RI: Small: Intelligent Compressive Multi-Walker Recognition and Tracking (iSMART) through Pyroelectric Sensor Networks

尽管高成本、数据密集型的多摄像头系统已被广泛用于移动人体跟踪和识别，但热释电红外（PIR）传感器具有成本低、化学稳定性好、对人体热变化的高灵敏度和极低的传感数据吞吐量等诸多优点。本项目实现了一个基于PIR传感器网络（PSN）的智能压缩多步行者识别与跟踪（iSMART）测试平台。iSMART的新颖之处包括三个方面：(1)上下文感知感兴趣区域（RoI）探索，实现了传感器覆盖面积和信息获取分辨率之间的内在权衡。本研究使用严格的数学模型来测量RoI上下文。(2)网络内智能的去中心化推理/学习。本项目开发了一种基于信念传播的分布式推理方案，该方案具有数据到对象的关联，用于连续跟踪和识别多个步行者。它使用基于正交投影的分布式学习来进行传感器校准和特征模型训练。(3)网络化、压缩采样结构和传感协议。该项目扩展了压缩和多路传感理论的最新进展，以指导新型网络传感器接收器模式几何形状和分散传感协议的设计。上述研究工作将导致一种新颖的低成本，高保真的无线分布式传感系统，用于多步行者识别和跟踪。作为视频摄像机系统的替代方案，iSMART系统可以广泛部署到自动监控机场、海关/港口和其他关键的国家基础设施。该项目还将为本科生和研究生提供有趣的智能传感器/传感器网络实践实验和课堂项目。

Although high-cost, data-intensive multi-camera systems have been widely used for mobile human tracking and recognition, the pyroelectric infrared (PIR) sensor has a variety of advantages including dramatically low costs, chemical stability, high sensitivity to human body thermal variation, and extremely low sensory data throughput.This project implements an Intelligent Compressive Multi-Walker Recognition and Tracking (iSMART) testbed based on PIR Sensor Networks (PSN). The novelties of iSMART include three aspects: (1) Context-aware region-of-interest (RoI) exploration to achieve an inherent tradeoff between area of sensor coverage and degree of information acquisition resolution. This research uses strict mathematical models to measure RoI context. (2) Decentralized inference / learning for in-network intelligence. This project develops a belief-propagation-based distributed inference scheme with data-to-object association for continuous tracking and recognition of multiple walkers. It uses orthogonal-projection-based distributed learning for sensor calibration and feature model training. (3) Networked, compressive sampling structures and sensing protocols. This project extends the latest progress in compressive and multiplex sensing theories to guide the design of novel networked sensor receiver pattern geometries and decentralized sensing protocols.The above research efforts will lead to a novel low-cost, high fidelity wireless distributed sensing system for multiple walker recognition and tracking. As an alternative to video camera systems, iSMART systems can be widely deployed to automatically monitor airports, customs / harbors, and other critical national infrastructures. This project will also generate interesting hands-on labs on intelligent sensor / sensor networks and class projects for both undergraduate and graduate students.