Claims:We claim:
1) System for prediction of crops by using big data technology is comprising of:
a. Crop prediction web application –used for prediction of crop for farming;
b. Any electronic device which has active internet connection – used for communicating the crop prediction web application;
c. Sensors and device – Internet of Things (IoT) enabled which is used for soil testing and other parameters;
d. Backend server – used for storing all data related to soil and related factor testing, analysing and predicting for crop yield; and
e. Any open-source framework like Hadoop for data analysis which stored data on big data
Wherein, through an electronic device the said application can be accessed through which soil data come from sensors and devices is submitted to application by said user and get analysed data and prediction about yield for soil.
2) Method for prediction of crops by using big data technology is comprising the steps of:
a) Creating a database for storing result data of various soil test;
b) Soil data came from sensors and devices is submitted to the web application through an electronic device;
c) Selecting the current location from the web application through an electronic device;
d) Selecting the option for yield advice from the web application;
e) Data analysis is done by big data technology for selected location and for data related to soil submitted by said user;
f) Predicating about yield which is suitable for particular condition and soil by using big data technology; and
g) Displaying detailed description of various crop which would be best survived for selected location and for particular soil on the screen of said electronic device
3) The system claimed in claim 1, wherein the internet of things enabled sensors and devices are installed at the farm for measuring various reading of soil.
4) The system claimed in claim 1, wherein the data provided by sensors and device is stored on the said backend server.
5) The method claimed in claim 2, wherein data is gathered for selected location weather from various resources by big data technology.
6) The method claimed in claim 2, wherein soil data and weather data are analysed to predict which crop yield is suitable for said condition.
7) The method claimed in claim 2, wherein displays the detail information about crop yield which is suitable to plant through said electronic device.
, Description:Field of the invention:
The present invention is related generally to the agriculture, and more particularly to system and method for prediction of crops by using big data technology.
Background of the invention:
In agriculture different crops have different requirement for grow such as type of soils, types of nutrients, amounts of nutrients, types of water and amounts of water. There are other factors which also affects the growth of crop such as climate and season where crop is growing. To select right crop for particular soil conditions and climate by saving water requirements for irrigation is really tough job.
Selecting a crop is an important agricultural problem. The agricultural crop growth is mainly depending upon weather conditions, pests and planning of harvest operation. Right information of crop history is an important feature for making decisions related to agricultural risk management.
There are a system having crop related inventions, which are patented, are listed below.
US patent application US20140035752A1 by Jerome Dale Johnson discloses Methods, apparatus, and systems for determining in-season crop status in an agricultural crop and alerting users. A crop's status may be determined from analysis of information regarding the crop received from, for example, a user, an in-season data gathering source, a database, a data feed, an aerial sensor, a UAV, and/or a remote sensor via a communication network. The received data may be compared to, for example, a benchmark, a parameter, a previously determined crop status, and/or a baseline associated with the crop and the comparison may be scored. When the score exceeds a predetermined threshold, an alert may be generated and provided to a user via the communication network.
US patent application US8208680B2 by Peter Clifton Scharf, Victoria Cacnio Hubbard discloses Method of predicting crop yield loss due to N-deficiency. A method for determining the yield loss of a crop using remote sensor data is described. The yield loss is determined using the reflectivity of green light by the crop canopy measured from remote sensor data such as an aerial photograph that is digitized and spatially referenced to the field's longitude and latitude. Green pixel values from the aerial photograph, expressed relative to green pixel values from well-fertilized areas of the field, are transformed to yield losses using a linear transformation that was developed using empirical data. A similar method is described to determine recommended nitrogen fertilization rates for the crop fields. The yield loss data is useful for nitrogen fertilization management, as it allows a producer of crops to weigh the expense of fertilization against the loss of revenue due to yield loss.
PCT patent application WO2015051339A9 by Sammy Stehling, Christopher FASANO discloses Crop model and prediction analytics. Various agronomic technologies are described, including a computer-implemented method for forecasting crop yield and an agronomic web portal.
US patent application US20050234691A1 by Ramesh Singh, Anup Prasad, Vinod Tare, Menas Kafatos discloses Crop yield prediction. Crop yield may be assessed and predicted using a piecewise linear regression method with break point and various weather and agricultural parameters, such as NDVI, surface parameters (soil moisture and surface temperature) and rainfall data. These parameters may help aid in estimating and predicting crop conditions. The overall crop production environment can include inherent sources of heterogeneity and their nonlinear behaviour. A non-linear multivariate optimization method may be used to derive an empirical crop yield prediction equation. Quasi-Newton method may be used in optimization for minimizing inconsistencies and errors in yield prediction. Minimization of least square loss function through iterative convergence of pre-defined empirical equation can be based on piecewise linear regression method with break point. This non-linear method can achieve acceptable lower residual values with predicted values very close to the observed values. The present invention can be modified and tailored for different crops worldwide.
Though the prior art patent discloses Methods, apparatus, and systems for determining in-season crop status in an agricultural crop and alerting users, Method of predicting crop yield loss due to N-deficiency, Crop model and prediction analytics and Crop yield prediction, they do not give any perfect solution for predictions of crops.
Big data is a field that treats ways to analyse, systematically extract information from, or otherwise deal with data sets that are too large or complex to be dealt with by traditional data-processing application software.
Object of the invention:
The primary object of the present invention is to provide system and method for prediction of crops by using big data technology.
Another object of the present invention is to provide system and method for prediction of crops which have internet of things enabled sensors and devices installed at various location of farm.
Another object of the present invention is to provide system and method for prediction of crops where sensors and devices send information to the backend server periodically.
Another object of the present invention is to provide system and method for prediction of crops provides an option to the said user for selecting the current location of said user from the web application through an electronic device.
Another object of the present invention is to provide system and method for prediction of crops provides analysis of data for selected location and data come from sensors and devices with the help of big data technology.
Another object of the present invention is to provide system and method for prediction of crops provides prediction of crops which is suitable for particular condition and soil by using big data technology.
Another object of the present invention is to provide system and method for prediction of crops which displays detailed description of various crop which would be best survived for selected location and for particular soil on the screen of said electronic device.
Summary of the invention:
The present invention discloses system and method for prediction of crops by using big data technology. The prediction of crops system is comprising of;
Crop prediction web application –used for prediction of crop for farming;
Any electronic device which has active internet connection – used for communicating to the crop prediction web application;
Sensors and device – Internet of Things (IoT) enabled which is used for soil testing and other parameters;
Backend server – used for storing all data related to soil and related factor testing, analysing and predicting for crop yield; and
Any open-source framework like Hadoop for data analysis which stored data on big data
According to the present invention, user would have to open the web application where the said user should select current location through an electronic device. Sensors and devices installed at farm send data to backend server and said user submit this data to the web application and said user should have to select the option “submit data”. With the help of big data technology, data is gathered from various resources. This data may be structured as well as unstructured type. Big data opens source framework analyses this data and predicts which crops are suitable for said condition, climate and location. It displays list of crops which is suitable for current location and selected soil.
Brief description of the drawings:
Fig.1 illustrates system of this invention.
Fig. 2 illustrates flowchart of method for this invention.
Detailed description of the invention:
The present invention discloses system and method for prediction of crops by using big data technology.
Big Data Technology can be defined as a Software-Utility that is designed to Analyse, Process and Extract the information from an extremely complex and large data sets which is difficult for the Traditional Data Processing Software.
Big data includes vast volume of structured or unstructured data that is readily available at collective fingertips. These large data sets are analysed to reveal previously unknown patterns and provide insights into businesses, human behaviour, and more. Big data analysis is used for everything from financial services, to gauging someone’s productivity, to even monitoring the weather and now for agriculture also.
Fig.1 illustrates the system for prediction of crops by using big data technology is comprising of contents;
Crop prediction web application – used for prediction of crop for farming;
Any electronic device which has active internet connection – used for communicating to the crop prediction web application;
Sensors and device – Internet of Things (IoT) enabled which is used for soil testing and other parameters;
Backend server – used for storing all data related to soil and related factor testing, analysing and predicting for crop yield; and
Any open-source framework like Hadoop for data analysis which stored data on big data
Fig.1 illustrates the system of present invention which includes internet of things enabled sensors and devices which are installed at various places of farm. This sensors and devices are used for testing various parameters of soil, weather, temperature. The result data of these sensors and devices are send to the backend server. Backend server store all this data in the database. When said user open the web application through an electronic device, he/she would have to enter all this data into web application. Also, said user would have to select his/her current location from the list provided in the application. After selecting and entering all the data said user has to submit this data into the application.
Fig. 1 illustrates the system of present invention which includes big data framework. Big data framework consists of mainly five stages such as-
Data sources- web and social media, machines, Sensing, IoT
Content format – structured, semi-structured, unstructured data
Data stores – document oriented, column oriented, graph database, key value
Data Staging – cleaning, transform and normalization
Data processing – Batch and real time
The embodiment of present invention includes big data framework. This framework mainly gathered data from various sources such as web, social media, machine, sensors and IoT. This data may have structured data type, semi-structured data type and unstructured data type. Big data framework analyses this data and predicts which crops are most suitable for selected location and soil condition and climate condition.
Fig. 2 illustrates method for prediction of crops by using big data technology is comprising of the steps are as;
Step 1) A database is created for storing sensors result data of various soil test
Step 2) User open the web application on any electronic device
Step 3) Soil data came from sensors and devices is submitted to the web application through an electronic device by said user

Step 4) User select the current location from the web application through an electronic device
Step 5) User select option for crop advice from the web application
Step 6) With the help of big data technology, the data of selected location is retrieved from various source and stored in the database
Step 7) Data analysis is done by big data technology for selected location and for data related to soil submitted by said user
Step 8) The application predicts the list of crops which are suitable for condition and location by using big data technology
Step 9) The list of crops which are predicted is shown on the screen of said electronic device
There are some advantages of the present invention such as;
As information related to soil and weather is collected through internet of things enabled sensors and devices, it reduces erroneous manual work and provides useful insights on crop prediction.
It is more reliable as all data is gathered with trusted resources and this data is then analysed to come into a particular decision.
It reduces time to check and test for soil and weather and other parameter which affects growth of crop.
It checks future weather conditions which would affect to the growth of crop and by considering it gives advice to the said user which time is best for particular crop farming.
It has consistency of prediction of crops as it is purely based on scientific knowledge. No other assumptions are considered while making any predictions.
It is low cost which saves money of said user.
User can get more options for cultivation beyond his/her imagination.
The present invention can be better understood with the help of examples.
Example 1:
According to present invention user open web application for prediction of crop on any electronic device which has active internet connection. Internet of things enabled sensors and devices are installed at various location of farm to check parameters such as test related to soil, weather, etc. The sensors and devices send data to the backend server. User has to select current location from the web application and enter the data send by sensors and devices to the application through electronic device. And select option for prediction of crop. After selecting the option, big data gathered information related to current location such as climate, rainfall, humidity. Big data framework then analysed this data and soil data submitted by said user. Big data predicts the list of crops which are most suitable for certain conditions and location and show this list to user on the screen of an electronic device. User living in heavy rain area, where system is suggested to cultivate rice and other option for a particular time to get maximum profit from it.
Example 2:
According to present invention user open web application for prediction of crop on any electronic device which has active internet connection. Internet of things enabled sensors and devices are installed at various location of farm to check parameters such as test related to soil, weather, etc. The sensors and devices send data to the backend server. User has to select current location from the web application and enter the data send by sensors and devices to the application through electronic device. And select option for prediction of crop. After selecting the option, big data gathered information related to current location such as climate, rainfall, humidity. Big data framework then analysed this data and soil data submitted by said user. Big data predicts the list of crops which are most suitable for certain conditions and location and show this list to user on the screen of an electronic device. User living in minimum rain area, where system is suggested to cultivate cotton and other option for a particular time to get maximum profit from it.
It should be kept in mind that the described embodiment(s) is only presented by way of example and should not be construed as limiting the inventive concept to any particular hardware and software configuration.
The present invention is not limited to components, which is mentioned in the description. Based on the same concept, prediction of crops can be built. Those who are familiar in the art will understand that a number of variations may be made in the disclosed embodiments, all without departing from the scope of the invention, which is defined solely by the appended claims.