Conference: NSF Workshop on the Convergence of Smart Sensing Systems, Applications, Analytic and Decision Making

会议：NSF 智能传感系统、应用、分析和决策融合研讨会

• 批准号: 2334288
• 负责人: Mingyi Hong
• 金额: $ 10万
• 依托单位: University of Minnesota-Twin Cities
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-10-01 至 2024-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2334288&HistoricalAwards=false
• 关键词: Conference; NSF; Workshop; Convergence; Smart

We live in a highly interconnected world, and this interconnectivity is predicted to grow exponentially in the next decade. As a result of this rapid expansion, we anticipate a network of more than 50 billion interconnected smart systems, encompassing intelligent appliances, cars, gadgets, and tools. These systems possess the capability to collect extensive real-time data, perform complex computational tasks, and deliver valuable services and actionable insights, greatly enriching our lives and collective productivity. Essential components of these smart systems include distributed sensors, communication modules, as well as analytical and computational modules. These components are intricately intertwined and rely on each other. Overall, there is a natural synergy between different sensing technologies, their applications, and methodologies developed in analytical areas. The objective of the proposed workshop is to identify significant research and educational challenges pertaining to these areas related to smart sensing technologies. More specifically, the workshop aims to address significant research gaps in how researchers approach problems and formulate solutions in sensing applications while integrating tools and algorithms from analytical areas. Overall, the workshop aims to foster collaboration, knowledge exchange, and innovation between experts from various fields to advance the understanding and application of analytical tools in sensing systems. The main goals and areas of focus are as follows: 1 )Aligning the State-of-the-Art of Analytical Areas: The workshop aims to bridge the gap between various scientific fields, academia, and industry in data science, particularly machine learning, by presenting the cutting-edge computational and analytical capabilities in a way that is understandable to the sensing community. It seeks to establish effective methods to keep sensing system researchers updated on advancements in analytical areas and make these practices available in a publicly accessible repository. 2) Appreciating Algorithmic Limitations & Application Requirements: The workshop recognizes that the direct application of advanced algorithms from analytical areas to sensing systems can be distracting and limited, especially when considering the physical constraints inherent in sensing systems. Researchers need to develop customized computational and analytical tools that respect these constraints and align with specific application requirements. 3) Application-Specific Sensor Systems: The workshop acknowledges the broad range of sensors used in various applications and aims to develop new sensors or integrate existing ones to meet specific application requirements. It brings together experts from different fields to define and deliver technologies that address performance, cost, sampling, environmental, deployment, data collection, and ease-of-use needs in sensor systems.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.

我们生活在一个高度相互联系的世界中，预计这种相互联系将在未来十年内成倍增长。由于这种快速扩展，我们预计将拥有超过500亿个相互联系的智能系统的网络，包括智能设备，汽车，小工具和工具。这些系统具有收集广泛的实时数据，执行复杂的计算任务，提供宝贵的服务和可行的见解的能力，从而极大地丰富了我们的生活和集体生产力。这些智能系统的基本组件包括分布式传感器，通信模块以及分析和计算模块。这些组件复杂地交织在一起并彼此依赖。总体而言，不同的感应技术，它们的应用和在分析区域开发的方法之间存在自然的协同作用。拟议研讨会的目的是确定与智能传感技术有关的这些领域的重大研究和教育挑战。更具体地说，该研讨会旨在解决研究人员如何处理问题并在传感应用中制定解决方案的重大研究差距，同时集成分析领域的工具和算法。总体而言，该研讨会旨在促进来自各个领域的专家之间的协作，知识交流和创新，以提高传感系统中分析工具的理解和应用。重点的主要目标和领域如下：1）使分析领域的最新面积保持一致：该研讨会旨在通过呈现剪切的计算和分析能力来弥合各种科学领域，学术界和数据科学领域的差距，尤其是机器学习，以对感应社区可以理解的方式。它旨在建立有效的方法，以保持感应系统研究人员在分析领域的进步方面进行最新信息，并在公共可访问的存储库中提供这些实践。 2）欣赏算法的局限性和应用要求：研讨会认识到，从分析区域到感应系统的高级算法直接应用可能会分散注意力且有限，尤其是在考虑感应系统中固有的物理约束时。研究人员需要开发自定义的计算和分析工具，以尊重这些约束并与特定的应用要求保持一致。 3）特定于应用程序的传感器系统：研讨会承认各种应用中使用的广泛传感器，旨在开发新的传感器或整合现有传感器以满足特定的应用程序要求。它汇集了来自不同领域的专家来定义和提供有关传感器系统中的性能，成本，抽样，环境，部署，数据收集以及易用需求的技术。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的智力和更广泛影响的评估来通过评估来获得支持的。