NSF-AoF: FET: Small: Ubiquitous in-sensor computing for adaptive intelligent systems

NSF-AoF：FET：小型：适用于自适应智能系统的无处不在的传感器内计算

• 批准号: 2133475
• 负责人: Qiangfei Xia
• 金额: $ 50万
• 依托单位: University of Massachusetts Amherst
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2133475&HistoricalAwards=false
• 关键词: NSF; AoF; FET; Small; Ubiquitous

Miniaturized sensor systems with built-in memory and computing functionalities are the cornerstones of artificial intelligence at the edge. However, in currently deployed systems, sensing and computing occur in separate physical locations, imposing massive data shuttling between the sensor module and the cloud-computing platform. This is unsustainable in terms of energy efficiency, latency, and capacity to process sensor data, and hence has a negative environmental impact with billions of sensors connected in the era of the Internet of Things (IoT). The proposed project intends to go beyond state-of-the-art by system-level integration of sensing, memory, and computing functionalities into one chip, allowing for ubiquitous applications at low energy budget and low latency. Furthermore, building such systems on flexible substrates will enable affordable and biodegradable smart-wearables electronics capable of monitoring human health continuously and adaptively. The proposed educational and outreach activities will promote STEM careers, encourage diversity in engineering education and research, and significantly impact securing the future prosperity of the U.S. and the European collaborative partner (Finland). The proposed research aims at delivering intelligent and energy-efficient wearable electronics that will become ubiquitous in the era of IoT. The specific objectives towards this goal are as follows: 1) to design and fabricate emerging materials and devices for flexible sensors; 2) to integrate ferroelectric sensors and memristor crossbar arrays into a flexible near-sensor computing system with embedded security functionality; and 3) to demonstrate an in-sensor computing platform where emerging devices will be used as both sensing and non-volatile memory elements for in-pixel intelligent processing of images. The proposed research will enable the next-generation smart and flexible wearable electronics to process the acquired information onsite. By integrating the sensor module with the computing engine, the emerging hardware technologies will substantially improve power efficiency and computing throughput.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.

具有内置内存和计算功能的微型传感器系统是边缘人工智能的基石。但是，在当前部署的系统中，传感和计算发生在单独的物理位置中，在传感器模块和云计算平台之间施加了大规模的数据穿梭。这在能源效率，延迟和处理传感器数据的能力方面是不可持续的，因此在物联网时代（IoT）时期连接的数十亿个传感器会产生负面影响。拟议的项目旨在通过系统级的感应，内存和计算功能将功能的整合到一个芯片中，超越最新的，以便在低能预算和低潜伏期下使用无处不在的应用。此外，在柔性基材上构建此类系统将使能够负担得起且可生物降解的智能耐磨物电子产品能够连续和适应性地监测人类健康。拟议的教育和外展活动将促进STEM职业，鼓励工程教育和研究的多样性，并显着影响确保美国和欧洲合作伙伴（芬兰）的未来繁荣。拟议的研究旨在提供智能和节能的可穿戴电子产品，这些电子设备在物联网时代将变得无处不在。 实现此目标的具体目标如下：1）设计和制造新兴的材料和设备以智能传感器； 2）将铁电传感器和备忘录横梁阵列集成到具有嵌入式安全功能的灵活的近传感器计算系统中； 3）为了演示一个发射器计算平台，在该平台中，新兴设备将用作图像内像素内智能处理的传感和非挥发记忆元素。拟议的研究将使下一代智能和灵活的可穿戴电子设备能够在现场处理获得的信息。通过将传感器模块与计算引擎集成，新兴硬件技术将大大提高功率效率和计算吞吐量。该奖项反映了NSF的法定任务，并被认为是通过基金会的知识分子的智力优点和更广泛的影响来评估值得支持的。

项目成果

Towards Energy-Efficient Computing Hardware Based on Memristive Nanodevices

• DOI: 10.1109/mnano.2023.3297106
• 发表时间: 2023-10
• 期刊: IEEE Nanotechnology Magazine
• 影响因子: 1.6
• 作者: Y. Huang;Vignesh Ravichandran;Wuyu Zhao;Qiangfei Xia

Flexible Piezoelectric Pressure Sensors with In-Memory Computing Capabilities for Intelligent Electronic Skin.

具有内存计算功能的柔性压电压力传感器，适用于智能电子皮肤。

• 发表时间: 2023
• 期刊: EIPBN'23
• 作者: Majumdar, Sayani;Mäkelä, Tapio;Pernu, Tapio;Zhao, Wuyu;Xia, Qiangfei
• 通讯作者: Xia, Qiangfei