展示PlanetSense:从众包和社交媒体数据中收集地理空间情报

Gautam Thakur, Kevin A. Sparks, Roger G. Li, R. Stewart, M. Urban
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引用次数: 1

摘要

众包和志愿者信息、社交媒体和参与式传感器能够提供实时活动数据。在危机管理期间,及时监测这些来源,然后利用它们收集操作知识非常重要。除此之外,为地理空间研究目的整理这些信息也很重要,包括土地利用分类和人口占用分析。在这次演示中,我们将展示PlanetSense——一个地理空间研究平台,旨在利用现有存档数据的力量,并添加来自社交媒体和自愿来源的异构实时流数据的动态,与复杂的机器学习算法和可视化工具无缝集成。演示将集中于- 1)最近的倡议,强调需要大规模利用群众资源、志愿者和社交媒体数据;2)对数据采集工作流程的剖析与洞察。我们将展示实时收集和处理数tb原始数据的能力;3)将对20多个数据来源进行详细讨论。这些来源包括文本、传感器以及图像数据;4) PlanetSense的端到端分布式架构将重点讨论在地理数据云中收集和处理大量流数据。用于将不同数据源与现有遗留产品集成的数据融合方法和算法。用于动态生成操作智能的数据分析和机器学习方法;5)此外,PlanetSense“App”平台将展示动手应用,使感兴趣的观众能够快速开发和部署解决方案。6)几个案例研究将讨论相关的,土地利用分类,监测流动人口,高分辨率占用分析,绘制特殊事件人口,近实时发现全球突发事件和反应的能力,跟踪抗议,骚乱和监测其他社会动荡的能力,以及实时监测基础设施中断。
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Demonstrating PlanetSense: gathering geo-spatial intelligence from crowd-sourced and social-media data
Crowd-sourced and volunteered information, social media, and participatory sensors are capable of providing real-time activity data. Monitoring these sources in time of relevance and then using them to gather operational knowledge is important during crisis management. Beyond that, it's important to curate this information for geo-spatial research purposes, including land use classification and population occupancy analysis. In this demonstration, we will showcase PlanetSense - a geo-spatial research platform built to harness the existing power of archived data and add to that, the dynamics of heterogeneous real-time streaming data from social media and volunteered sources, seamlessly integrated with sophisticated machine learning algorithms and visualization tools. A demonstration will focus on - 1) Recent initiative emphasizing the need to harness crowd-sources, volunteered, and social media data at scale; 2) Anatomy and insight into data collection workflow. We will show the ability to harvest and process several terabytes of raw data in real-time; 3) A detailed discussion with insight into more than 20 sources of data will be given. These sources include text, sensors, as well as imagery data; 4) PlanetSense's end to end distributed architecture will be discussed with focus on collecting and processing high-volumes of streaming data in a Geo-Data Cloud. Data fusion methods and algorithms for integrating disparate data sources with existing legacy products. Data analytics and machine learning methods for generating operational intelligence on the fly; 5) In addition, PlanetSense "App" platform will be shown with hands-on application enabling interested audience to quickly develop and deploy solutions. 6) Several case studies will be discussed relevant to, land use classification, monitoring transient population, high-resolution occupancy analysis, mapping special events population, ability to uncover global breaking events and reactions in near-real time, ability to track protest, unrest, and monitor other societal turbulences as they happen, and real-time monitoring of infrastructure outages.
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