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Advanced Real-Time Monitoring of Rainfall Using Commercial Satellite Broadcasting Service: A Case Study.

Gian Luigi Gragnani1, Matteo Colli1,2, Emanuele Tavanti1

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Summary
This summary is machine-generated.

A new IoT-based sensor network offers real-time rainfall monitoring for sustainable water resource management. This cost-effective system strategically covers critical areas, outperforming traditional weather radars and rain gauges.

Keywords:
meteoric flow watersnowcastingrainfall monitoringsensor networks

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Area of Science:

  • Environmental Science
  • Hydrology
  • Sensor Technology

Background:

  • Effective management of meteoric water flow is crucial for sustainable territorial development.
  • Traditional monitoring methods like weather radars and rain gauges have limitations in coverage and cost.
  • There is a need for advanced, real-time systems for rainfall monitoring.

Purpose of the Study:

  • To introduce and discuss a novel system for real-time monitoring of rainfall and cumulated rainfall.
  • To demonstrate the system's capability in covering safety-critical 'hot spots' with minimal sensors.
  • To evaluate the system's cost-effectiveness in deployment and maintenance compared to traditional devices.

Main Methods:

  • Implementation of an Internet of Things (IoT) based Sensor Network.
  • Strategic placement of a small number of sensors in areas lacking traditional coverage.
  • Pilot plant implementation at the Monte Scarpino landfill (Genoa, Italy).

Main Results:

  • The IoT sensor network provides real-time rainfall and cumulated rainfall data.
  • The system effectively covers critical areas with a reduced number of sensors.
  • Performance assessment showed comparable or superior data to polarimetric weather radar and traditional rain gauges.

Conclusions:

  • The developed IoT sensor network is a viable and cost-effective solution for real-time rainfall monitoring.
  • This system enhances the sustainable management of surface and subsurface water resources.
  • The technology offers a valuable alternative to traditional monitoring methods, especially in underserved areas.