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International Workshop on GeoStreaming最新文献

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Area-to-point kernel regression on streaming data 流数据的区域到点核回归
International Workshop on GeoStreaming Pub Date : 2011-11-01 DOI: 10.1145/2064959.2064967
A. Pozdnoukhov, C. Kaiser
{"title":"Area-to-point kernel regression on streaming data","authors":"A. Pozdnoukhov, C. Kaiser","doi":"10.1145/2064959.2064967","DOIUrl":"https://doi.org/10.1145/2064959.2064967","url":null,"abstract":"Spatial data streams are often referenced to an areal spatial unit such as a polygon rather than to a precise point location. This is the case when geo-referencing is done by user IP addresses or from a mobile phone cell ID in various location-based service applications. One problem of interest in this case is spatial modelling of various spatially continuous quantities, such as an intensity of the usage of particular service in the area. This paper investigates a machine learning framework that account for area-to-point data processing. The approach is based on so-called vicinal risk minimization principle. It is elaborated in detail for a class of kernel recursive algorithms developed for distributed processing of streaming data. Concrete examples of kernel computations are provided and the method performance is investigated experimentally.","PeriodicalId":190366,"journal":{"name":"International Workshop on GeoStreaming","volume":"242 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121332084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
In an era of GPS traces 在GPS追踪的时代
International Workshop on GeoStreaming Pub Date : 2011-11-01 DOI: 10.1145/2064959.2064960
Mohamed H. Ali
{"title":"In an era of GPS traces","authors":"Mohamed H. Ali","doi":"10.1145/2064959.2064960","DOIUrl":"https://doi.org/10.1145/2064959.2064960","url":null,"abstract":"In an era of a proliferation of GPS devices, family members can track each other as they are moving around on a minute to minute basis. In an era of a proliferation of communication technologies, the whole world is becoming a big family. Would the world's big family track its own members? In an era where cell phones, cars, cameras, portable devices and probably key chains and pencils may have GPS devices; are we going to develop location-intelligent software that reasons about the collected GPS traces?\u0000 This talk discusses the utilization of GPS traces at various scales starting from logging a \"single\" person's own GPS trace and up to collecting huge amounts of GPS traces from a \"crowd\" of objects. This talk elaborates on how software can reason about GPS traces starting from applications that we use on a daily basis, e.g., email clients and calendars, and up to complex systems for data analysis and response. This talk oscillates between the pros and cons of collecting GPS traces, exploits the associated opportunities and highlights the inevitable risks. Finally, this talk addresses the industrial interest and the research trend in collecting, handling, processing and enriching GPS traces.","PeriodicalId":190366,"journal":{"name":"International Workshop on GeoStreaming","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125301877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
SGST: an open source semantic geostreaming toolkit SGST:一个开源语义地理流工具包
International Workshop on GeoStreaming Pub Date : 2011-11-01 DOI: 10.1145/2064959.2064964
J. Lee, Yong Liu, Liang Yu
{"title":"SGST: an open source semantic geostreaming toolkit","authors":"J. Lee, Yong Liu, Liang Yu","doi":"10.1145/2064959.2064964","DOIUrl":"https://doi.org/10.1145/2064959.2064964","url":null,"abstract":"Geo-referenced data streams (geostreams) have created major challenges on streaming data management, query, and integration. Semantically managing geostream data has the potential to provide better data integration and reasoning. We develop an open source Semantic GeoStreaming Toolkit (SGST) that aims to provide an integrated sensor data management solution. In particular, this paper uses the Open Geospatial Consortium (OGC) GeoSPARQL recommendation and a time-annotated RDF streaming data management service. The toolkit offers geostreaming data management, fetching, and RESTful web services. We demonstrate SGST with two real-world use cases including USGS earthquake GeoRSS feeds and geo-referenced Twitter feeds for citizen sensing. Issues related to interoperability, performance, and full support of GeoSPARQL are discussed.","PeriodicalId":190366,"journal":{"name":"International Workshop on GeoStreaming","volume":"140 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133765596","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Geostreaming in cloud 云中的地质流
International Workshop on GeoStreaming Pub Date : 2011-11-01 DOI: 10.1145/2064959.2064962
Seyed Jalal Kazemitabar, F. Kashani, D. McLeod
{"title":"Geostreaming in cloud","authors":"Seyed Jalal Kazemitabar, F. Kashani, D. McLeod","doi":"10.1145/2064959.2064962","DOIUrl":"https://doi.org/10.1145/2064959.2064962","url":null,"abstract":"In recent years, geospatial databases have been commercialized and widely exposed to mass users. Current exponential growth in data generation and querying rates for these data highlights the importance of efficient techniques for streaming. Traditional database technology, which operates on persistent and less dynamic data objects does not meet the requirements for efficient geospatial data streaming. Geostreaming, the intersection of data stream processing and geospatial querying, is an ongoing research focus in this area. In this paper, we describe why cloud is the most appropriate infrastructure in which to support geospatial stream data processing. First, we argue that cloud best fits the requirements of a large-scale geostreaming application. Second, we propose ElaStream, a general cloud-based streaming infrastructure that enables huge parallelism by means of the divide, conquer, and combine paradigm. Third, we examine key related work in the data streaming and (geo)spatial database fields, and describe the challenges ahead to build scalable cloud-based geostreaming applications.","PeriodicalId":190366,"journal":{"name":"International Workshop on GeoStreaming","volume":"374 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128002057","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 17
A perception based selection of vector map LoDs for progressive transmission 一种基于感知的矢量地图负载累进传输选择
International Workshop on GeoStreaming Pub Date : 2011-11-01 DOI: 10.1145/2064959.2064966
L. Paolino, M. Sebillo, G. Tortora, G. Vitiello
{"title":"A perception based selection of vector map LoDs for progressive transmission","authors":"L. Paolino, M. Sebillo, G. Tortora, G. Vitiello","doi":"10.1145/2064959.2064966","DOIUrl":"https://doi.org/10.1145/2064959.2064966","url":null,"abstract":"In many daily real problems it is necessary to exchange spatial data over the network and visualize them as soon and with higher quality as possible. Unfortunately, this is not always possible. As an instance, in case of event when slow or obstructed communication lines may make exchange of information difficult or even impossible. In order to mitigate this issue, an approach is sending data in a progressive way by generating simplified versions of the map and then, transmitting the coarsest map and then adding refinements passing through intermediate versions until reaching an acceptable detail. However, choosing the first and the subsequent versions is a complex problem and designers are often let to decide on a case-by-case basis. In this paper, we present a three step schema for generating simplified versions which is based on an empirical experiment whose aim is to determine which reduction levels can be applied by analyzing the perception of map changes with respect to the original map.","PeriodicalId":190366,"journal":{"name":"International Workshop on GeoStreaming","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129145729","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
A public transport awareness solution based on IBM InfoSphere Streams 基于IBM InfoSphere Streams的公共交通感知解决方案
International Workshop on GeoStreaming Pub Date : 2011-11-01 DOI: 10.1145/2064959.2064961
R. Rea
{"title":"A public transport awareness solution based on IBM InfoSphere Streams","authors":"R. Rea","doi":"10.1145/2064959.2064961","DOIUrl":"https://doi.org/10.1145/2064959.2064961","url":null,"abstract":"Uncertain arrival and departure times cause reduced usage of public transportation. A Public Transport Awareness solution from IBM captures, processes, stores and visualizes vehicle movements across a public transportation network. The solution continuously analyses vehicle data and generates vehicle location, status, speed and predicted time of arrival based on realtime GPS signals. With a vision to improve information for citizens to increase ridership and revenues, this solution predicts when their bus will arrive, and optimal routes to reach their destination at the desired time. The solution uses the Geospatial Toolkit for IBM InfoSphere Streams, which implements the World Geodetic System 84 to accurately track locations in real time. InfoSphere Streams, an advanced, commercial stream processing platform provides an innovative, distributed runtime and a graph-based, extensible programming paradigm. It is well suited to extreme performance requirements and highly s ophisticated processing and analytics on all kinds of data, from structured business records to text, audio, imagery, time-series and geospatial data. Geospatial is one of the hundreds of Streams applications that have been written for commercial, governmental, scientific and academic projects.","PeriodicalId":190366,"journal":{"name":"International Workshop on GeoStreaming","volume":"2 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115730419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Modeling and prediction of moving region trajectories 运动区域轨迹的建模与预测
International Workshop on GeoStreaming Pub Date : 2010-11-02 DOI: 10.1145/1878500.1878507
Conny Junghans, Michael Gertz
{"title":"Modeling and prediction of moving region trajectories","authors":"Conny Junghans, Michael Gertz","doi":"10.1145/1878500.1878507","DOIUrl":"https://doi.org/10.1145/1878500.1878507","url":null,"abstract":"Data about moving objects is being collected in many different application domains with the help of sensor networks, GPS-enabled devices, and in particular airborne sensors and satellites. Such moving objects often represent not just point-based objects, but rather moving regions like hurricanes, oil-spills, or animal herds. One key application feature users are often interested in is the exploration and prediction of moving object trajectories. While there exist models and techniques that help to predict the movement of moving point objects, no such method for moving regions has been proposed yet.\u0000 In this paper, we present an approach to model and predict the development of moving regions. Our method not only predicts the trajectory of regions, but also the evolution of a region's spatial extent and orientation. For this, moving regions are modelled using minimum enclosing boxes, and evolution patterns of regions are determined using linear regression and a recursive motion function. We demonstrate the functionality and effectiveness of the proposed technique using real-world sensor data from different application domains.","PeriodicalId":190366,"journal":{"name":"International Workshop on GeoStreaming","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130085698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 13
OpenSense: open community driven sensing of environment OpenSense:开放社区驱动的环境感知
International Workshop on GeoStreaming Pub Date : 2010-11-02 DOI: 10.1145/1878500.1878509
K. Aberer, Saket K. Sathe, D. Chakraborty, A. Martinoli, G. Barrenetxea, B. Faltings, L. Thiele
{"title":"OpenSense: open community driven sensing of environment","authors":"K. Aberer, Saket K. Sathe, D. Chakraborty, A. Martinoli, G. Barrenetxea, B. Faltings, L. Thiele","doi":"10.1145/1878500.1878509","DOIUrl":"https://doi.org/10.1145/1878500.1878509","url":null,"abstract":"This paper outlines a vision for community-driven sensing of our environment. At its core, community sensing is a dynamic new form of mobile geosensor network. We believe that community sensing networks, in order to be widely deployable and sustainable, need to follow utilitarian approaches towards sensing and data management. Current projects exploring community sensing have paid less attention to these underlying fundamental principles. We illustrate this vision through OpenSense -- a large project that aims to explore community sensing driven by air pollution monitoring.","PeriodicalId":190366,"journal":{"name":"International Workshop on GeoStreaming","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130921101","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 143
The Oracle platform for real time streaming event driven architecture based solutions Oracle平台的实时流事件驱动架构为基础的解决方案
International Workshop on GeoStreaming Pub Date : 2010-11-02 DOI: 10.1145/1878500.1878503
Robin J. Smith
{"title":"The Oracle platform for real time streaming event driven architecture based solutions","authors":"Robin J. Smith","doi":"10.1145/1878500.1878503","DOIUrl":"https://doi.org/10.1145/1878500.1878503","url":null,"abstract":"At the core of the Oracle Event Stream Processing strategy, the Oracle Complex Event Processing (CEP) technology provides a complete Real Time Integration Platform for building applications to filter, correlate and process streaming events, so that downstream ED-SOA applications are driven by true, real-time intelligence.\u0000 http://www.oracle.com/technetwork/middleware/event-driven-architecture/overview/index.html\u0000 Applications face an increasing need to track \"assets of interest\" and initiate actions based on encroachment of boundary proximity to fixed and moving objects and other geographic, temporal, or event conditions. This session will provide an overview of how the integration of Oracle Complex Event Processing with Oracle Spatial can address these conditions, showcasing a mission critical, highly available Real Time geo-fencing application demonstration.","PeriodicalId":190366,"journal":{"name":"International Workshop on GeoStreaming","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130273408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
A programming framework for integrating web-based spatiotemporal sensor data with MapReduce capabilities 集成基于web的时空传感器数据与MapReduce功能的编程框架
International Workshop on GeoStreaming Pub Date : 2010-11-02 DOI: 10.1145/1878500.1878511
James L. Horey
{"title":"A programming framework for integrating web-based spatiotemporal sensor data with MapReduce capabilities","authors":"James L. Horey","doi":"10.1145/1878500.1878511","DOIUrl":"https://doi.org/10.1145/1878500.1878511","url":null,"abstract":"Web-based sensor data, provided by organizations such as the National Oceanographic and Atmospheric Administration, provide a valuable service to the public and scientific communities. However, much of this data is locked in a variety of presentation formats and is computationally inaccessible. In addition, although these data have a spatiotemporal context, both the spatial and temporal data are usually only implicitly defined. Although storing this data in a consistent database can partially resolve this problem, a data-driven programming model coupled with MapReduce capabilities is a more flexible and extensible solution. Our implementation of this programming model allows users to parse a wide array of sensor data and express complex computation in a simple, scalable manner. In addition, our framework uses a simple key-value storage mechanism and provides convenient geospatial output mechanisms. In this paper, we discuss some early results of our programming model within the context of our current Java-oriented implementation, and demonstrate how the system can be used to create many different applications. We also discuss and evaluate our system with respect to memory usage and scalability.","PeriodicalId":190366,"journal":{"name":"International Workshop on GeoStreaming","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129211295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 5
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