NeTS: Small: Collaborative: Non-Isotropic Networked Sensor Deployment for Smart Buildings

本提案的目的是彻底研究智能建筑应用中非各向同性传感器的部署。智能建筑中的各种传感和控制应用需要对人员和活动进行准确、高效的定位和跟踪。为了实现这一目标，非各向同性网络传感器的部署是必不可少的。这一建议解决了由于部署四种类型的传感器而产生的一系列新问题：摄像头、绊线、运动传感器和麦克风。这一系列部署问题将力求在复杂的平面图上实现传感器的全面覆盖和无线连接，并涉及以下一个或多个限制：(i)使用能见度（摄像头和绊网）的非各向同性模型，（ii）不重叠的传感范围，（iii）精确定位的鲁棒2覆盖。传感器部署问题将大量涉及环境的几何特性（建筑布局），以及传感器的几何特性（非各向同性传感范围）。计算几何的思想将应用于解决这些问题，并将开发具有最坏情况保证的理论严谨性和适合实现的实用算法的近似算法。对如何为智能建筑系统部署传感器的清晰理解将允许有效的规划和有效的网络传感器部署实践，以实现各种室内应用所需的高质量传感。对于开发人员来说，这项工作将大大降低设计和构建智能建筑系统的设计和开发成本。对于最终用户来说，最终的测试平台将带来令人兴奋的应用程序，这将显著提高生活质量。将计算几何理论与系统构建实践相结合，丰富了工程课程内容。pi致力于提高女性在计算机科学领域的地位，并为高中生提供研究机会。

The objective of this proposal is to thoroughly investigate the deployment of non-isotropic sensors for smart building applications. Various sensing and control applications in smart building require accurate and efficient localization and tracking of human and activities. To achieve this goal, the non-isotropic networked sensor deployment is essential.This proposal addresses a new set of problems arising from the deployment of four types of sensors: cameras, tripwire, motion sensors and microphones. The set of deployment problems would strive for full sensor coverage and wireless connectivity with a complex floor plan, and involve one or more of the following constraints: (i) Non-isotropic model using visibility (cameras and tripwires), (ii) Non-overlapping sensing range, (iii) Robust 2-coverage for accurate localization. The sensor deployment problem will heavily involve the geometric properties of the environment (building layout), as well as the geometric properties of the sensors (non-isotropic sensing ranges). Ideas from computational geometry will be applied to tackle these problems and approximation algorithms with worst-case guarantee for theoretical rigor as well as practical algorithms suitable for implementations will be developed.A clear understanding on how to deploy sensors for smart building systems will allows for efficient planning and effective practice of networked sensor deployment to achieve the high quality sensing desired by various indoor applications. For developers, this work will significantly reduce the design and development costs for designing and building smart building systems. For end users, the resultant testbed will lead to exciting applications that will significantly improve the quality of life. It also enriches engineering curriculum to integrate the theory of computational geometry with the system building practice. The PIs are committed in improving female presence in computer science and exposure of research for high school students.