Smart Cities Solutions for More Flood Resilient Communities
Smart Cities Solutions for More Flood Resilient Communities
复制标题
为更具抗洪能力的社区提供智慧城市解决方案
DOI：
10.1109/sieds.2019.8735625
复制
发表时间：
2019
期刊：
影响因子：
--
通讯作者：
J. Goodall
中科院分区：
文献类型：
--
作者：
Katie Carlson;Ashif Chowdhury;A. Kepley;E. Somerville;Kevin Warshaw;J. Goodall
有证据表明，由于气候变化，洪水事件正变得更加频繁和严重。这个问题在弗吉尼亚州的诺福克尤其普遍，这里是东海岸海平面上升速度第二高的地方。需要模型和传感创新来实时生成高分辨率的洪水警报，以改善公共安全。还需要新的传感方法来准确测量风暴事件期间的洪水范围，以便这些数据可以用于校准模型。我们的方法创建了一个端到端的建模系统，为诺福克，弗吉尼亚州提供实时洪水预报信息给用户。我们的流程始于通过我们集团的水位传感器收集数据。该设备依靠超声波传感器来测量其与地面的距离如何随着水位上升而变化。然后在将读数传输到持久数据库之前对其进行过滤。来自该传感器的数据与历史洪水数据相结合，存储在本地托管的关系SQLite数据库和云托管的InfluxDB数据库中。本地托管的数据库可用于进一步开发洪水预测模型。云托管的数据库可以在收集数据时存储数据以用于真实的时间分析。目前，该传感器已经在实验室中准确记录了长达10英尺的距离变化，并成功传输了这些读数。对于未来的测试，测量结果将发送到Heroku上托管的静态URL。已经编写了一个Python函数，它以JSON格式读取URL并将数据传输到Influx数据库。另一个Python函数已经编写，它读取包含历史数据的csv并将其转换为正确的格式，然后将其插入SQLite。
There is evidence that flooding events are becoming more frequent and intense as a result of climate change. This problem is especially prevalent in Norfolk, VA which has the second highest rate of sea level rise on the east coast. Model and sensing innovations are needed to produce high-resolution flood warnings in real-time to improve public safety. New sensing approaches are also needed to accurately measure the extent of flooding during storm events so this data can be used to calibrate models. Our methodology creates an end-to-end modeling system for Norfolk, VA to provide real-time flood forecast information to users. Our process begins with data collection through our group's water level sensor. This device relies on an ultrasonic sensor to measure how its distance from the ground changes as water levels rise. Readings are then filtered before they are transmitted to a persistent database. The data from this sensor, combined with historical flood data, are stored in a locally-hosted relational SQLite database and a cloud-hosted InfluxDB database. The locally-hosted database can be used for further development of flood prediction models. The cloud-hosted database can store data as it is collected for real time analysis. Currently, the sensor has accurately recorded changes in distances of up to ten feet in the lab and successfully transmitted these readings. For future testing, measurements will be sent to a static URL hosted on Heroku. A Python function has been written that reads the URL in JSON format and transmits the data to the Influx database. Another Python function has been written that reads a csv containing historical data and transforms it to the proper format, then inserts it into SQLite.
影响因子：
6.4
作者：
J. Sadler;J. Goodall;Mohamed M. Morsy;K. Spencer
通讯作者：
J. Sadler;J. Goodall;Mohamed M. Morsy;K. Spencer
影响因子：
64.8
作者：
Schuerch, Mark;Spencer, Tom;Brown, Sally
通讯作者：
Brown, Sally