Big Data in Agriculture has great scope as Agriculture is heavily dependent on data. Agriculture Analytics in the form of success rate of fertilizers in a particular terrain for a soon to be launched fertilizing product is of importance. Agriculture Data could be data about the success of a specific crop in a given geographical climate. Such information can be particularly of interest to farmers, Agricultural companies, and Agriculture consultants. However, information exchange is rather limited for all these parties due to the following problems:
Many Farmers have limited knowledge of Agriculture Data and methodologies of farming. Due to this agricultural productivity remains limited.
Consultants to guide Farmers regarding new technology and Agriculture Analytics are limited especially in remote areas.
Agriculture Companies producing fertilizers and other agricultural products resort to physical testing before they launch the products.The results from such tests are not very reliable since the trials take place in a specific environment and do not take into account other types of geographical conditions.
At Qwentic we have developed a Mobile and Web based IoT Application that can solve the above problems by providing an Organized crop-planning and process management platform:
- It enables farmers to analyze crop health in real-time. With secure messaging channel between consultants and farmers, help is readily available to farmers, thereby reducing damage to the crops.
- It also allows Consultants to reach out to as many farmers as possible.
- The Big data in Agriculture thus collected from such interactions regarding crops, weather, terrain, geographic conditions, water and more is stored and processed. This leads to the analytics part of our solution. By processing this data, the application will be able to assist:
- Agriculture companies regarding prospective success of products in different markets
- Farmers about success of different crops, predictive impact of natural conditions, etc.
- Consultants will learn more about the most affected geographic areas where farmers could be assisted to deliver higher productivity.
We have developed the Web Application server using Golang and an android application using
Hadoop Platform stores Big Data and deep learning/Machine learning allow the platform to provide:
To predict the success of a product or crop or predict ill effects of a natural event on crops.
Historical Data Analysis
Process vast volumes of historical data regarding crops, geography, etc.
To provide Farmers with real-time assistance by analyzing information provided by them in real time.
Increased Agricultural Productivity through Agriculture Data
Greater success of Fertilising Products across variety of geographic conditions for Agriculture Companies.
Avoid ill effects of a particular natural occurrence
Given all the above facts Qwentic aims to increase the role of Big Data in Agriculture through our Big Data Analytics Platform.