Simulation of Flood Detection System Using Atmega 8535 Microcontroller

Abstract. One of the main challenges for global hydrological modelling is the limited availability of observational data for calibration and model verification. This is particularly the case for real-time applications. This problem could potentially be overcome if discharge measurements based on satellite data were sufficiently accurate to substitute for ground-based measurements. The aim of this study is to test the potentials and constraints of the remote sensing signal of the Global Flood Detection System for converting the flood detection signal into river discharge values. The study uses data for 322 river measurement locations in Africa, Asia, Europe, North America and South America. Satellite discharge measurements were calibrated for these sites and a validation analysis with in situ discharge was performed. The locations with very good performance will be used in a future project where satellite discharge measurements are obtained on a daily basis to fill the gaps where real-time ground observations are not available. These include several international river locations in Africa: the Niger, Volta and Zambezi rivers. Analysis of the potential factors affecting the satellite signal was based on a classification decision tree (random forest) and showed that mean discharge, climatic region, land cover and upstream catchment area are the dominant variables which determine good or poor performance of the measure\\-ment sites. In general terms, higher skill scores were obtained for locations with one or more of the following characteristics: a river width higher than 1km; a large floodplain area and in flooded forest, a potential flooded area greater than 40%; sparse vegetation, croplands or grasslands and closed to open and open forest; leaf area index > 2; tropical climatic area; and without hydraulic infrastructures. Also, locations where river ice cover is seasonally present obtained higher skill scores. This work provides guidance on the best locations and limitations for estimating discharge values from these daily satellite signals.

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Enhanced Flood Detection System using IoT

2021 6th International Conference on Communication and Electronics Systems (ICCES) ◽

10.1109/icces51350.2021.9489059 ◽

2021 ◽

Author(s):

A. Pravin ◽

T.Prem Jacob ◽

R. Rajakumar

Keyword(s):

Detection System ◽

Flood Detection

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Internet-Based Flood Detection System (Iot) and Telegram Messenger Using Mcu Node and Water Level Sensor

JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING ◽

10.31289/jite.v4i1.3892 ◽

2020 ◽

Vol 4 (1) ◽

pp. 230-235

Author(s):

Novianda Nanda Nanda ◽

Rizalul Akram ◽

Liza Fitria

Keyword(s):

Water Level ◽

Early Warning ◽

High Intensity ◽

Rainy Season ◽

Early Warning System ◽

Detection System ◽

Warning System ◽

Level Sensor ◽

Flood Detection ◽

Internet Of Thing

During the rainy season, several regions in Indonesia experienced floods even to the capital of Indonesia also flooded. Some of the causes are the high intensity of continuous rain, clogged or non-smooth drainage, high tides to accommodate the flow of water from rivers, other causes such as forest destruction, shallow and full of garbage and other causes. Every flood disaster comes, often harming the residents who experience it. The late anticipation from the community and the absence of an early warning system or information that indicates that there will be a flood so that the community is not prepared to face floods that cause a lot of losses. Therefore it is necessary to have a detection system to provide early warning if floods will occur, this is very important to prevent material losses from flooded residents. From this problem the researchers designed an internet-based flood detection System of Things (IoT). This tool can later be controlled via a smartphone remotely and can send messages Telegram messenger to citizens if the detector detects a flood will occur.Keywords: Flooding, Smartphone, Telegram messenger, Internet of Thing (IoT).

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Fuzzy Logic-Based Flood Detection System Using Lora Technology

2020 16th IEEE International Colloquium on Signal Processing & Its Applications (CSPA) ◽

10.1109/cspa48992.2020.9068698 ◽

2020 ◽

Author(s):

Choo Kam Khuen ◽

Alireza Zourmand

Keyword(s):

Fuzzy Logic ◽

Detection System ◽

Flood Detection

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FLOOD DETECTION IN NORWAY BASED ON SENTINEL-1 SAR IMAGERY

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-3-w8-349-2019 ◽

2019 ◽

Vol XLII-3/W8 ◽

pp. 349-355 ◽

Cited By ~ 1

Author(s):

J. H. Reksten ◽

A.-B. Salberg ◽

R. Solberg

Keyword(s):

Detection System ◽

Aerial Images ◽

Automated System ◽

Training Dataset ◽

Reference Image ◽

Visual Interpretation ◽

Sar Images ◽

Additional Information ◽

Flood Detection ◽

Sar Imagery

<p><strong>Abstract.</strong> After large flood incidents in Norway, The Norwegian Water Resources and Energy Directorate (NVE), has the responsibility for documenting the flooded areas. This has so far mainly been performed by utilising aerial images and visual interpretation. Satellite images are a valuable source of additional information as they are able to cover vast areas in each satellite pass. In this paper a fully automated system for detecting and delineating floods with the use of Synthetic Aperture Radar (SAR) images from the Sentinel-1 satellites is presented. In SAR images wet areas and water bodies usually show lower backscatter than dry areas. The flood detection system is thus based on comparing a reference image acquired before the flood with the flood event image. A Sentinel-1 training dataset has been obtained and manually annotated by NVE from three flood events in Norway. This training set has been used to train a random forest (RF) classifier, which outputs a score for each pixel in the SAR image. This score image is thresholded in order to obtain a crude flood detection. Unfortunately, changes in the backscatter may also be triggered by other events such as melting snow and harvested fields of crops. To mitigate such <q>lookalikes</q>, several techniques have been implemented and tested. This includes masking based on size, slope and <q>height above nearest drainage</q> (HAND). The experiments presented show that the system performance is very good. Of the 179 manually labelled flood objects, 168 are detected. The system is being applied operationally at NVE.</p>

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Automatic Detection of Flood Using Remote Sensing Images

Journal of Information Technology and Digital World - September 2019 ◽

10.36548/jitdw.2020.1.002 ◽

2020 ◽

Vol 02 (01) ◽

pp. 11-26 ◽

Cited By ~ 2

Author(s):

Amith Chandrakant Chawan ◽

Vaibhav K Kakade ◽

Jagannath K Jadhav

Keyword(s):

Neural Network ◽

Remote Sensing ◽

Convolutional Neural Network ◽

Detection System ◽

Deep Convolutional Neural Network ◽

Remote Sensing Images ◽

Hazardous Area ◽

High Resolution Images ◽

Flood Detection

Remote sensing imaging (RSI) technology has recently been identified as an effective photogrammetric data acquisition platform to rapidly provide high resolution images due to its profitability, its ability to fly at low altitude and the ability to analysis in dangerous areas. The various kinds of classification techniques are have been used for flood extent mapping for finding the flood affected region, but based on the color region based analysis the classified hazardous area has very complex. Due to over the above issues in this work there significant enhancements have appeared in the classification of remote sensing images using Contiguous Deep Convolutional Neural Network (CDCNN).In the flood detection system the four different kinds of process like preprocessing, segmentation, feature extraction and the Contiguous Deep Convolutional Neural Network (CDCNN) has been executed for identifying the flood defected region. This works also investigates and compare with the possible methods with the proposed CDCNN for accurately identified by the Classification details of the RSI

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Flood Detection System Using Ultrasonic Sensor with Fuzzy Logic Method

10.2991/aer.k.211106.027 ◽

2021 ◽

Author(s):

Jessy Nasyta Putri Santoso ◽

Tri Tisna Firly Hartini ◽

Ali Suryaperdana Agoes

Keyword(s):

Fuzzy Logic ◽

Detection System ◽

Ultrasonic Sensor ◽

Fuzzy Logic Method ◽

Flood Detection ◽

Logic Method

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Implementation of the SMS Gateway in the Flood Early Warning Information System for Village Warning and Community Information

International Journal of Engineering and Advanced Technology - Regular Issue ◽

10.35940/ijeat.f9287.088619 ◽

2019 ◽

Vol 8 (6) ◽

pp. 4005-4009

Keyword(s):

Information System ◽

Early Warning ◽

Detection System ◽

Warning System ◽

Short Term ◽

The Public ◽

Detection Systems ◽

Flood Warning ◽

Flood Detection ◽

Flood Warning System

Flooding is a national disaster that often occurs in Indonesia. Flood disasters require long-term and short-term action. In the short-term system, the government currently emphasizes state and private institutions to jointly reduce flood victims by developing a flood disaster early warning system. Therefore, this study discusses the making of flood early warning information systems by utilizing GSM communication systems as a means of communication between clients and servers. The GSM communication service used is the SMS Gateway. The SMS gateway service is used for the first time sending data from a flood detection system to a flood information system. Second, disseminating flood information to the public. In this study, the flood warning system for flood early warning works with the integration of three modes.The three systems are flood detection systems, flood alarm systems, and flood early warning information systems. Flood detection systems are built using ultrasonic sensors and rain sensors as inputs, Arduino Uno as data processors and GSM SIM900 modules as outputs. The alarm system consists of GSM SIM900 module as Input, Arduino Uno as processor and electric alarm as output. The flood early warning information system was built using a Wavecom GSM modem, and data processing using PHP, MySQL DBMS, and Gammu. The communication system between each system uses SMS data. This method as a whole began in a flood detection system that sends flood and rain data to the flood early warning information system. And the flood warning system sends alarm activation data to the alarm system. Finally, the system distributes flood information to the public via SMS Gateway. This research is expected to help the community in anticipating more victims with flood information previously obtained

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