RAPID: Preventing the Spread of Coronavirus with Efficient Deep Learning

RAPID：通过高效的深度学习防止冠状病毒的传播

• 批准号: 2027266
• 负责人: Song Han
• 金额: $ 12.5万
• 依托单位: Massachusetts Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-06-15 至 2021-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2027266&HistoricalAwards=false
• 关键词: RAPID; Preventing; Spread; Coronavirus; Efficient

The novel coronavirus, COVID-19 is a pandemic infecting people in the United States and around the world. It is of utmost importance to prevent the fast spread of the virus. This project will use artificial intelligence (AI) methods to slow down the infection by encouraging proper wear of Personal Protective Equipment (PPE) by hospital staff and by supporting social distancing. The planned method will help monitor dangerous activities pointed out by Center for Disease Control (CDC), such as hand-to-face contact, touching inside or crossing arms when taking off the gown and masks and social distancing. It will advance the national health, protect the healthcare workers and help the whole nation combat the pandemic. Video understanding and activity recognition have made great progress in recent years. This project will apply artificial intelligence on a mobile platform for efficient activity recognition techniques to guide people's activities in healthcare settings, including patients', health care workers' and community residents'. To protect privacy in transmission to the cloud, the project applies the team's work on model compression techniques and neural architecture search to make the AI more compact and efficient so that it can be deployed on edge devices. As a result, videos can be locally processed; only key information or the detection result is sent over the cloud, preserving people's privacy. Finally, the project will efficiently deploy such algorithms on mobile devices and make it freely available in the hospitals.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.

新型冠状病毒新冠肺炎是一种流行病，感染着美国和世界各地的人们。防止病毒的快速传播是至关重要的。该项目将使用人工智能(AI)方法，通过鼓励医院工作人员正确穿戴个人防护装备(PPE)和支持社交距离来减缓感染。计划中的方法将有助于监测疾病控制中心(CDC)指出的危险活动，如手对脸接触，脱下长袍和口罩时触摸或交叉手臂，以及社交距离。它将促进国民健康，保护医护人员，并帮助整个国家抗击疫情。近年来，视频理解和活动识别取得了很大的进展。该项目将在移动平台上应用人工智能，以获得高效的活动识别技术，以指导人们在医疗保健环境中的活动，包括患者、医护人员和社区居民的活动。为了保护传输到云中的隐私，该项目应用了该团队在模型压缩技术和神经架构搜索方面的工作，使人工智能更加紧凑和高效，从而可以部署在边缘设备上。因此，视频可以在本地处理；只有关键信息或检测结果通过云发送，保护了人们的隐私。最后，该项目将在移动设备上高效地部署这些算法，并在医院免费提供。这一奖项反映了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。