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

这一小型企业创新研究(SBIR)第二阶段项目将进一步开发HunchLab，这是一种利用空间统计的软件工具，使警察人员能够根据在日常警务活动中收集的数据来检验他们的犯罪理论。之前的第一阶段项目证明了将HunchLab开发为一套创新的软件工具的可行性，该工具可以搜索警察部门的历史数据，搜索犯罪分析师提出的理论或预感所预期的地理偏差，并应用空间统计学来证实或否认这一假设。预防犯罪是一项比简单地绘制事件或逮捕情况并相应地部署资源更为复杂的任务。发现和分析犯罪和骚乱地理格局变化的能力是警务方面的一项创新，有可能加强全国警察部门的组织能力。此第二阶段项目将优化应用程序并构建附加功能，包括针对不同用户类型的替代工作流、扩展警报基础设施和构建文本挖掘功能。此产品将影响的明显部门是各级政府的执法部门。此外，成功的结果将影响联邦执法机构和区域犯罪分析联盟。大约有250个城市，人口超过10万，每个城市都有警察部门，他们会发现这种系统的使用。这些工具将帮助数千名警察每天更好地完成他们的工作。这种效率将带来更好的治安，这意味着罪犯将被更有效地抓获。犯罪分子造成的损失远远超过直接归因于其活动的财产和医疗费用。也许更重要的是，这项研究将为在执法以外的领域运营的其他产品奠定基础。在第一阶段原型中开发的算法和技术可以转移到其他展示类似点模式过程的数据集-具有明确的空间和时间属性的事件。我们的第一阶段流程在执法以外的领域展示了实质性的效用，包括欺诈检测、房地产、销售和公共卫生。第二阶段工作计划包括使用其他数据集进行测试，以完善该软件应针对这些其他市场的情况。

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.