Low-Cost Acoustic Sensor Array for Building Geometry Mapping using Echolocation for Real-Time Building Model Creation
Low-Cost Acoustic Sensor Array for Building Geometry Mapping using Echolocation for Real-Time Building Model Creation
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发表时间：
2017
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通讯作者：
T. A. Sevilla;W. Tian;Y. Fu;W. Zuo
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作者：
T. A. Sevilla;W. Tian;Y. Fu;W. Zuo
室内环境建模和仿真结果准确性的验证通常需要昂贵的传感器和操作员收集的高质量数据。在处理建筑改造时，特别是在获取建筑几何形状以供以后用于气流、围护结构或人与建筑交互模拟时，这成为一个问题。因此，我们开发了一种低成本声学传感器阵列（不到 70 美元），利用回声定位自动检测和绘制建筑物几何形状。我们这项研究的重点是让建筑建模者获得现有建筑物的几何和空间信息。底层硬件使用开源计算机视觉库，它允许多核处理，并启用底层异构计算平台的硬件加速，使我们能够在多个设备之间进行分布式计算。同样，当集群设备用于聚合数据收集以便在大型测绘项目中使用时，这非常有用。总的来说，这项研究为该领域的未来工作提出了一个原型。
Validation of result accuracy for indoor environment modeling and simulation usually requires high-quality data collected by expensive sensors and human operators. This becomes a problem when dealing with building retrofits, specifically when obtaining building geometry for later use in airflow, envelope, or human-building interaction simulations. Thus, we developed a low-cost acoustic sensor array (less than $70) to automatically detect and map building geometry using echolocation. Our focus of this research is to allow building modelers to obtain geometric as well as spatial information of existing buildings. The underlying hardware uses the Open Source Computer Vision Library which allows multi-core processing and enables hardware acceleration of the underlying heterogeneous compute platform, allowing us to perform distributive calculation among multiple devices. Likewise, this is useful when clustering devices for aggregate data collection for use in large mapping projects. Overall, this study proposes a prototype for future work in this field.