Predicting Agricultural Produce using Machine Learning Techniques
Riddhi Dange, Jinisha Kande, Kunal Bhosale, Ankush Hutke
Agriculture, Google Maps API, GPS, Machine Learning
Agriculture is the largest contributor of the GDP in our country. But still the farmers do not get the exact worth price of the crops. It is mostly due to improper irrigation or imprecise crops selection, sometimes the crop yield is less than expected. In order to add efficiency to the whole agriculture process a “Predicting Agricultural Produce using Machine Learning Techniques” is proposed in the following project. The system aims at predicting the agricultural produce by obtaining area on Google Maps API and further calculate area under cultivation. GPS technology is now used widely by various people and organizations for determining the position of objects. GPS can be used to measure the area of land under cultivation.
Article Details
Unique Paper ID: 154759

Publication Volume & Issue: Volume 8, Issue 12

Page(s): 329 - 334
Article Preview & Download

Share This Article

Join our RMS

Conference Alert

NCSEM 2024

National Conference on Sustainable Engineering and Management - 2024

Last Date: 15th March 2024

Call For Paper

Volume 11 Issue 1

Last Date for paper submitting for Latest Issue is 25 June 2024

About Us enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on

Social Media

Google Verified Reviews