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

NetS：小型：协作研究：智能建筑的非各向同性网络传感器部署

• 批准号: 1463722
• 负责人: Shan Lin
• 金额: $ 20.53万
• 依托单位: SUNY at Stony Brook
• 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: 2014-08-11 至 2018-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1463722&HistoricalAwards=false
• 关键词: NeTS; Small; Collaborative; Research; Non

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.

该提案的目的是彻底调查部署非各向同性传感器的智能建筑应用。智能建筑中的各种传感和控制应用需要对人和活动进行准确有效的定位和跟踪。为了实现这一目标，非各向同性的网络传感器部署是必不可少的。该建议解决了一组新的问题所产生的四种类型的传感器的部署：摄像头，绊网，运动传感器和麦克风。这组部署问题将努力实现具有复杂平面图的全传感器覆盖和无线连接，并且涉及以下约束中的一个或多个：（i）使用可见性（相机和绊网）的非各向同性模型，（ii）非重叠感测范围，（iii）用于准确定位的鲁棒2-覆盖。传感器部署问题将严重涉及环境的几何特性（建筑布局），以及传感器的几何特性（非各向同性的传感范围）。从计算几何的思想将被应用到解决这些问题和近似算法与最坏情况下保证理论的严谨性以及实用的算法适用于实施将被开发。一个清晰的理解如何部署传感器的智能建筑系统将允许有效的规划和有效的实践网络传感器部署，以实现高品质的传感所需的各种室内应用。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，由此产生的测试平台将带来令人兴奋的应用，从而显著提高生活质量。将计算几何理论与系统构建实践相结合，丰富了工程课程。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。