I-Corps: A contactless, non-intrusive, artificial intelligence (AI)-enabled contact tracing system for reducing the spread of viruses

这个I-Corps项目更广泛的影响/商业潜力是利用人工智能（AI）和深度学习的最新进展来增强养老院的公共卫生挑战。发热作为一种非特异性的感染指标，在广泛的疾病和流行病中经常观察到。拟议的人工智能评估系统将创建一个有效的，非侵入性的工具，使养老院设施和诊所能够对抗传染病和未来流行病的传播，同时为我们的社区提供更高的健康弹性。所提出的技术创建了一个实时健康监测系统，该系统也可以被广泛的公共卫生应用所采用和定制，这些应用需要通过预测分析和主动决策进行连续的非侵入性健康监测。I-Corps项目的基础是开发一个监测系统，通过实时人工智能、多传感器融合和视频数据分析来降低风险并控制流行病毒的传播。与现有的方法相比，现有的方法具有有限的智能能力，所提出的技术提供了一个整体的解决方案，可以在确保严格的个人隐私措施的情况下，从远处进行可扩展的，可靠的症状评估和接触者追踪。通过利用红绿色蓝（RGB）和热感相机（现成产品），可以提供能够同时监测若干健康指标的更精确的系统;例如，体温、呼吸频率、咳嗽和打喷嚏，同时采取非侵入性方法。拟议的设备配备了一个支持AI的接触者追踪系统，通过在早期阶段识别潜在感染者来减少病毒的传播。对于隐私感知的联系人跟踪，该计划将利用先前开发的技术进行实时隐私内置人体姿势估计，重新识别，轨迹分析和活动识别。该技术基于RGB摄像头创建轻量级的端到端实时计算机视觉执行，能够在嵌入式和边缘设备上以高帧率执行。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响力评审标准进行评估，被认为值得支持。

The broader impact/commercial potential of this I-Corps project is to use recent advances in artificial intelligence (AI) and deep learning to enhance public health challenges in nursing homes. Fever, as a non-specific measure of infection, is commonly observed in a broad range of diseases and pandemics. The proposed AI-powered assessment system will create an effective, non-intrusive tool for empowering nursing home facilities and clinics to combat the spread of contagious diseases and future pandemics, all the while providing a higher health resiliency for our communities. The proposed technology creates a real-time health surveillance system that also may be adopted and customized to a wide range of public health applications that require continuous, non-intrusive health monitoring with predictive analytics and proactive decision making. The proposed research has significant opportunities both in the public and private sectors.This I-Corps project is based on the development of a monitoring system to mitigate the risk and control the spread of epidemic viruses through real-time artificial intelligence, multi-sensor fusion, and video data analytics. In contrast to existing approaches that have a narrow focus with limited intelligence capabilities, the proposed technology offers a holistic solution to enable scalable, reliable symptom assessment and contact tracing from a distance with strict personal privacy measures ensured. By utilizing both red green blue (RGB) and thermal cameras (off-the-shelf products), it may be possible to provide a more precise system that is capable of monitoring several health indicators simultaneously; e.g., body temperature, respiratory rate, coughing, and sneezing while taking a non-intrusive approach. The proposed device is equipped with an AI-enabled contact tracing system for reducing the spread of viruses by identifying the potentially infected individuals at the early stage. For privacy-aware contact tracing, the plan is to leverage previously developed technology for real-time privacy built-in human pose estimation, re-identification, trajectory analysis, and activity recognition. The technology creates lightweight, end-to-end execution of real-time computer vision based on RGB cameras, with the ability to perform at a high frame rate on embedded and edge devices.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.