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| Content Provider | ACM Digital Library |
|---|---|
| Author | Artigas, Francisco Ae Chun, Soon |
| Abstract | This study presents a Sensor Network based Tide Gate Monitoring System (SensorTGMS) that automatically collects the real-time water levels at tide gates in the New Jersey Meadowlands District where ninety percent of which lies within two feet of the high water mark. We report our experience of developing the SensorTGMS, and how the real-time water level data from the sensor-enabled tide gates provide water level alerts for government officials and citizens for planning evacuations and allocating resources by identifying risk areas in timely manner. The data, augmented with the social media data shared by citizens on their flood incident episodes can provide real-time situation awareness and promote community-based incident management during and after a disaster. Additionally, the SensorTGMS data supports the objective unbiased account of the progression of flood events. The animated visualization of the water levels over a time line can be a powerful tool for understanding where and how residents and infrastructure were affected by a high energy rain event and/or a tidal surge. This objective data captured by the system can be used as a forensic tool for understanding the weak points of coastal defenses and to assess the magnitude of the flood damages. |
| Starting Page | 277 |
| Ending Page | 278 |
| Page Count | 2 |
| File Format | |
| ISBN | 9781450320573 |
| DOI | 10.1145/2479724.2479771 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2013-06-17 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Superstorm sandy Forensic analysis Water level Tide gate monitoring system Water quality Emergency management Sensor network Hurricane Hurricane damages Flood alerts |
| Content Type | Text |
| Resource Type | Article |
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