IOT BASED FLOOD MONITORING USING ARTIFICIAL NEURAL NETWORK
Author(s):
SWATHI.D, SNEHAA.S, RAGAPRIYA.R, PRIYANKA.P
Keywords:
flood forecasting, Internet of Things, Wireless Sensor Network, Digital Image Processing, Artificial Neural Network.
Abstract
Flood is the most common natural disaster which causes damage to the life and economy. This paper work focuses on the flood forecasting system using Internet of Things(IOT) and Artificial Neural Network(ANN). Along with this the Digital Image Processing technique is implemented to save the life of the victims affected by the flood. The algorithmic approaches have been proved as better flood forecasting scheme and it is used for data analysis in this project. This design incorporates certain monitoring features like water level, humidity, pressure, water flow and rainfall. These parameters for predicting the flood are determined by various sensors and the sensor aggregates data’s and these data’s are collected by the Wireless Sensor Network(WSN) from controller and it is transferred by the GPS to Internet Processing Centre(IPC). The IPC alerts the people community through siren. After flood, the digital image processing technique detects the victims affected by flood depending on the factors like body positioning and the surrounding environment. ANN is used for better accuracy. This information is passed to rescue team using IOT. The results of the analysis which are also appended show a considerable improvement over the currently existing methods.
Article Details
Unique Paper ID: 145369

Publication Volume & Issue: Volume 4, Issue 9

Page(s): 348 - 353
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