Record Details

An Artificial Intelligence-based Crop Recommendation System using Machine Learning

NOPR - NISCAIR Online Periodicals Repository

View Archive Info
 
 
Field Value
 
Title An Artificial Intelligence-based Crop Recommendation System using Machine Learning
 
Creator Apat, Shraban Kumar
Mishra, Jyotirmaya
Raju, K Srujan
Padhy, Neelamadhab
 
Subject AI
Crop harvesting quality
Feature selection
Industry 4.0
SMOTE
 
Description 558-567
Agriculture is the backbone of the Indian economy and a source of employment for millions of people across the globe.
The perennial problem faced by Indian farmers is that they do not select crops based on environmental conditions, resulting
in significant productivity losses. This decision support system assists in resolving this issue. In our study, the AI system
helps precision agriculture improve overall crop harvest quality and accuracy. This research feature selection, Industry 4.0,
proposes one solution, such as a recommendation system, using AI and a family of machine learning algorithms. The data
set used in this research work is downloaded from Kaggle, and labeled. It contains a total of 08 features with 07 independent
variables, including N, P, K, Temperature, Humidity, pH, and rainfall. Then SMOTE data balancing technique is applied to
achieve better results. Additionally, authors used optimization techniques to tune the performance further as smart factories.
Cat Boosting (C-Boost) performed the best with an accuracy value of 99.5129, F-measure-0.9916, Precision-0.9918, and
Kappa-0.8870. GNB, on the other hand, outperformed ROC-0.9569 and MCC-0.9569 in the classification, regression, and
boosting family of machine learning algorithms.
 
Date 2023-05-10T05:09:39Z
2023-05-10T05:09:39Z
2023-05
 
Type Article
 
Identifier 0022-4456 (Print); 0975-1084 (Online)
http://nopr.niscpr.res.in/handle/123456789/61883
https://doi.org/10.56042/jsir.v82i05.1092
 
Language en
 
Publisher NIScPR-CSIR,India
 
Source JSIR Vol.82(05) [May 2023]