ELite Coders
NASA Space Apps
we have used the Rainfall dataset in India from the Kaggle for predicting the rainfall at different parts of the country at a particular time based upon the seasons. Granularity is on a monthly basis and this data is taken from 36- meteorological subdivisions located in India, where the amount of rainfall is being measured in Millimeters(mm).Using Machine Learning(ML) models we have predicted the future rainfall of India in different places.
In our project, we have used machine learning algorithms such as linear regression/logistic regression, support vector machine (SVM), matplotlib for plotting the graphs.
Linear regression is used to determine or identify the relationships between two columns/variables in a dataset. Logistic regression is used for analyzing a dataset that has one independent variable or more. The results obtained from analyzing the variables are either 0s or 1s/true or false.
The support vector machine is used for classification between any set of groups present in the dataset. The objective of the SVM is to draw the best fit line which is used to differentiate between two different classes or groups present in the dataset.
Matplotlib is the library which can be used for creating visualization by plotting graphs where we can differentiate the rainfall rate based on states when the rain occurs & further differentiates the quantity of the rainfall of each city at each month
The required hardware modules are the sensors, microcontroller and the materials for power supply. The objective of these hardware components is to control and measure the pressure of water. It collects the data on water level and the information is stored in the cloud through the communication of WIFI and the data is being enabled to pass the information through the internet.
The microcontroller helps in processing the information which is being fetched from the sensors and this information is being sent to the admin through the medium of the cloud
The sensors which help to give the information to the microcontroller from various nodes located at a different place. The sensors that are required for this project are as follows: The ultrasonic sensor-This sensor is used to measure the level of the water and the average rainfall that is being occurred at a particular place. If water level strikes at a particular level it emits very high frequency so these echo signals are reflected in the sensors and it gives an alert message to the microcontroller and send the information to the cloud. The ultrasonic sensor consists of 4-pin. The 4-pins are used to measure water level, trigger, ground connection & the last current. Pressure sensor - BMP Barometric sensor is used to identify the atmospheric pressure present inside the water. Humidity sensor - DHT11 sensor works on the principle of one wire protocol which identifies the climatic changes and the humidity which gives us the output in a digital format.
High energy of power supply is not needed, so the current we get in the AC power supply is being converted to the DC power supply and it can be used in the implementation.
The values that are being fetched by the microcontrollers from the sensors are sent to the cloud via WIFI. The cloud will have the access of all the registered users. This stored data is being redirected to the websites where the users can access the information about the condition of flood occurring .