Capacitance measurement for classification of snow packs to estimate avalanche risk

增加了滑雪者、雪地摩托车手和产业工人进入雪崩多发地带的机会 偏远地区每年都会发生许多灾难性事件和人员伤亡。创建一种可以 告知用户雪崩的风险，考虑到雪和天气条件，可以防止此类事件和 死亡。弗雷泽仪器有限公司开发了一款手持和易于使用的工具，可以解决即时的 业余爱好者和专业人士在某种程度上都需要，但他们目前正在追求一种 更先进的积雪分析设备，称为AvyStick，可以可靠地评估更广泛的风险 基于涉及的大多数主要参数的场景。集成了许多电子传感器，用于 对雪坑数据的测试和分析，新的AvyStick设备将帮助偏远地区的用户做出决定 制定滑雪地形是否安全不受雪崩影响的过程。 该项目的目标是开发一种小型化的积雪传感器，它可以测量重要的 利用积雪在不同层的电容特征，更准确地识别积雪的特性。 具体地说，弗雷泽仪器将与纳吉兰的研究实验室合作，将高度敏感的 基于电容的芯片实验室探头及其定制的硬件和软件集成到AvyStick中 提高了它的稳健性和准确性。拟议的研究将旨在开发适当的传感器，该传感器 在测量重量(含水率的百分比)并将其与 各种类型的雪的密度。这项技术将被应用到手掌大小的设备中，以节省 用户花费大量时间进行雪崩分析，从而提高了个人能够处理的数据的数量和质量 在评估过程中获得。

Increased backcountry access by skiers, snowmobilers and industrial workers to avalanche-prone terrain in remote regions has led to numerous catastrophic events and fatalities each year. Creating a device that can inform its users about the risk of avalanche given the snow and weather condition can prevent such events and deaths. Fraser Instruments Ltd. has developed a handheld and easy-to-use tool that addresses the immediate need of both amateurs and professionals to some extent, but they are currently pursuing the development of a more advanced snowpack analysis device called AvyStick that can reliably assess the risk in much broader scenarios based on most dominant parameters involved. Incorporating numerous electronic sensors for the testing and analysis of snow pit data, the new AvyStick device will aid backcountry users in the decision making process of whether or not the skiable terrain is safe from avalanches. The objective of the proposed project is to develop a miniaturized snow sensor that can measure important properties of snow much more accurately using the capacitance signature of snowpack at different layers. Specifically, Fraser Instruments will work with Najjaran's research laboratory to incorporate highly sensitive capacitance-based lab-on-chip probes as well as its customized hardware and software into AvyStick to increase its robustness and accuracy. The proposed research will aim to develop the appropriate sensor, which can achieve a less than 5% error when measuring the weight (a percentage of water content) and relating it to the density of various types of snow. The technology will be implemented into a palm-sized device to save users time with their avalanche analysis thereby improving the quantity and quality of data an individual is able to acquire during assessment.