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

小型企业创新研究(SBIR)第一阶段项目的更广泛影响/商业潜力是减少建筑环境和自然环境中的伤害、财产损失、运营成本和责任。过多的雪、雨、风和地震活动会产生高结构负荷，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诸如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变得更加常见和不可预测。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60万座公路桥中，有4.5万座存在结构缺陷。山体滑坡造成的物理破坏造成了35亿美元的修复费用，并导致每年25至50人死亡。由于微小的结构运动往往发生在损坏甚至灾难性故障之前，因此在关键位置检测和监控这些运动并向任何使用手机或计算机的用户发送警告的能力具有巨大的社会效益。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，以测量和记录各种基础设施和地理特征中的运动。对结构运动的早期预警有助于降低风险，防止不必要的损害，启动疏散，并确保居住者的安全。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，测量商业屋顶的移动，就像从高雪和风荷载下看到的那样。现有的灾害预测系统价格昂贵，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程序服务器，在那里将创建一个算法来分析和显示地理位置数据。必要时，会通过短信系统(短信)和电子邮件向用户发送警报，指明问题的位置和严重程度。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造一个稳定的低气动阻力的外壳是必要的。因此，一种新型的混合能源将执行额外的系统功能，并将对输出效率进行评估。为了减少对电池的需求，将开发算法，指示单位在活动较少的时期保持“省电模式”，然后在检测到或预期运动时切换到“高保真模式”，例如在风暴或地质事件期间。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势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.