Urban Fusion: Visualizing Urban Data Fused with Social Feeds via a Game Engine

Perháč, Ján; Zeng, Wei; Asada, Shiho; Arisona, Stefan Mueller; Schubiger, Simon; Burkhard, Remo; Klein, Bernhard

doi:10.1109/iv.2017.33

Cited by 11 publications

(9 citation statements)

References 20 publications

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“…Nonetheless, this work is not capable of interpreting human interactions. Another related study combines data sources of public transportation with social media to investigate how virtual reality can visualize big data in real-time [8]. Despite the insights on user-urban data interactions, the accuracy of the results in this work strongly relies on the level of social media use across the city.…”

Section: Digital Twinning In Smart Citiesmentioning

confidence: 99%

“…Monitoring human behavior and interactions in the urban context constitutes a critical step towards this realization. SCDT have previously captured human behavior and interactions in cities using social media [8] and crowdsourcing data through individual mobile phones [9]. Largely due to data limitations, these methods are limited in their ability to locate and capture the collective interactions of different communities.…”

Section: Introductionmentioning

confidence: 99%

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Community Dynamics in Smart City Digital Twins: A Computer Vision-based Approach for Monitoring and Forecasting Collective Urban Hazard Exposure

Mavrokapnidis¹,

Taylor²

2021

Proceedings of the Annual Hawaii International Conference on System Sciences

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Urbanization and the growth of human population are leading to increased complexities in the interactions of citizens with public spaces, creating cities that must be more responsive to community dynamics. Despite the critical need for community-based city management, current decision-making approaches are often uninformed by the collective behavior of communities across time and in different locations. Here, we introduce a computer vision-based monitoring and forecasting approach for Smart City Digital Twins (SCDT) that enables integrating collective behavior into the spatiotemporal assessments of exposure to urban heat stress. Our results from a pilot case study in the city of Columbus, GA, demonstrate the significance of integrating community dynamics into monitoring and forecasting urban hazard exposure. This ongoing study highlights how SCDT can make community dynamics more accessible to and responsive by city managers.

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Section: Digital Twinning In Smart Citiesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Community Dynamics in Smart City Digital Twins: A Computer Vision-based Approach for Monitoring and Forecasting Collective Urban Hazard Exposure

Mavrokapnidis¹,

Taylor²

2021

Proceedings of the Annual Hawaii International Conference on System Sciences

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“…Concretely, Moran et al [18] developed a project in which users, using a first-person perspective, can navigate in a 3D virtual world (built from LADAR data textured with Google Earth) populated with Twitter publications represented as 3D objects. More recently, the tool Urban Fusion [14] was developed to merge urban taxis data with Twitter publications. Urban Fusion is based on a 3D density map to represent geo-referenced data on the city map and a 3D histogram based on cubes to represent user trends at the beginning and end of taxi trips.…”

Section: Related Workmentioning

confidence: 99%

“…More recently, several projects started to explore the use of 3D virtual environments to visualise the data produced by sensor networks. Examples of application domains in which the use of 3D virtual worlds for data visualisation has demonstrated benefits include paleontology [9], health care [10,11], biology [12], astronomy [13], urban data visualisation [14], and big data visualisation in general [15,16].…”

Section: Introductionmentioning

confidence: 99%

Game-Like 3D Visualisation of Air Quality Data

Teles

Mariano

Santana

2020

MTI

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The data produced by sensor networks for urban air quality monitoring is becoming a valuable asset for informed health-aware human activity planning. However, in order to properly explore and exploit these data, citizens need intuitive and effective ways of interacting with it. This paper presents CityOnStats, a visualisation tool developed to provide users, mainly adults and young adults, with a game-like 3D environment populated with air quality sensing data, as an alternative to the traditionally passive visualisation techniques. CityOnStats provides several visual cues of pollution presence with the purpose of meeting each user’s preferences. Usability tests with a sample of 30 participants have shown the value of air quality 3D game-based visualisation and have provided empirical support for which visual cues are most adequate for the task at hand.

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“…The potential of VR in the field of data visualization has been widely recognized [4,7,18] 3 . VR data visualization systems have been created for the areas of climate research [23], social media feed data [20] and software analysis [26]. Companies such as Kineviz 4 , Virtualitics 5 and Dynamoid 6 already offer VR data visualization applications for businesses, science and engineering.…”

Section: Related Workmentioning

confidence: 99%