SBIR Phase I: Algorithms and Visualization Techniques for the Detection of Geographic Aberrations in Crime (GIS)

SBIR 第一阶段：犯罪地理畸变检测算法和可视化技术 (GIS)

• 批准号: 0637589
• 负责人: M. Cecelia Buchanan
• 金额: $ 10万
• 依托单位: Azavea Inc
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-01-01 至 2007-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0637589&HistoricalAwards=false
• 关键词: SBIR; Phase; Algorithms; Visualization; Techniques

This Small Business Technology Transfer Phase I research project tests the feasibility of software tools that leverage spatial statistics to enable police personnel to test their theories of criminality against data collected in the day-today activities of policing. Specifically, the research will validate the feasibility of innovative software tools that scour the historic data of a police department, search for geographic aberrations expected by the theories or 'hunches' put forth by crime analysts, and apply spatial statistics to confirm or deny the supposition. Preventing crime is a more sophisticated task than simply mapping incidents or arrests and deploying resources accordingly. The ability to analyze crime spikes, or unusual aberrations that occur in concentrated geographic areas, is an innovation in policing which holds the potential to enhance the organizational capacity of police departments across the country. The project will also study the development of a software interface that enables everyday crime analysts, police officers, and police captains to perform spatial analysis of crime by applying spatial statistics to test 'hunches'. In addition to this product's obvious market, i.e. law enforcement, there are applications in all levels of government. In addition, there is a market in 'special' law enforcement agencies such as The Department of Homeland Security, the Coast Guard or Military Police. Of the roughly 250 municipalities with populations of over 100,000 people, each has police departments that would find this system of use. The tools will assist police personnel to do a better job, and the efficiency gains will result in better policing and other societal benefits. Because 'Hunches' are not limited to policing, the algorithms and technologies developed in this research project will be applicable to other datasets that have the same sort of informational pattern - points of time occurring in space and time, such as consumer buying patterns or epidemiology.

这个小型企业转移阶段研究项目测试了软件工具的可行性，这些软件工具利用空间统计数据使警察人员能够测试他们的犯罪理论，以针对在警务日期活动中收集的数据。具体而言，该研究将验证创新的软件工具的可行性，这些工具可以搜索警察局的历史数据，寻找犯罪分析师提出的理论或“ hunches”期望的地理畸变，并应用空间统计数据以确认或否认假设。预防犯罪是一项更复杂的任务，而不是简单地绘制事件或逮捕和相应地部署资源。在集中地理区域中分析犯罪峰值或异常畸变的能力是警务的创新，具有提高全国警察部门的组织能力的潜力。该项目还将研究一个软件界面的开发，该软件界面可以使日常犯罪分析师，警察和警察队长通过应用空间统计数据测试“ Hunches”来对犯罪进行空间分析。除了该产品的明显市场（即执法部门）外，所有级别的政府都有应用。此外，“特殊”执法机构（例如国土安全部，海岸警卫队或军警察）还有一个市场。在大约250个市政当局中，有超过100,000人的人口，每个城市都有警察部门可以找到这种使用系统。这些工具将帮助警察人员做得更好，效率提高将带来更好的警务和其他社会利益。因为“预感”不仅限于警务，因此该研究项目中开发的算法和技术将适用于具有相同信息模式的其他数据集 - 时空中发生的时间点，例如消费者购买模式或流行病学。