intelligent emotion recognition and cyber training for children with autism spectrum disorder (ASD); 2) cognitive and body posture control for persons with disabilities; and 3) smart-city fire response. The REU research projects will advance the state of the art in ecological assessment utilizing ML computational models, AR visualization, and data analysis and will be performed by the undergraduate students to serve their communities. Eight weeks of in-depth summer research will increase undergraduate students’ retention, improve their career perspectives, engage them to participate in the next frontier of data-driven research, and motivate them to enter graduate STEM-Health programs.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(1)
专著(0)
科研奖励(0)
会议论文
Data Collection and Real-Time Facial Emotion Recognition in iOS Apps with CNN-Based Models
使用基于 CNN 的模型在 iOS 应用程序中进行数据收集和实时面部情绪识别
DOI: 10.1109/aiiot58121.2023.10174520
发表时间: 2023
期刊: IEEE
影响因子: --
作者: [Valles, Damian, Umali, Lois Adrianne, Paveglio, Thomas, Brinson, Josiah N., Hyder, Mohammed, Jackson, Gavin E., Hall, Dylan, Farrell, John W., Li, Yumeng, Aslan, Semih]
通讯作者: Aslan, Semih
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  • 项目类别:
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  • 资助金额:
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  • 批准年份:
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  • 负责人:
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  • 批准号:
    41340011
  • 项目类别:
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  • 资助金额:
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  • 批准年份:
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