Wireless Smart Sensor Network for Flood Management Optimization

Recent development in the sensing technologies and wireless sensor networks has encouraged many innovative applications in disaster management and forecasting. Flood is one of the most dangerous natural disasters that occurs frequently in south Asia. Therefore, water level monitoring and flood ear...

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Bibliographic Details
Main Authors: Alfarra, Hossam Adden, Alsibai, Mohammad Hayyan
Format: Article
Language:English
Published: Penerbit Universiti Malaysia Pahang 2017
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/18515/1/ftech-2017-hayyan-Wireless%20Smart%20Sensor%20Network.pdf
http://umpir.ump.edu.my/id/eprint/18515/
http://ijets.ump.edu.my/images/archive/Vol7/5.pdf
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Summary:Recent development in the sensing technologies and wireless sensor networks has encouraged many innovative applications in disaster management and forecasting. Flood is one of the most dangerous natural disasters that occurs frequently in south Asia. Therefore, water level monitoring and flood early prediction,play an important role in lives and properties saving. In this paper, an optimized Flood Warning System (FWS) is presented. The system is based on multi parameters Wireless Smart Sensor Network (WSSN) for early flood warning. WSSN performs pre-processing procedures at sensor level before sending the data to a base data analyzing station. This pre-processing step is to improve the reliability,data quality and transmission quality. For the purpose of validation, the proposed method is applied using two parameters: The water level (L) and streamflow of water (R) in rivers. The proposed system provides early flood detection by continuously measuring R and L in real-time. The collected data is to be used to predict flood time and place. Data is exchanged among sensors in real-time. Pre-analyzing is performed and reports are sent to the base station only if the analysis gave a high risk level. The main purpose is to cut down the data size. Analysis and simulation showed that the data size is improved significantly using this method. Calculations considers real cases on a part of Pahang River (Sungai Pahang).