A Mobile Visual Analytics Approach for Law Enforcement Situation Awareness

Razip, Ahmad M; Malik, Abish; Afzal, Shehzad; Potrawski, Matthew; Maciejewski, Ross; Jang, Yun; Elmqvist, Niklas; Ebert, David S.

doi:10.1109/pacificvis.2014.54

Cited by 27 publications

(9 citation statements)

References 26 publications

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“…Razip et al. (2014) present a mobile toolkit to help citizens and law enforcers assess risk levels in urban areas where risk was visualized as a density estimation, and de Queiroz Neto and co‐workers use marching squares to quickly generate high‐resolution hotspots (de Queiroz Neto, dos Santos, & Vidal, 2016) and characterize tasks for hotspot analysis (de Queiroz Neto, Santos, Vidal, & Ebert, 2020). Hu et al.…”

Section: Related Workmentioning

confidence: 99%

Exploring geographic hotspots using topological data analysis

Zhang

Lukasczyk

Wang³

et al. 2021

Transactions in GIS

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This article describes a scalar field topology (SFT)‐based methodology for the interactive characterization and analysis of hotspots for density fields defined on a regular grid. In contrast to the common approach of simply identifying hotspots as areas that exceed a chosen density threshold, SFT provides various data abstractions—such as the merge tree and the Morse complex—to characterize hotspots and their boundaries at multiple scales. Moreover, SFT enables the ranking of hotspots based on analyst‐defined importance measures, which also makes it possible to explore hotspots using a level‐of‐detail approach. We present a visual analytics system to support analysts in hotspot analysis and abstraction using SFT, and we demonstrate the merit of the proposed SFT‐based methodology on two crime datasets.

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Section: Related Workmentioning

confidence: 99%

Exploring geographic hotspots using topological data analysis

Zhang

Lukasczyk

Wang³

et al. 2021

Transactions in GIS

Self Cite

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“…Visualisation that taps the human cognitive ability to recognise patterns has also been employed by Razip et al [167] in helping law enforcement officers increase their situational awareness. Officers are equipped with mobile devices that tap into crime data and spatio-temporal sensor data to show interactive alerts of hotspots, risk profiles and on demand chemical plume models.…”

Section: Living: Cultural Behaviour Public Safety Smart Buildings Memorymentioning

confidence: 99%

Analytics for the Internet of Things

2018

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The Internet of Things (IoT) envisions a world-wide, interconnected network of smart physical entities. These physical entities generate a large amount of data in operation and as the IoT gains momentum in terms of deployment, the combined scale of those data seems destined to continue to grow. Increasingly, applications for the IoT involve analytics. Data analytics is the process of deriving knowledge from data, generating value like actionable insights from them. This article reviews work in the IoT and big data analytics from the perspective of their utility in creating efficient, effective and innovative applications and services for a wide spectrum of domains. We review the broad vision for the IoT as it is shaped in various communities, examine the application of data analytics across IoT domains, provide a categorisation of analytic approaches and propose a layered taxonomy from IoT data to analytics. This taxonomy provides us with insights on the appropriateness of analytical techniques, which in turn shapes a survey of enabling technology and infrastructure for IoT analytics. Finally, we look at some tradeoffs for analytics in the IoT that can shape future research.

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“…Razip et al designed a situation awareness app that provided officers with mobile analysis capabilities for recent crimes in their area [11]. Mobile systems like this are typically easier to use for non-analysts, lower the technological barriers to more powerful forms of analysis, and reduce the need for additional technical staff at already cash-strapped public institutions [2].…”

Section: Related Workmentioning

confidence: 99%