Real-Time Flood Supervising and Forecasting using Simulated Neural Network


Authors : Vinaya Kumar S R, Geetha Kumari T M, Harshadha M, Meghana R

Volume/Issue : Volume 5 - 2020, Issue 3 - March

Google Scholar : https://goo.gl/DF9R4u

Scribd : https://bit.ly/3ecLcJG

As the monsoon kicks in, brings the hope to the farmers for good yield, where as darker side of it can be disastrous, FLOODS. They have adverse effect both economically and socially across globe while some artificial measures are been taken to overcome one of them like dams, How long do they could prevent? Here is our help to the society, where in by using the technology the social life could be saved. Our design of the project mainly concentrates on supervising characteristics like level of water, humidity, temperature and rainfall. These parameter help vitally in flood forecasting. As the parameters are aggregatted and are collected by using from the controller and it sends the message over the internet. This affects the locals. After flood, also there is drastic effect, the victams can be detected by image processing are immersed. For the greater precision purpose ANN is used and further the information is passed to the rescue team near by via IOT. Along with this digital image processing technique is implemented to save life of victims. Our project mainly focuses on the flood forecasting and detecting the victams using IOT and Artificial neural network.

Keywords : Floods, Artificial Neural Network, Internet of Things, Digital Image Processing

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Paper Submission Last Date
31 - May - 2022

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