Zusammenfassung
This paper presents a forecasting model designed using WSNs( Wireless Sensor Networks) to predict flood
in rivers using simple and fast calculations to provide real-time results and save the lives of people who
may be affected by the flood. Our prediction model uses multiple variable robust linear regression which is
easy to understand and simple and cost effective in implementation, is speed efficient, but has low resource
utilization and yet provides real time predictions with reliable accuracy, thus having features which are
desirable in any real world algorithm. Our prediction model is independent of the number of parameters,
i.e. any number of parameters may be added or removed based on the on-site requirements. When the
water level rises, we represent it using a polynomial whose nature is used to determine if the water level
may exceed the flood line in the near future. We compare our work with a contemporary algorithm to
demonstrate our improvements over it. Then we present our simulation results for the predicted water level
compared to the actual water level.
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