CAREER: SensorFly: Minimalistic Dynamic Sensing and Organization in Groups of Semi-Controllable Mobile Sensing Devices

职业：SensorFly：半可控移动传感设备组中的简约动态传感和组织

• 批准号: 1149611
• 负责人: Pei Zhang
• 金额: $ 40万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-01 至 2017-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1149611&HistoricalAwards=false
• 关键词: CAREER; SensorFly; Minimalistic; Dynamic; Sensing

In a rapidly developing emergency situation the timely discovery of discovery of information about the inside of a building, such as temperature during a fire, is key to a successful response. A challenge is that the needed sensors are difficult to deploy and maintain in these situations. While robots can be used to gather some information, considerations of deployment logistics, dynamic environment, infrastructural dependence, reliability, and speed have limited their adoption. To address these problems, this project explores a novel approach of using a collection of simple controlled mobile air vehicles with sensors (SensorFly). By taking a minimalistic approach, where each device has few sensors, the SensorFly project will develop a basic understanding of such controlled-mobile networked systems, including trade-offs between per device capability and system capability, and low-level collaborative techniques to counter system non-determinism. To test models and evaluate different approaches, the project builds on testbeds involving SensorFly nodes, a low-cost 30-gram flying sensor node. The SensorFly project has the potential for broad social impact. Studies that improve information gathering in emergency situations will improve safety for both the responders and building occupants. Although the size and weight of available sensors and platforms may decrease over time, the application of minimal mobile sensing platforms will remain attractive due to their reduced intrusiveness. Therefore, the investigation into minimalistic approaches will have a lasting impact that extends beyond today's sensing systems. Finally, the project continues the PI's efforts for advising students in research and encouraging members of under-represented groups into science and engineering fields.

在迅速发展的紧急情况下，及时发现有关建筑物内部的信息，如火灾期间的温度，是成功应对的关键。一个挑战是，在这些情况下，所需的传感器很难部署和维护。虽然机器人可以用来收集一些信息，但对部署后勤、动态环境、基础设施依赖性、可靠性和速度的考虑限制了它们的采用。为了解决这些问题，该项目探索了一种使用带有传感器的简单控制移动飞行器（SensorFly）的新方法。通过采用极简主义的方法，每个设备只有很少的传感器，SensorFly项目将对这种受控移动网络系统有一个基本的了解，包括每个设备能力和系统能力之间的权衡，以及对抗系统非确定性的低级协作技术。为了测试模型和评估不同的方法，该项目建立在包含SensorFly节点的试验台上，这是一个低成本的30克飞行传感器节点。SensorFly项目有可能产生广泛的社会影响。改进紧急情况下信息收集的研究将提高响应者和建筑物居住者的安全。尽管可用的传感器和平台的尺寸和重量可能会随着时间的推移而减少，但由于其侵入性降低，最小移动传感平台的应用仍将具有吸引力。因此，对极简主义方法的研究将产生持久的影响，超出当今的传感系统。最后，该项目继续PI的努力，为学生的研究提供建议，并鼓励代表性不足的群体成员进入科学和工程领域。