“Floodie”: Smart Flood Detection and Warning System

Registration ID: IJNRD_181949

Published ID: IJNRD2207078

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Jayakantha J.H.C.M, Kumarasiri A.D.V.I.S, Medaela M.P.G.P.M.G, Perera W.A.D.C.T, Dammika De Silva

Internet of things (IoT), Arima Model, Facebook Prophet, Gray Model, Convolutional Neural Network

Floods are the most common natural disaster in the world. The main reason for flooding is the heavy rain. Sri Lanka also faces floods almost in every year. Floods cause great damage not only to human lives but also properties. Due to this, Sri Lankan government spends a lot of money to provide relief to those affected by the floods. The main reason for this situation is, the lack of a proper system for predicting rainfall and floods in Sri Lanka and informing the public about it. As a solution, this research proposes to create a proper weather forecasting and water level forecasting system and visualize the flooding areas in a google map. As well as this research propose a chatbot to give significant weather data to the public. It is complicated to predict the rainfall accurately with changing climatic conditions. For the predictions, Machine Learning are used normally. In this research Long Short-Term Memory (LSTM), Facebook prophet, gray model, Convolutional Neural Network and Arima model are used as forecasting models. In addition, create a device, which connected with IoT sensors, and it retrieves the real-time weather data and flood water levels. Then all real-time data which is taken from IoT devices are monitored in a web application. And in the web application, it visualizes the flooding areas in a google map. Then, after executing all predictions and validation which is implemented, highlight the spots which can be affected by flood disaster. And finally implement a chatbot to provide extensive knowledge about real-time weather data and forecasted data and others.

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Jayakantha J.H.C.M, Kumarasiri A.D.V.I.S, Medaela M.P.G.P.M.G, Perera W.A.D.C.T, & Dammika De Silva (July-2022). “Floodie”: Smart Flood Detection and Warning System. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 7(7), 652-657. https://ijnrd.org/papers/IJNRD2207078.pdf

Volume 7 Issue 7, July-2022

Pages : 652-657

Paper Reg. ID: IJNRD_181949

Published Paper Id: IJNRD2207078

Research Area: Computer Science & Technology 

Author Type: Foreign Author

Country: Kuliyapitiya, North Western, Sri Lanka

Published Paper PDF: https://ijnrd.org/papers/IJNRD2207078.pdf

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