Exploring Agriculture Sector Using Crowdsourcing Predictors

Abstract

India is a nation where agriculture is considered as a basic occupation and the largest source of national growth. Farmer is said to be man of nation. We consider this as our responsibility and prime duty to explore this occupation and take it to a higher level from technology point of view .Our project emphasizes on describing a new approach to machine science which is representing for the first time that non-domain experts can collectively formulate features and provide values for those features such that they are prediction of some behavioural outcome of interest. This project will be focusing on the each and every single concept related to agriculture. It will also have a provision where farmers can share their experiences regarding best agriculture practices and methods. This will be accomplished by building a web platform in which human groups interact to both, respond to questions likely to help by predicting a their behavioural outcome and pose new questions to their peers, share their experiences and knowledge. This results in a dynamically-growing online survey, but the result of this outcome behaviour also leads to models that can anticipates users results based on their responses to the user-generated survey questions. The purpose behind developing such a portal based on agriculture is to make Indian farmer to interact with farmers over the nationwide using the technology. This portal can be used for multiple purposes where entrepreneurs can launch the products as well as acquire the feedbacks.

Authors and Affiliations

Chetan V. Pawar, Sapna S. Patni, Sandesha K. Wale, Harshal B. Chemate, Prof. A. Dasgupta

Keywords

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  • EP ID EP20219
  • DOI -
  • Views 209
  • Downloads 5

How To Cite

Chetan V. Pawar, Sapna S. Patni, Sandesha K. Wale, Harshal B. Chemate, Prof. A. Dasgupta (2015). Exploring Agriculture Sector Using Crowdsourcing Predictors. International Journal for Research in Applied Science and Engineering Technology (IJRASET), 3(4), -. https://europub.co.uk/articles/-A-20219