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Early Flood Detection and Disaster Victim Detection


Author(s):

Naveen K , Sapthagiri College of Engineering; Lokesh Kumar N, Sapthagiri College of Engineering; Kumaresh PM, Sapthagiri College of Engineering; Mallikarjun SC, Sapthagiri College of Engineering; Prachetha K, Sapthagiri College of Engineering

Keywords:

Monitoring flood, Sensor, Convolutional neural network, Artificial Neural Network

Abstract:

Flood is an unavoidable natural disaster in India, causing heavy flow of traffic and can also cause severe damage to properties and lives. For this reason, we created a flood detection system to monitor rising water in residential areas. Using ultrasonic sensor, we created flood level sensing device which is attached to Node MCU controller to process the sensor’s analog signal into a usable digital value of distance. The user can get real-time information on monitoring flooded roads over SMS based service. Flood height is determined by subtracting the sensor’s height with respect to the floor minus the sensed distance between the sensor and the flood water. Natural disasters can cause losses, both assets and objects can even take lives. Convolutional Neural Network is one of the developments of Artificial Neural Networks for image classification, image segmentation, and object recognition with high accuracy and high performance. CNN can learn to detect various images according to images from the dataset studied. So to reduce the number of losses, the System is designed for detecting victims of natural disasters using the CNN method.


Other Details:

Manuscript Id :IJSTEV7I1003
Published in :Volume : 7, Issue : 1
Publication Date: 01/08/2020
Page(s): 11-17
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