SCC-PG: Coordinated Safety Management Across Smart Communities

这项规划补助金使研究在佛罗里达大学（UF）和盖恩斯维尔市（市），以指导UF和城市社区如何最好地整合和协调安全相关的数据，决策和保护性干预措施。除其他目标外，UF-City联合战略计划预计将部署智能传感和适应性基础设施，以实现社区安全的数据信息协调管理。UF和城市正在UF和邻近街道的多条街道上部署智能照明基础设施，这也提供了部署多种传感器所需的脚手架。可以设想多种场景来增强安全性，包括用于警告或指示的对讲扬声器、枪击/主动射击者和胁迫声音检测、远程图像/视频捕获以及光和移动性管理。预计人类传感器（例如使用智能手机的人）将通过社交网络平台，家庭安全系统和安全应用程序提供信息。从社交网络生成的数据可以通过早期预警补充来自基础设施传感器的数据，并帮助实施和评估干预措施，以解决潜在的风险领域和实际的安全事件。在该项目的范围内，正在审议若干多学科问题。如何从用友和城市位置的数据流，相关，集成，分析和可视化由单独的安全管理实体联合？如何从观察到的数据模式中真实的实时预防和/或检测安全事件？如何整合来自基础设施传感器和人体传感器的数据？人类（管理人员和公民）如何访问、可视化和与用于提取和呈现安全信息的数据分析系统交互？如何共同解决安全、安保和隐私问题？如何构建分布式计算系统，以支持智能城市基础设施（包括社区用户拥有的设备）中此类工作流的计算、存储和网络需求？该项目的预期成果包括（1）在UF城市社区的背景下整合社会技术视角的精心制定的研究问题，（2）确定具备解决问题所需知识的学术界和社区伙伴关系;（3）将纳入未来SCC的初步工作和试验台设计-该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This planning grant enables research at the University of Florida (UF) and the City of Gainesville (City) to guide UF and City communities on how best to integrate and coordinate safety-relevant data, decision-making, and protective interventions. A joint UF-City strategic plan, among other objectives, anticipates the deployment of smart sensing and adaptable infrastructure for data-informed coordinated management of community safety. UF and the City are deploying smart-lighting infrastructure on multiple streets across UF and neighboring streets which also provides the scaffolding needed to deploy sensors of several kinds. Multiple scenarios can be envisioned for safety enhancement, including talk-down speakers for warnings or instructions, gunshot/active shooter and duress sounds detection, remote image/video capture and light and mobility management. It is anticipated that human sensors (e.g. people using smartphones) will provide information via social networking platforms, home-security systems and safety apps. Data generated from social networks can complement data from infrastructure sensors with early warnings and help implement and evaluate interventions to address potential risk areas and actual safety events. Several multidisciplinary questions are being considered in the context of the project. How can data from UF and City locations be streamed, correlated, integrated, analyzed and visualized jointly by separate safety management entities? How can safety incidents be prevented and/or detected in real time from observed data patterns? How can data from infrastructure sensors and human sensors be integrated? How can humans (managers and citizens) access, visualize and interact with data analytics systems used to extract and present safety information? How are safety, security and privacy issues collectively addressed? How can distributed computing systems be architected to support computing, storage and network needs of such workflows across a smart city infrastructure, including devices owned by users in the community? The anticipated outcomes of this project include (1) well formulated research problems that integrate socio-technical perspectives in the context of UF-City communities, (2) identification of academic and community partnerships with the necessary knowledge to address the problems and (3) preliminary work and testbed designs to be included in a future SCC-IRG proposal to address the problems.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.