ABSTRACT

Our current research focus is to build and implement open source and scalable system for Agro Advisory System (AAS). Compared with the existing agro advisory systems that are demonstrated after a human-in-loop decision process, the proposed system provides analytics and integrated platform to develop various analytical services for agriculture and provide customized solutions to agro users in the form of crop calendar, alerts based on adverse events etc. in local languages.

Description

Agriculture is becoming increasingly information and knowledge centric today. With a billion plus mouths to feed it is quite evident how important the agriculture sector is in India. In addition, there is a worrisome trend that is increasing the population with a low agricultural growth rate. Hence, exploiting the full potential of existing resources with technologies would be the only approach for next-generation agriculture. Modern trends in the agriculture domain have made people realize the importance of big data. The key challenge of big data in agriculture is to identify the effectiveness of big data analytics. Moreover, how big data analytics can be used to improve productivity in agricultural practices. The purpose of the proposed research is to reduce the technological gap between rural communities and information through recommendations and decision support system.

The concept of big data in agriculture is still relatively new and the applications have been very limited, especially in the Indian context. More research effort is required by government agencies and research organizations to meet the demand for big data analytics in agriculture. The application of big data analytics in agriculture has a huge potential which has been untapped so far.

Our current research focus is to build and implement open source and scalable system for Agro Advisory System (AAS). Compared with the existing agro advisory systems that are demonstrated after a human-in-loop decision process, the proposed system provides analytics and integrated platform to develop various analytical services for agriculture and provide customized solutions to agro users in the form of crop calendar, alerts based on adverse events etc. in local languages.

 

Keywords: Data Science: Cloud Computing, Data Analytics and Machine Learning