A Flood Forecasting Model based on Wireless Sensor and Actor Networks

Sheikh Tahir Bakhsh, Naveed Ahmed, Basit Shahzad, Mohammed Basheri
2020 International Journal of Advanced Computer Science and Applications  
Flood forecasting is a challenging area of research that can help to save precious lives by timely intimating about the flood possibilities. The role of advancements in computing and allied technologies has moved the research towards a new horizon. Researchers from all over the world are using Artificial Neural Networks (ANN), Global Information Systems (GIS), and Wireless Sensor Networks (WSN) based schemes for flash flood forecasting and hydrological risk analysis. ANN and GIS-based solutions
more » ... are much costly whereas the analysis and prediction using WSN require much less cost for infrastructure deployment. It will enable the use of flood prediction mechanisms in the third world and poor countries. New variation in storage capacity can be a vital source to eliminate or reduce the chance of flood. By considering this observation, it is proposed to develop a generic flood prediction scheme that can manage the system as per resources and environmental conditions. A heterogeneous WSN has considered where powerful Collector Nodes (CN) continuously takes values from member sensor nodes in the region. CN transmits the alerts to Administration Unit (AU) when threshold values are crossed. It is proposed to save the threshold values from all water sources like storage capacity, water inflow, and outflow in the repository for decision making. Moreover, environmental parameters including water level, humidity, temperature, air pressure, rainfall, soil moisture, etc. are considered for the analysis of flood prediction. We have also considered the evaluation of these parameters in specified boundary values that were not considered in existing schemes. In this research study, we have used Arc GIS and NS2 simulation tools to analyze the parameters and predict the probability of the occurrence of a flood. been obtained graphically in which the x-axis represents the number of wireless sensor nodes and the y-axis represents the average energy cost per sensor node [13] . Flood prediction schemes are discussed categorically to identify the level of work already done in this area of research. The review is generally based on ANN, WSN, and GIS-based schemes used in managing the flood-related risks and doing effective forecasting in the areas of disaster management. ANN is used to extract the required data either from existing datasets containing flood-related details for previous years or live data capturing form radars and sensor networks. Existing schemes are discussed in subsections and shown in Fig. 3 . The network architecture for the flood forecasting system consists of a distributed prediction algorithm. The optimum intermediate deployment scheme has been used for WSN based communication infrastructure. The fuzzy risk analysis scheme is implemented employing the probability distribution method [1].
doi:10.14569/ijacsa.2020.0110856 fatcat:kdk354scmnfqvjp7vodhlicwnu