Designing Smart and Secure Communities: from Sensors to Risk-based Reasoning

这个为期五年的计划侧重于使社区安全的概念和技术，包括人类生物识别和人工智能传感器。这项新兴研究的核心是基于风险的概率融合数据，如人类生物特征（例如，面部或步态），属性（如步态类型）和上下文数据（位置，环境）。该计划的动机是需要实现安全和智能，并平衡它们以解决隐私问题。该计划有四个主要目标：1.开发一个基于机器推理的框架，也称为推理，系统级决策方法。在我们的方法中的决策风险进行评估，使用概率推理。然后，框架还将解决隐私方面的问题，这实际上可以通过使用上下文数据和通过强调行为和属性生物识别来实现去个性化来大大增强。2.进一步扩展概率推理理论，开发了一个多度量推理引擎，用于处理生物特征感知和上下文数据的不确定性。多度量推理引擎是基于概率因果模型与新的集成机制的多个度量，包括点，区间和模糊概率，以及基于Dempster-Shafer方法的冲突解决。这将成为基于风险的决策框架的核心。3.为实际应用提出概念验证解决方案和原型，例如：a）安全可靠的城市，公共交通枢纽，公共活动以及公共建筑。一个例子是该小组目前开展的试点项目，即开发智能避难所出入信息亭，对医疗紧急情况和安全威胁进行基于风险的综合评估。B）自动过境基础设施的风险评估，包括隐藏武器探测。一个例子是与一个工业合作伙伴开始的项目，对使用有和没有隐藏物体的身体指标的各种场景进行基于风险的分析。c）在医疗保健、康复和辅助生活中对生物识别技术进行基于风险的监测。特别地，所提出的多度量推理引擎将被应用于术后患者的监测和风险推理，以及老年人福尔斯风险的预测。4.实施HQP培训和教育计划，包括研究生的行业实习以及高年级本科课程中的实践研究和设计部分，让本科生参与研究，并促进学生的国际合作研究。从战略角度来看，该计划将有助于（1）推进民用和军用安全应用的计算机辅助系统，（2）开发下一代风险评估工具。(3)在学术和工业部门的合作中整合加拿大的研发人员。

This five-year Program focuses on the concepts and technologies that make a community secure, including sensors of human biometrics and artificial intelligence. The core of this emerging research is a risk-based probabilistic fusion of data such human biometrics (for example, face or gait), attributes (such as gait type), and contextual data (location, environment). This program is motivated by the need to achieve security and intelligence, and to balance them to address privacy aspects. This Program has four main goals: 1.To develop a framework that is based on machine reasoning, also known as inference, approach to system-level decision-making. The risks of decision-making in our approach are assessed using probabilistic inference. Then framework will also address the privacy aspects, which can actually be greatly enhanced through usage of contextual data and de-personalization by emphasizing on behavioral and attributed biometrics. 2.To further extend the theory of probabilistic inference by developing a Multi-metric Inference Engine that deals with uncertainty of biometric sensory and contextual data. The Multi-metric Inference Engine is based on probabilistic causal models with novel integrated mechanism for multiple metric including point, interval, and fuzzy probabilities, as well as conflict resolution based on Dempster-Shafer approach. This will become the core of the risk-based framework for decision-making. 3.To propose the proof-of-concept solutions and prototypes for the practical applications such as: a)Safe and secure cities, mass-transit hubs, public events, as well as public buildings. An example includes the current pilot project conducted in the group, on developing smart shelter access kiosks with integrated risk-based assessment of medical emergency and security threats. b)Risk assessment in automated border crossing infrastructure including concealed weapon detection. An example is the project started with an industrial partner, on risk-based analysis of various scenarios that use body metrics with and without concealed objects. c)Risk-based monitoring of biometrics in healthcare, rehabilitation, and assisted living. In particular, the proposed Multi-metric Inference Engine will be applied to monitoring and risk inference for post-surgery patients, and prediction of risk of falls in the elderly. 4.To implement an HQP training and educational plan which incorporates industry internships for graduate students as well as practical research and design component in senior undergraduate curriculum, involves undergraduates in research, and promotes student international collaborative research. From a strategic perspective, this Program will contribute to (1) advancing in computer-assisted systems for both civil and military security applications, (2) developing of future generation risk assessment tools. (3) integrating the Canadian R&D workforce in collaboration within the academic and industrial sectors.