An Intelligent Irrigation Scheduling and Monitoring System for Precision Agriculture Application

RajinderKumar Mallayya Math and Nagaraj V. Dharwadkar
Additional contact information
RajinderKumar Mallayya Math: Department of Electronics and Communication Engineering, B.L.D.E.A's V.P. Dr. P.G. Halakatti College of Engineering and Technology, Vijayapur, India & VTU-RRC, Belagavi, India
Nagaraj V. Dharwadkar: Department of Computer Science and Engineering, Rajarambapu Institute of Technology, Uran Islampur, India

International Journal of Agricultural and Environmental Information Systems (IJAEIS), 2020, vol. 11, issue 4, 1-24

Abstract: In spite of technological advancements, the farm productivity of Indian agriculture is still on the lower side. The underlying reason for poor farm productivity in India is due to the inefficient usage of agricultural inputs, resulting in low or poor-quality agricultural yields. Water happens to be one of such imperative agricultural input that has a huge impact on agricultural productivity. Precision agriculture systems can take care of irrigation requirements by optimally and efficiently using irrigation water for producing crops having superior quality and quantity. This work proposes a smart irrigation system that can efficiently manage the water requirements of the crop for its optimal growth. The irrigation schedules are developed using a feed forward neural network model that can predict the variation in the soil moisture considering the environmental factors such as temperature, humidity, atmospheric pressure, and the rain. The results indicate the effectiveness of the developed system in predicting the soil moisture with mean square error as low as 0.13 and the R value as high as 0.98.

Date: 2020
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 18/IJAEIS.2020100101 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jaeis0:v:11:y:2020:i:4:p:1-24

Access Statistics for this article

International Journal of Agricultural and Environmental Information Systems (IJAEIS) is currently edited by Frederic Andres

More articles in International Journal of Agricultural and Environmental Information Systems (IJAEIS) from IGI Global
Bibliographic data for series maintained by Journal Editor ().