SBIR Phase I: Computer Aided Policing (CAP) Software: An Agent-Based Decision Making Tool for Law Enforcement

SBIR 第一阶段：计算机辅助警务 (CAP) 软件：基于代理的执法决策工具

• 批准号: 1415710
• 负责人: MARIA FONOBEROVA
• 金额: $ 14.98万
• 依托单位: AIMDYN, INC
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-07-01 至 2015-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1415710&HistoricalAwards=false
• 关键词: SBIR; Phase; Computer; Aided; Policing

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is in the field of predictive policing, with broader applications to crime and terrorism-fighting efforts. The product will be the first software to assimilate real-time crime data and provide dynamic model-based forecasting of policing resources necessary to fight criminal activity in specific locations within a city. Over a third of local police agencies in the US with 100 or more officers have implemented a program similar to Compstat (crime information and record management software), which shows their interest in computer-aided policing. The proposed software will be an independent product, but compatible with such current police software tools. Expansions for anti-terrorist applications are envisioned. This Small Business Innovation Research Phase I project will address the development of a gang activity agent-based model, from which a software tool for law enforcement decision making - "Computer Aided Policing" (CAP) - will be developed. An agent-based model of gang activity, which will include individual behavior of an agent or a group in interaction with other agents or groups, as well as an individual's reaction to regulatory, economic and other societal pressures, will be developed based on criminology theory and practical experience. Data management and data mining techniques will be used for development and validation of the agent-based model. Using data assimilation, real-time observations will be incorporated into the model. Tools that enable rapid and automated visualization and analysis of simulation results and the optimization of force deployment for crime mitigation will be developed. This model-based development will be first-of-a-kind in computational social science and will go well beyond the current state of the art in predictive policing.

这个小企业创新研究（SBIR）第一阶段项目的更广泛影响/商业潜力是在预测性警务领域，更广泛地应用于犯罪和打击恐怖主义的努力。该产品将是首个吸收实时犯罪数据的软件，并提供基于动态模型的警务资源预测，以打击城市内特定地点的犯罪活动。在拥有100名或更多警官的美国地方警察机构中，超过三分之一的机构已经实施了类似于Compstat（犯罪信息和记录管理软件）的程序，这显示了他们对计算机辅助警务的兴趣。拟议的软件将是一个独立的产品，但与现有的警察软件工具兼容。还设想了反恐应用的扩展。“小型企业创新研究”第一阶段项目将致力于开发一个以帮派活动代理人为基础的模型，并据此开发一个执法决策的软件工具——“计算机辅助警务”（CAP）。将根据犯罪学理论和实践经验开发一个基于代理人的帮派活动模型，该模型将包括一个代理人或一个团体与其他代理人或团体相互作用中的个人行为，以及个人对监管、经济和其他社会压力的反应。数据管理和数据挖掘技术将用于开发和验证基于代理的模型。利用数据同化，实时观测将被纳入模型。将开发能够对模拟结果进行快速和自动化可视化和分析以及优化部队部署以减轻犯罪的工具。这种基于模型的开发将是计算社会科学领域的首创，并将远远超出预测警务的当前技术水平。