NeTS-ProWiN: Emergency Ad Hoc Networking Using Programmable Radios and Intelligent Swarms

NetS-ProWiN：使用可编程无线电和智能群的紧急自组织网络

• 批准号: 0520332
• 负责人: Mario Gerla
• 金额: $ 75万
• 依托单位: University of California-Los Angeles
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-09-01 至 2010-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0520332&HistoricalAwards=false
• 关键词: NeTS; ProWiN; Emergency; Ad; Hoc

The focus of this project is the networking of intelligent, autonomous swarms. The typical application scenario is a disaster area that requires the intervention of police, firemen, paramedics etc, but where the unfriendly environment bars direct access. The swarm establishes a communications network between the rescue teams and all critical fixed and mobile sensors and actuators in the disaster area. In the aftermath of a disaster typically some disconnected "islands" of sensors, monitors and actuators have survived the impact. A rapidly deployed swarm of air/ground agents reestablishes network connectivity, restores access to critical sensor probes, installs new probes as necessary and helps the collection and filtering of relevant data. This goal is achieved with the concurrent interworking of several elements: agile, programmable radios that can work in adverse, highly heterogeneous conditions; flexible network protocols for swarm to swarm communications and for "mobile backbone" deployment; adaptive video streaming, and; advanced vision processing for location and motion estimation. Scientific contributions and broader impacts will include: (1) robust, reconfigurable Mobile Backbone design methodology for emergency networking (2) modular, flexible, programmable MAR radio technology for unfriendly/hostile scenarios. (3) real time video streaming and "delayed" forwarding.(4) In-swarm processing of video data for image registration and mosaicing, including partial 3-D reconstruction and matching to existing blueprint and mapping data(5) Region-of-interest computation for visual odometry and swarm configuration refinement

该项目的重点是智能、自主群体的网络。 典型的应用场景是需要警察、消防员、护理人员等介入的灾区，但环境恶劣又无法直接进入。集群在救援队与灾区所有关键的固定和移动传感器和执行器之间建立通信网络。在灾难发生后，通常一些断开连接的传感器、监视器和执行器“孤岛”能够幸免于难。快速部署的空中/地面代理群重新建立网络连接，恢复对关键传感器探头的访问，根据需要安装新探头，并帮助收集和过滤相关数据。这一目标是通过多个要素的并发互通来实现的：灵活的可编程无线电，可以在不利的、高度异构的条件下工作；用于群体间通信和“移动骨干”部署的灵活网络协议；自适应视频流，以及；用于位置和运动估计的高级视觉处理。科学贡献和更广泛的影响将包括：(1) 用于紧急网络的稳健、可重新配置的移动骨干网设计方法 (2) 用于不友好/敌对场景的模块化、灵活、可编程的 MAR 无线电技术。 (3) 实时视频流和“延迟”转发。(4) 用于图像配准和拼接的视频数据群内处理，包括部分 3D 重建以及与现有蓝图和地图数据的匹配(5) 用于视觉里程计和群配置细化的感兴趣区域计算