IDEAS home Printed from https://ideas.repec.org/a/igg/jaeis0/v10y2019i3p72-92.html
   My bibliography  Save this article

State of the Art and Gap Analysis of Precision Agriculture: A Case Study of Indian Farmers

Author

Listed:
  • Vaibhav Bhatnagar

    (Amity Institute of Information Technology, Amity University Rajasthan-Jaipur, Rajasthan, India)

  • Ramesh C. Poonia

    (Amity Institute of Information Technology, Amity University Rajasthan-Jaipur, Rajasthan, India)

  • Surendra Sunda

    (ISRO-India, Bangalore, India)

Abstract

Precision Agriculture (PA) is now becoming the base for rapid development of a nation. So many technologies are used in precision agriculture such as Global Positioning System (GPS), Artificial Intelligence (AI), Sensor Network and Geographical Information System (GIS). This manuscript per the authors will review all the factors that influence the precision agriculture. This article describes the major endeavors in the past of precision agriculture. The noble intention behind this literature review and analogy is to figure out the gap between theoretical research and actual needs of farmers. In order to find out the actual requirements manuscripts per the authors have conducted a questionnaire in Rajasthan State of India. This gap analysis would be helpful for researchers to design an effective and efficient decision support system for irrigation and fertilization can be designed for Indian farmers.

Suggested Citation

  • Vaibhav Bhatnagar & Ramesh C. Poonia & Surendra Sunda, 2019. "State of the Art and Gap Analysis of Precision Agriculture: A Case Study of Indian Farmers," International Journal of Agricultural and Environmental Information Systems (IJAEIS), IGI Global, vol. 10(3), pages 72-92, July.
    • Handle: RePEc:igg:jaeis0:v:10:y:2019:i:3:p:72-92
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJAEIS.2019070105
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jaroslav Vrchota & Martin Pech & Ivona Švepešová, 2022. "Precision Agriculture Technologies for Crop and Livestock Production in the Czech Republic," Agriculture, MDPI, vol. 12(8), pages 1-18, July.
    2. Lucas Santos Santana & Gabriel Araújo e Silva Ferraz & Gabriel Henrique Ribeiro dos Santos & Nicole Lopes Bento & Rafael de Oliveira Faria, 2023. "Identification and Counting of Coffee Trees Based on Convolutional Neural Network Applied to RGB Images Obtained by RPA," Sustainability, MDPI, vol. 15(1), pages 1-17, January.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:igg:jaeis0:v:10:y:2019:i:3:p:72-92. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.