SBIR Phase I: Remote IoT Monitoring Network for Early Warning and Measurement of Structural Movements

这个小企业创新研究（SBIR）第一阶段项目的更广泛的影响/商业潜力是减少伤害，财产损失，运营成本，以及在建筑和自然环境中的责任。 过度的雪、雨、风和地震活动会产生很高的结构载荷，可能导致建筑物、桥梁和其他基础设施倒塌。 这些负荷还可能破坏蓄水池和山坡等地理特征的稳定。 日益极端的气候影响和老化的基础设施使这些情况更加普遍和不可预测。 天气事件影响了美国590万座商业建筑和13.7万所学校。 在美国的60万座公路桥中，有4.5万座存在结构缺陷。山体滑坡造成35亿美元的修复费用，每年造成25至50人死亡。 由于小的结构运动往往会导致损坏甚至灾难性的故障，因此在关键位置检测和监测这些运动并向任何使用手机或计算机的用户发出警告的能力具有很大的社会效益。 该项目将导致开发一种低成本、快速安装和直观的无线系统，以测量和记录广泛类别的基础设施和地理特征内的移动。 结构移动的早期预警有助于减轻风险，防止不必要的损害，启动疏散，并保持居住者的安全。这个小型企业创新研究（SBIR）第一阶段团队将建造一系列传感器，测量商业屋顶的运动，就像从高雪和风荷载中看到的那样。 现有的灾害预报系统价格昂贵，操作复杂，和/或提供的数据有限。 该项目中的传感器将使用精密无线电接收器来创建3轴厘米精度的运动数据。 传感器将移动报告给应用服务器，应用服务器将创建算法来分析和显示地理定位数据。 必要时，通过短消息系统（SMS，即，文本）和电子邮件，指出问题的位置和严重性。 成功的一个关键指标将是传感器在金属屋顶等结构上准确运行的能力，这可能会给射频设备带来挑战。 紧凑的设计对于商业可行性和创建具有低气动阻力的稳定外壳是必要的。因此，一种新型的混合能源供应将执行额外的系统功能，并将评估输出效率。 为了减少电池需求，将开发算法，指示设备在低活动期间保持“省电模式”，然后在检测到或预期运动时（如风暴或地质事件期间）切换到“高保真模式”。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to reduce injury, property damage, operating costs, and liability in the built and natural environments. Excessive snow, rain, wind and seismic activity create high structural loads that can lead to the collapse of buildings, bridges, and other infrastructure. These loads can also destabilize geographical features such as water impoundments and hillsides. Increasingly extreme climate impacts and aging infrastructure make these situations more common and unpredictable. Weather events affect 5.9 million commercial buildings and 137,000 schools in the US. Of the 600,000 highway bridges in the US, 45,000 are structurally deficient. Landslides result in $3.5 billion in repair costs due to physical damage and result in 25 to 50 deaths annually. Since small structural movements often precede damage and even catastrophic failure, the ability to detect and monitor these motions at key locations and deliver warnings to any user with a cell phone or computer is of great societal benefit. This project will lead to the development of a low cost, rapidly installed, and intuitive wireless system to measure and record movements within broad categories of infrastructure and geographic features. Early warning of structural movements helps mitigate risk, prevent unnecessary damage, initiate evacuations, and keep occupants safe. This Small Business Innovation Research (SBIR) Phase I team will construct a series of sensors that measure commercial rooftop movement like that seen from high snow and wind loading. Existing disaster forecasting systems are expensive, operationally complex, and/or provide limited data. The sensors in this project will use precision radio receivers to create 3 axis centimeter-accurate movement data. Sensors report movements to an application server where an algorithm will be created to analyze and display geo-located data. When necessary, alerts are sent to users via Short Message System (SMS, i.e., text) and email, indicating the location and severity of the problem. A key metric to success will be the ability for the sensors to operate accurately on structures such as metal-decked rooftops which can create challenges for radio frequency devices. A compact design is necessary for commercial viability and to create a stable enclosure with low aerodynamic drag. Therefore, a novel hybrid energy supply will perform additional system functions and will be evaluated for output efficiency. To reduce battery demands, algorithms will be developed instructing units to remain in “power saving mode” during periods of low activity then switch into “high fidelity mode” when motion is detected or expected, such as during storms or geological events.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.