Flash-floods develop at space and time scales that conventional observation systems were not able to monitor for rainfall, stream flow and sediment discharge. This condition resulted in greater casualties and tremendous economic losses. One of the regions in Indonesia affected by the flash floods was Aceh Besar Regency. It was located in Krueng Teungku watershed. The flash floods were recurring events, which occurred in 1987 and 2000. The disaster reocurred on January 2, 2013 at 19:30P.M. with the huge impact.
Eliminating variables during a flash flood can actually make it quite predictable. And one major variable before a flash flood is water sheds. A watershed, also known as a drainage basin, is an area of land where all water drains to a central point like a lake, river, or stream. When rain sweeps over a surface, it will eventually make its way to that central point. And before a flash flood if these water bodies are left unchecked, the will play a major role during a potential disaster.
Potential disaster due to flash floods can be averted using potential data from watersheds in the area. I propose an IoT nod comprising of the in-bulit sensors in the which has the ability to transmit data from these watersheds. The IoT nods transmit data using the inbuilt LoRaWAN capable radio which make the transmission of data between the console easier using a centralized LoRaWAN network.My system utilizes the inbult sensors in X-NUCLEO-IKS01A3 which provides data on the surrounding humidity. The water levels in the local watersheds are measured using AS7263 NIR which helps in measuring the water level, as near-infrared spectral bands are strongly absorbed by water, yet reflected by land. The data from the nodes are transmitted with the help of a LoRaWAN network making it highly reliable during extreme weathers.
To run the device using the AAA battery supply, you will need to remove (SB3 NRST) a resistor on the underside of the board.
ST X-NUCLEO-IKS01A3 has on board humidity and pressure sensor which helps in detecting the presence of rainfall in the location.
The sensor on the AS7263 NIR provides multi-spectral sensing in the NIR wavelengths from approximately 610nm to 860nm with the full width at half maximum (FWHM) of 20nm. Making it optimal for the project.
The nodes are placed strategically on vulnerable water bodies that has previous history of flooding. The data from the nodes are transmitted to the Helium console, this data is then integrated with mydevices cayenne using AWS IoT.
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