“IOT Based Rainfall Monitoring System Using WSN Enabled Architecture”

The effect of climate change and human activities ends in a chain of risky phenomena, inclusive of landslides and flood. The environmental problems are also a captious part of human’s quality of life and the advancement of civilization. Old methods of monitoring the environmental parameters which as physically receiving information rainfall data from stations can be brutal and inhibiting monitoring required for careful imposition. This paper makes specialty of a flexible and efficient WSN for detecting rainfall-induced landslides. WSN which offer the high quality rainfall monitoring at very cheap rate in terms of labor invested and capital. This paper includes the WSN-enabled architecture for rainfall monitoring system to transmit and collect real time data using GPRS (General Pocket Radio Service) via a cellular network. The data is sent from remote stations to the web server known as Weather Underground. Contribution work is an approach is bandwidth compressed waveform signal for increasing the number of connected devices Performance analysis using SVM machine learning classifier for prediction of rainfall.