I-Corps: Embedded Artificial Intelligence and Machine Learning for Drone Vision

I-Corps：用于无人机视觉的嵌入式人工智能和机器学习

• 批准号: 1925742
• 负责人: Rodney Boehm
• 金额: $ 5万
• 依托单位: Texas A&M Engineering Experiment Station
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-04-15 至 2020-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1925742&HistoricalAwards=false
• 关键词: Corps; Embedded; Artificial; Intelligence; Machine

The broader impact/commercial potential of this I-Corps project is that it will enable artificial intelligence and machine learning (AI/ML) solutions to be implemented in embedded and remote devices. It provides the means to make any camera, remote sensor, or detector truly intelligent and capable of discernment and prediction; any device that has already been electronically equipped will have the potential to utilize decision making intellect. It will be a catalyst in making AI/ML truly ubiquitous and a commodity of the human experience. Intelligent sensors will help make the world safer, cameras will be able to detect anomalies and alert authorities before tragedies, and detectors will be able to predict emergencies instead of simply telemetering data. Economically, through human assistance, embedded AI/ML will enable society to be more efficient and produce greater yield. This has the potential to be a transformative technology that impacts multiple levels of society.This I-Corps project further develops an implementation of artificial intelligence and machine learning (AI/ML) directly as a hardware circuit. AI/ML have revolutionized several technical industries such as voice recognition, image processing, healthcare, and personalized advertisements. AI/ML operates by training a mathematical model, often a combination of non-linear functions, to make inferences about the model's environment. However, AI/ML has been primarily restricted to cloud-based applications with large quantities of computing resources. In contrast, this technology implements the AI/ML model as hardware circuit that fits within a single integrated circuit. This project builds off previous technical accomplishments that implemented software design principles, such as extensibility, service-oriented architecture, modularity, and loose coupling, in hardware design through software assisted compilation. Creating a software aid to automatically restructure the hardware design enabled the hardware to change much more dynamically according to a series of parameters. By applying similar techniques to AI/ML, the technology will be able deconstruct and analyze the AI/ML model, and through a series of algorithms construct a matching hardware circuit.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.

这个I-Corps项目更广泛的影响/商业潜力在于，它将使人工智能和机器学习（AI/ML）解决方案能够在嵌入式和远程设备中实现。它提供了使任何相机、遥感器或探测器真正智能化并能够识别和预测的手段;任何已经电子装备的设备都有可能利用决策智能。它将成为使AI/ML真正无处不在的催化剂，并成为人类体验的商品。智能传感器将有助于使世界更安全，摄像头将能够检测异常情况并在悲剧发生前向当局发出警报，探测器将能够预测紧急情况，而不仅仅是遥测数据。在经济上，通过人类的帮助，嵌入式AI/ML将使社会更有效率，产生更大的收益。 这有可能成为一项影响社会多个层面的变革性技术。这个I-Corps项目进一步开发了直接作为硬件电路的人工智能和机器学习（AI/ML）的实现。AI/ML已经彻底改变了几个技术行业，如语音识别，图像处理，医疗保健和个性化广告。AI/ML通过训练数学模型（通常是非线性函数的组合）来进行操作，以推断模型的环境。然而，AI/ML主要局限于具有大量计算资源的基于云的应用程序。相比之下，该技术将AI/ML模型实现为适合单个集成电路的硬件电路。该项目建立在以前的技术成就，实现软件设计原则，如可扩展性，面向服务的体系结构，模块化和松耦合，在硬件设计中通过软件辅助编译。创建一个软件辅助来自动重构硬件设计，使硬件能够根据一系列参数动态地改变。通过将类似的技术应用于AI/ML，该技术将能够解构和分析AI/ML模型，并通过一系列算法构建匹配的硬件电路。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。