基于gis的犯罪可视化框架

Jaichandran R, S. Jagan, S. Khasim, Logeshwari Dhavamani, V. Mathiazhagan, Dilip Kumar Bagal
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引用次数: 1

摘要

在过去的几十年里,地理信息系统技术在一个永无止境的范围内蓬勃发展。在当今时代,高维高光谱数据的可视化是一项不可或缺的任务,而GIS只是一个实际体验可视化的平台。此外,犯罪是一个前所未有的事件,分析犯罪他们存在许多技术,但我们仅限于采用少数技术和GIS是其中之一。由于特定地点的犯罪数据是犯罪分析的更好数据,因此我们更倾向于使用GIS技术进行制图和可视化。本文重点研究了利用GIS技术对犯罪数据进行可视化处理,并提出了一个基于后端深度学习的未来犯罪分析框架。在犯罪数据集上进行的实验显示了基于数据集的特定区域的犯罪热点的可视化。整个工作流程是GIS技术对犯罪热点检测的结果。进一步,提出了深度学习的本质是犯罪实时可视化的未来研究方向,以便在犯罪发生之前进行检查。最后,通过适当的实验,提供犯罪热点映射作为可视化和分析的输出。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Crime Visualization using A Novel GIS-Based Framework
Past decades have experienced the rage of GIS technology in a never-ending scope. In today’s era, visualization of high-dimensional hyperspectral data is an indispensable task and GIS is simply a platform to practically experience the visualization. Furthermore, crime is an unprecedented event and to analyze crime their exists many technologies but to visualize it we are limited to adopt a few technologies and GIS is one of those few. Since crime data which are location-specific acts as a better data for crime analysis, we prefer GIS technology for mapping and visualization. This paper focuses on visualization of crime data using GIS technology and proposes a framework for futuristic crime analysis with the aid of deep learning acting at the backend. The experimentation performed over crime dataset presents the visualization of crime hotspots over a specified region basing on the dataset. The entire workflow is mentioned as a consequence of GIS technology over crime hotspot detection. Furthermore, the essence of deep learning is proposed as a future research direction for the real-time visualization of crime so that it can be checked before it happens. Finally, this paper provides the crime hotspot mappings as the output for visualization and analysis through proper experimentation.
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