City360: Visualizing Multimodal City Events for Decision Support

Vaikunth Sridharan; Tanvi Banerjee; Pramod Anantharam; Archana Sheshadri; RoopTeja Muppalla; Amit P. Sheth; Krishnaprasad Thirunarayan

City360: Visualizing Multimodal City Events for Decision Support

Vaikunth Sridharan, Tanvi Banerjee, Pramod Anantharam, Archana Sheshadri, RoopTeja Muppalla, Amit P. Sheth, Krishnaprasad Thirunarayan

Research output: Contribution to conference › Abstract › peer-review

Abstract

Cities are increasingly outfitted with sensors for monitoring various conditions such as traffic, weather, air quality, and infrastructure related issues. Such well outfitted cities are generating massive amounts of multi-modal data leading to daunting challenges in assimilating, visualizing, and making sense of this data by city authorities and citizens. We propose City360 to address these challenges and provide decision support to city authorities and citizens. We demonstrate the utility of our system through concrete use cases for San Francisco Bay area that utilize heterogeneous data from various open city data sources.

Original language	American English
State	Published - Apr 15 2016
Event	Symposium of Student Research, Scholarship, and Creative Activities Materials - Wright State University Duration: Apr 15 2016 → …

Conference

Conference	Symposium of Student Research, Scholarship, and Creative Activities Materials
Period	4/15/16 → …

Keywords

Decision support
Multi-modal data visualization
Spatiotemporal querying
City infrastructure events

Disciplines

Arts and Humanities
Engineering
Life Sciences
Medicine and Health Sciences
Physical Sciences and Mathematics
Social and Behavioral Sciences

Access to Document

City360: Visualizing Multimodal City Events for Decision SupportFinal published version, 104 KBLicense: CC BY

Cite this

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title = "City360: Visualizing Multimodal City Events for Decision Support",

abstract = " Cities are increasingly outfitted with sensors for monitoring various conditions such as traffic, weather, air quality, and infrastructure related issues. Such well outfitted cities are generating massive amounts of multi-modal data leading to daunting challenges in assimilating, visualizing, and making sense of this data by city authorities and citizens. We propose City360 to address these challenges and provide decision support to city authorities and citizens. We demonstrate the utility of our system through concrete use cases for San Francisco Bay area that utilize heterogeneous data from various open city data sources.",

keywords = "Decision support, Multi-modal data visualization, Spatiotemporal querying, City infrastructure events",

author = "Vaikunth Sridharan and Tanvi Banerjee and Pramod Anantharam and Archana Sheshadri and RoopTeja Muppalla and Sheth, {Amit P.} and Krishnaprasad Thirunarayan",

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TY - CONF

T1 - City360: Visualizing Multimodal City Events for Decision Support

AU - Sridharan, Vaikunth

AU - Banerjee, Tanvi

AU - Anantharam, Pramod

AU - Sheshadri, Archana

AU - Muppalla, RoopTeja

AU - Sheth, Amit P.

AU - Thirunarayan, Krishnaprasad

PY - 2016/4/15

Y1 - 2016/4/15

N2 - Cities are increasingly outfitted with sensors for monitoring various conditions such as traffic, weather, air quality, and infrastructure related issues. Such well outfitted cities are generating massive amounts of multi-modal data leading to daunting challenges in assimilating, visualizing, and making sense of this data by city authorities and citizens. We propose City360 to address these challenges and provide decision support to city authorities and citizens. We demonstrate the utility of our system through concrete use cases for San Francisco Bay area that utilize heterogeneous data from various open city data sources.

AB - Cities are increasingly outfitted with sensors for monitoring various conditions such as traffic, weather, air quality, and infrastructure related issues. Such well outfitted cities are generating massive amounts of multi-modal data leading to daunting challenges in assimilating, visualizing, and making sense of this data by city authorities and citizens. We propose City360 to address these challenges and provide decision support to city authorities and citizens. We demonstrate the utility of our system through concrete use cases for San Francisco Bay area that utilize heterogeneous data from various open city data sources.

KW - Decision support

KW - Multi-modal data visualization

KW - Spatiotemporal querying

KW - City infrastructure events

UR - https://corescholar.libraries.wright.edu/urop_celebration/28

M3 - Abstract

T2 - Symposium of Student Research, Scholarship, and Creative Activities Materials

Y2 - 15 April 2016

ER -

City360: Visualizing Multimodal City Events for Decision Support

Abstract

Conference

Keywords

Disciplines

Access to Document

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