2018 IEEE International Science of Smart City Operations and Platforms Engineering in Partnership with Global City Teams Challenge (SCOPE-GCTC)最新文献

Facilitation of Smart City and Community Technology Convergence 促进智慧城市与社区技术融合

2018 IEEE International Science of Smart City Operations and Platforms Engineering in Partnership with Global City Teams Challenge (SCOPE-GCTC) Pub Date : 2018-04-10 DOI: 10.1109/SCOPE-GCTC.2018.00013

M. Burns, S. Rhee

引用次数: 1

StormSense: A Blueprint for Coastal Flood Forecast Information & Automated Alert Messaging Systems StormSense:沿海洪水预报信息和自动警报信息系统的蓝图

2018 IEEE International Science of Smart City Operations and Platforms Engineering in Partnership with Global City Teams Challenge (SCOPE-GCTC) Pub Date : 2018-04-10 DOI: 10.1109/SCOPE-GCTC.2018.00009

J. Loftis, S. Katragadda, S. Rhee, Cuong Nguyen

{"title":"StormSense: A Blueprint for Coastal Flood Forecast Information & Automated Alert Messaging Systems","authors":"J. Loftis, S. Katragadda, S. Rhee, Cuong Nguyen","doi":"10.1109/SCOPE-GCTC.2018.00009","DOIUrl":"https://doi.org/10.1109/SCOPE-GCTC.2018.00009","url":null,"abstract":"Increased availability of low-cost water level sensors communicating through the Internet of Things (IoT) has expanded the horizons of publicly-ingestible data streams available to modern smart cities. StormSense is an IoT-enabled inundation forecasting research initiative and an active participant in the Global City Teams Challenge seeking to enhance flood preparedness in the smart cities of Hampton Roads, VA for flooding resulting from storm surge, rain, and tides. In this study, we present the a blueprint and series of applicable protocols through the use of the new StormSense water level sensors to help establish a regional resilience monitoring network. In furtherance of this effort, the Virginia Commonwealth Center for Recurrent Flooding Resiliency's Tidewatch tidal forecast system is being used as a starting point to integrate the extant (NOAA) and new (USGS and StormSense) water level sensors throughout the region, and demonstrate replicability of the solution across the cities of Newport News, Norfolk, and Virginia Beach within Hampton Roads, VA. StormSense's network employs a mix of ultrasonic sonar and radar remote sensing technologies to record water levels and develop autonomous alert messaging systems through the use of three separate cloud environments. One to manage the water level monitoring sensors and alert messaging, one to run the model and interface with the post-processed results, and one to geospatially present the flood results.","PeriodicalId":233750,"journal":{"name":"2018 IEEE International Science of Smart City Operations and Platforms Engineering in Partnership with Global City Teams Challenge (SCOPE-GCTC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130966541","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

Smart and Secure Cities and Communities 智慧和安全的城市和社区

2018 IEEE International Science of Smart City Operations and Platforms Engineering in Partnership with Global City Teams Challenge (SCOPE-GCTC) Pub Date : 2018-04-10 DOI: 10.1109/SCOPE-GCTC.2018.00008

Scott Tousley, S. Rhee

引用次数: 4

Structured Summarization of Social Web for Smart Emergency Services by Uncertain Concept Graph 基于不确定概念图的智能应急服务社会网络的结构化总结

2018 IEEE International Science of Smart City Operations and Platforms Engineering in Partnership with Global City Teams Challenge (SCOPE-GCTC) Pub Date : 2018-04-01 DOI: 10.1109/SCOPE-GCTC.2018.00012

Hemant Purohit, S. Nannapaneni, A. Dubey, P. Karuna, Gautam Biswas

{"title":"Structured Summarization of Social Web for Smart Emergency Services by Uncertain Concept Graph","authors":"Hemant Purohit, S. Nannapaneni, A. Dubey, P. Karuna, Gautam Biswas","doi":"10.1109/SCOPE-GCTC.2018.00012","DOIUrl":"https://doi.org/10.1109/SCOPE-GCTC.2018.00012","url":null,"abstract":"The Web has empowered emergency services to enhance operations by collecting real-time information about incidents from diverse data sources such as social media. However, the high volume of unstructured data from the heterogeneous sources with varying degrees of veracity challenges the timely extraction and integration of relevant information to summarize the current situation. Existing work on event detection and summarization on social media relates to this challenge of timely extraction of information during an evolving event. However, it is limited in both integrating incomplete information from diverse sources and using the integrated information to dynamically infer knowledge representation of the situation that captures optimal actions (e.g., allocate available finite ambulances to incident regions). In this paper, we present a novel concept of an Uncertain Concept Graph (UCG) that is capable of representing dynamic knowledge of a disaster event from heterogeneous data sources, particularly for the regions of interest, and resources/services required. The information sources, incident regions, and resources (e.g., ambulances) are represented as nodes in UCG, while the edges represent the weighted relationships between these nodes. We then propose a solution for probabilistic edge inference between nodes in UCG. We model a novel optimization problem for the edge assignment between a service resource to a region node over time trajectory. The output of such structured summarization over time can be valuable for modeling event dynamics in the real world beyond emergency management, across different smart city operations such as transportation.","PeriodicalId":233750,"journal":{"name":"2018 IEEE International Science of Smart City Operations and Platforms Engineering in Partnership with Global City Teams Challenge (SCOPE-GCTC)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124115224","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

Towards a Design Studio for Collaborative Modeling and Co-Simulations of Mixed Electrical Energy Systems 面向混合电能系统协同建模与协同仿真的设计工作室

2018 IEEE International Science of Smart City Operations and Platforms Engineering in Partnership with Global City Teams Challenge (SCOPE-GCTC) Pub Date : 2018-04-01 DOI: 10.1109/SCOPE-GCTC.2018.00011

Yogesh D. Barve, H. Neema, Stephen A. Rees, J. Sztipanovits

引用次数: 6

Crowd Motion Detection and Prediction for Transportation Efficiency in Shared Spaces 共享空间交通效率的人群运动检测与预测

2018 IEEE International Science of Smart City Operations and Platforms Engineering in Partnership with Global City Teams Challenge (SCOPE-GCTC) Pub Date : 2018-04-01 DOI: 10.1109/SCOPE-GCTC.2018.00007

Dongfang Yang, John M. Maroli, Linhui Li, Menna El-Shaer, Bander A. Jabr, K. Redmill, Füsun Özguner, Ümit Özguner

引用次数: 3

SDN-ERS: A Timely Software Defined Networking Framework for Emergency Response Systems SDN-ERS:应急响应系统的及时软件定义网络框架

2018 IEEE International Science of Smart City Operations and Platforms Engineering in Partnership with Global City Teams Challenge (SCOPE-GCTC) Pub Date : 2018-04-01 DOI: 10.1109/SCOPE-GCTC.2018.00010

M. Rahouti, Kaiqi Xiong, Tommy Chin, Peizhao Hu

引用次数: 7