Our main mission was to prevent the physical and economical damage caused by floods. So we developed an algorithm which will study the precipitation datasets received from JAXA and will prematurely notify us in case it senses a heavy rainfall morphing into a flood. To further notify government; panchayath, district administration, weather department or sometimes people living in flood prone zones we developed a website (which is linked to the algorithm) which carries out the job.
We are researching the use of UAV's (unmanned air vehicles) in rescue operations. These UAV's can be used by rescue teams to detect people stuck in floods. These electronic birds will have 2 cameras; one of it will be used for detection of face and another one will be for thermal imaging. Using these we can locate people in distress during floods and rescue them safely.
Unusually flooding has affected millions of people, with dozens of casualties. Since June, continuous downpours have lashed large parts of area like Egypt floods(2016) , north Korean floods (2012) in world also Assam floods (2020 and 2016), Kerala floods ( 2019 and 2019) , Gujarat floods ( 2015) in India.
We can protect from flood hazards by taking measures to ensure the safety of life and property before, during, and after a flood occurs. If evacuation becomes necessary,
Hence this made us to take up this project.

we developed a tool (website) which will notify the government; panchayat, district administration, weather department sometimes people living in flood prone areas in the times of heavy rains which may cause floods.
We also developed the methods like floods forecasting , face detection and thermal imaging to help the people during the situation of floods.
TOOL USED
We have used website, artificial neural network for real time forecasting and machine learning tool for perdition of floods using dataset.We also have used software 3D model in CINEMA 4D to create virtual model
PROGRAMME USED
python with the libraries of tensorflow2.0,keras and seaborn.
PROBLEMS
We had faced the problems of the finding the solution of the challenge is to develop a new methodology or algorithm that leverages Earth observation and critical infrastructure datasets to estimate damages to infrastructure caused by flooding and make a measurable impact on the regional areas.
ACHIVEMENTS
We developed the website which which will notify the government; panchayath , district administration, weather department sometimes people living in flood prone areas in the times of heavy rains which may cause floods and also to tackle the situation of the after the floods by thinking the ideas of face detection and thermal imaging which is the face detection is used to detect the faces of people stuck whereas thermal camera detects the faces in dark vision. Drone face detection technique can also be used to find out the missing person drowned in flood. Drones can be used for more precision to find out the people struck under building debris, etc.
Inference :- In this We can save people who are note even seen by the rescuers.
We also used the method Flood forecasting is an important component of flood warning, where the distinction between the two is that the outcome of flood forecasting is a set of forecast time-profiles of channel flows or river levels at various locations, while "flood warning" is the task of making use of these forecasts to tell decisions on warnings of floods.
VIRTUAL MODEL (SIMULATION)
We have created a virtual model which explains about our idea.Whenever the flooding takes place, or when it is about to enter a rural or urban areas, people get notified well in advance by using the technique that is - to get all the individuals basic information like phone number etc.Using these contact numbers we can alert people by sending an SMS,but there is a drawback in this, that is the people who have immigrated recently have no data at the panchayat or the people who dont use cell phones.To overcome this situation,we can setup a propaganda which will alert all the people in that area, as the seismic sensors are activated in no time the towers and propanganda will be activated and alert alarm will be echoed, in this way people can clear the area well in advance.
The sensors can have a certain limit of range of radius of KM, range can be increased as the sensors are placed serially at a certain distance, by which the alerting area will be also increased.
the software we used to make the 3D model is CINEMA 4D.
We studied the world geographical maps from this which was needed for our project to understand the Global flood total economic loss risk.
2.GFMS(Global Flood Monitoring System):
GFMS was used by us to take idea how flood is monitored over weather forecast and earth data
3.Group on Earth Observations(GEO) Global Flood Risk Monitoring(GFRM) community activity
We collected few datasets from here.
4.JAXA Global Rainfall Watch (GSmap):
Global rainfall status was mapped. Result on simulation of land surface/river water for disaster monitoring and hydrological research by Today's Earth.
Website created by us - Helping hands (Github)
https://github.com/24-shweta/Technotip/blob/Wesite_helpinghands/website_helping%20hands
Helping hands:
https://pateldivya1762.wixsite.com/flood
Virtual model:

DATA & RESOURCES:
1.SocioEconomic Data And Application Centre(SEDAC) NASA.
https://sedac.ciesin.columbia.edu/data/set/ndh-flood-total-economic-loss-risk-deciles/maps
2.Algorithm.
https://www.mdpi.com/2073-4441/10/11/1536/htm
3.Tackling flood strategy.
4.JAXA Global Rainfall(GSmap)
https://sharaku.eorc.jaxa.jp/GSMaP/
5.Group on Earth Observations(GEO) Global Flood Risk Monitoring(GFRM) community activity
https://geo-floodrisk-nasa.opendata.arcgis.com/
6.GFMS(Global Flood Monitoring System)
https://disasters.nasa.gov/instruments/gfms
7.Looking at past worst hit floods we predicting forthcoming floods.
https://globalnews.ca/news/4411144/india-worst-floods/
8.Face Detection.
https://www.kaggle.com/drgilermo/face-images-with-marked-landmark-points?select=facial_keypoints.csv
9.Electricity tackling.
10.International Committee of Red Cross.