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

SBIR 第二阶段：犯罪地理畸变检测算法和可视化技术 (GIS)

• 批准号: 0750507
• 负责人: Robert Cheetham
• 金额: --
• 依托单位: Azavea Inc
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-04-01 至 2011-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0750507&HistoricalAwards=false
• 关键词: SBIR; Phase; II; Algorithms; Visualization

This Small Business Innovative Research (SBIR) Phase II project will further develop HunchLab -- software tools that leverage spatial statistics to enable police personnel to test their theories of criminality against data collected in the day-to-day activities of policing. The preceding Phase I project proved the feasibility of developing HunchLab as a set 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 detect and analyze changes in the geographic patterns of crime and disorder is an innovation in policing which holds the potential to enhance the organizational capacity of police departments across the country. This Phase II project will refine the application and build additional functionality, including alternate workflows for different user types, expanding the alert infrastructure, and building text mining capabilities.The obvious sector that this product will impact is law enforcement at all levels of government. Additionally the successful outcome will impact federal law enforcement agencies and regional crime analysis consortia. There are roughly 250 municipalities with over 100,000 people in them, and these each have police departments that would find this system of use. The tools will be helping thousands of police officers do their jobs better every day. This efficiency will result in better policing, meaning that criminals will be caught more effectively. Criminals cause damage far in excess of the property and medical costs directly attributable to their activity. Perhaps more importantly, the research will form the basis for other products that operate in realms other than law enforcement. The algorithms and technologies developed in the Phase I prototype are transferable to other datasets that demonstrate similar point pattern processes - events with explicit spatial and temporal attributes. Our Phase I process demonstrated a substantial utility in domains other than law enforcement including fraud detection, real estate, sales and public health. The Phase II work plan includes testing with other data sets to refine that software should address these other markets.

这项小型企业创新研究（SBIR）第二阶段项目将进一步开发HunchLab-Hunchlab - 软件工具，这些工具利用空间统计数据使警察人员能够测试其犯罪理论，以针对日常警务活动中收集的数据。第一阶段项目证明了开发HunchLab作为一组创新的软件工具的可行性，可搜索警察局的历史数据，搜索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该假设。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。检测和分析犯罪和混乱地理模式变化的能力是警务方面的一种创新，具有提高全国警察部门的组织能力的潜力。该阶段II项目将完善应用程序并构建其他功能，包括针对不同用户类型的替代工作流程，扩大警报基础架构以及构建文本挖掘功能。显而易见的部门将影响该产品会影响到所有级别的政府执法。此外，成功的结果将影响联邦执法机构和区域犯罪分析财团。大约有250个市政当局，其中有100,000多人，每个人都有警察部门可以找到这种使用系统。这些工具将帮助数千名警察每天更好地做出工作。这种效率将导致更好的警务，这意味着犯罪分子将被更有效地抓住。犯罪分子造成的损害远远超过财产，而医疗费用直接归因于其活动。也许更重要的是，这项研究将构成除执法以外的领域中其他产品的基础。在I期原型中开发的算法和技术可将其传输到其他数据集，这些数据集证明了相似的点模式过程 - 具有显式空间和时间属性的事件。我们的I阶段流程在执法部门以外的领域中表现出了实质性的实用性，包括欺诈检测，房地产，销售和公共卫生。第二阶段的工作计划包括使用其他数据集进行测试，以完善软件应解决其他市场。