Development of low-cost sensor suite for fog monitoring

伍德环境和基础设施解决方案公司(下称“伍德环境”)目前正在与各种学术、政府和行业合作伙伴合作，研究改进的技术，以预报加拿大大西洋和包括Grand Banks在内的近海地区的雾。雾预报不是一个简单的问题。过去，雾的预报大多依赖于理论数学模型，现场测量有限。最近，人们正在努力使用广泛的实时、大型无线传感器网络来提高准确性和响应速度。圣母大学项目的一组研究人员最近开始了一项新的倡议，利用研究飞行器上的现场测量来了解雾背后的基本原理和微观物理。*我们在约克大学的研究团队建议扩展我们目前的工程研究，以设计和制作一种低成本、集成、可重新配置的传感器套件，以补充Wood Environment正在进行的测量和预测雾的努力。在过去的11年里，我们的研究一直专注于为星载和机载测量单元设计低成本的解决方案，以增强对各种大气成分的实时监测。我们的研究专长主要集中在以空间环境为特征的商业电子产品的纳米卫星技术方面。基于这一经验，我们有信心为Wood Environment提供创新和可靠的工程解决方案，以补充他们目前在雾预测方面的研究。**通过拟议的Engage计划，我们将设计、原型和表征传感器套件，该套件将构成传感器网络的基础--这是在很长一段时间内提供大范围测量技术的自然步骤。这项拟议的研究直接支持伍德环境公司目前提高其雾预测模型准确性的努力。*

Wood Environment and Infrastructure Solutions (referred to as 'Wood Environment' hereinafter) is currently investigating improved technologies to forecast fog in Atlantic Canada and offshore areas including Grand Banks in collaboration with various academic, government and industry partners. Fog forecasting is not a simple problem. In the past, most of the fog prediction heavily relied on theoretical mathematical models with limited field measurement. More recently, efforts are being made to improve the accuracy and responsiveness using extensive real-time, large network of wireless sensors. A team of researchers at the University of Notre Dame program recently embarked on a new initiative to understand the fundamentals and microphysics behind fog using field measurement onboard research vehicles. ** Our research team at York University is proposing to extend our current engineering research to design and prototype a low-cost, integrated, reconfigurable sensor suite to complement Wood Environment's ongoing effort to measure and predict fog. In the past 11 years, our research has been focused on designing low-cost solution for space-borne and air-borne measurement units to enhance real-time monitoring of various atmospheric constituents. Our research expertise is mostly in the nanosatellite technologies where commercial electronics are characterized for the space environment. Building on this experience we are confident that we can offer innovative and reliable engineering solution for Wood Environment that can complement their current research on fog-prediction.** Through the proposed Engage program, we will design, prototype and characterize a sensor suite that will form a basis for network of sensors - a natural step in providing measurement techniques over a large area over long period of time. The proposed research is in direct support of Wood Environment's current efforts to improve the accuracy of their fog prediction model.****