0


基于语义和流技术的都柏林城市实时监控

Real-time Urban Monitoring in Dublin using Semantic and Stream Technologies
课程网址: http://videolectures.net/iswc2013_kotoulas_stream_technologies/  
主讲教师: Spyros Kotoulas
开课单位: IBM 研究
开课时间: 2013-11-28
课程语种: 英语
中文简介:
在大多数现代城市中,已经有几种信息来源,来自人、系统、事物。 处理这些连续的信息流并获取洞察力带来了独特的技术挑战,从响应时间限制到格式和吞吐量方面的数据异构性。 为了解决这些问题,我们将重点放在一个新的原型上,以简化都柏林的实时监控和决策过程,它具有三个主要的原创技术方面:(I)对SPARQL的扩展,以支持高效的异构流查询;(Ii)基于IBM InfoSphere Streams的查询执行框架和运行时环境,这是一个高性能、工业强度的流处理引擎;(Iii)混合RDFS推理器,针对我们的流处理执行框架进行了优化。 我们的方法已经通过现场收集的真实数据进行了验证,如我们的都柏林城视频演示所示。 结果表明,基于语义技术的城市信息流的实时处理不仅是可能的,而且具有高效、可伸缩、低延迟的特点。
课程简介: Several sources of information, from people, systems, things, are already available in most modern cities. Processing these continuous flows of information and capturing insight poses unique technical challenges that span from response time constraints to data heterogeneity, in terms of format and throughput. To tackle these problems, we focus on a novel prototype to ease real-time monitoring and decision-making processes for the City of Dublin with three main original technical aspects: (i) an extension to SPARQL to support efficient querying of heterogeneous streams; (ii) a query execution framework and runtime environment based on IBM InfoSphere Streams, a high-performance, industrial strength, stream processing engine; (iii) a hybrid RDFS reasoner, optimized for our stream processing execution framework. Our approach has been validated with real data collected on the field, as shown in our Dublin City video demonstration. Results indicate that real-time processing of city information streams based on semantic technologies is indeed not only possible, but also efficient, scalable and low-latency.
关 键 词: 信息流; 语义技术; 流处理引擎
课程来源: 视频讲座网
数据采集: 2021-10-05:zkj
最后编审: 2021-10-15:zkj
阅读次数: 69