Sensors: Strategic Design and Tactical Operation of Surveillance Sensor Systems for Ports and Waterway Security

这个传感器和传感器网络（NSF 05-526）项目的目标是为监测传感器系统的战略设计和战术操作建立一个知识库，以帮助确保港口和水道的强大安全，特别是处理未经授权的小型船只，这些船只可以轻松进入敏感的目标。战略设计需要规定传感器的类型、每种类型的数量和每个传感器的位置;战术行动需要检测异常船只行为并分析系统容错能力。 战略设计的方法包括制定数学模型，设计专门的算法来解决大规模的实例，并通过计算测试算法。 检测异常行为的方法需要设计一个广义贝叶斯框架和多变量统计监测程序，以确定“正常”的行为，使用历史数据来推断入侵者的意图，从位置和速度。 容错分析的方法涉及图论和组合数学。如果成功，社会将受益于休斯顿船舶通道和全国各地的港口和水道以及工业工厂，核电站，办公楼和国家纪念碑等敏感设施的改进监视系统所提供的增强的国土安全。 该项目将通过培训参与的学生和提供用于教学和研究的计算机程序来促进多学科教学和培训。 该项目将通过激励学生在相关领域从事职业，并让少数民族中学的教师参与进来，为研究和教育的基础设施做出贡献。 它将促进学习，因为在各大学讲授成果。 将积极从代表性不足的群体中招募参与者，以促进他们的社会经济福利。 传播计划将广泛提供研究结果，通过在专业会议上发言、在权威期刊上发表文章以及在大学课程中授课，为培训分析师、工程师和安全当局做出贡献。

The objective of this Sensors and Sensor Networks (NSF 05-526) project is to initiate a knowledge base for the strategic design and tactical operation of surveillance sensor systems that help assure robust security in ports and waterways, especially to deal with unauthorized, small vessels that can gain easy access to sensitive "targets." Strategic design entails prescribing the types of sensors, the number of each type and the location of each sensor; tactical operations require detecting anomalous vessel behavior and analyzing system fault tolerance. The approach to strategic design involves formulating mathematical models, devising specialized algorithms to solve large-scale instances, and testing algorithms computationally. The approach to detecting anomalous behavior entails devising a generalized Bayesian framework and a multivariate statistical monitoring procedure to determine "normal" behavior using historical data to infer an intruder's intentions from position and velocity. The approach to fault tolerance analysis involves graph theory and combinatorial mathematics.If successful, society will benefit from the enhanced homeland security provided by improved surveillance systems in the Houston ship channel and in ports and waterways throughout the country as well as in sensitive facilities like industrial plants, nuclear power plants, office buildings, and national monuments. The project will promote multidisciplinary teaching and training by training participating students and providing computer programs for teaching and research. It will contribute to the infrastructure for research and education by motivating students to pursue careers in relevant areas and by engaging teachers from minority-serving high schools. It will promote learning as results are taught in various universities. Participants will be actively recruited from under-represented groups to promote their socioeconomic welfare. The plan for dissemination will make results widely available, contributing to training analysts, engineers, and security authorities by presenting at professional conferences, publishing in refereed journals, and teaching at university-level courses.