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IOT based smart irrigation management system for environmental sustainability in India

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dc.contributor.author Sangeetha, B. Parvathi
dc.contributor.author Kumar, Neeraj
dc.contributor.author Ambalgi, Ambresh P.
dc.contributor.author Abdul Haleem, Sulaima Lebbe
dc.contributor.author Thilagam, K.
dc.contributor.author Vijayakumar, P.
dc.date.accessioned 2022-02-18T06:22:16Z
dc.date.available 2022-02-18T06:22:16Z
dc.date.issued 2022
dc.identifier.citation Sustainable Energy Technologies and Assessments Volume 52, Part A, August 2022; 101973 en_US
dc.identifier.issn 2213-1388
dc.identifier.uri https://doi.org/10.1016/j.seta.2022.101973
dc.identifier.uri http://ir.lib.seu.ac.lk/handle/123456789/5987
dc.description.abstract Food and clean water make agriculture a valuable asset to humanity, as it uses water to provide us with food. Environmental destruction and rapid population growth have had a massive effect on agriculture, a detrimental impact on the world's water supplies, and crucial for sustained development. To resolve the issue, implement the intelligent irrigation method using automated and Internet of Things (IoT) technologies. This study involves an intelligent agriculture management system to produce agricultural benefits and crop production. The hybrid remote-controlled device used the Global Positioning System (GPS) with Radial Function Network (RFN) was proposed to control the irrigated system, predict the temperature, maintain the air pressure, and reduced the humidity in water content. It uses IoT sensors and the Internet of Everything (IOE) environmental data for managing and monitors intelligent solar irrigation systems. The objective is agriculture intelligent by using automation and IoT technologies. It scientifically designed to perform tasks such as weeding, irrigation, sensing humidity, attempting to scare birds and livestock, maintaining surveillance, etc., to control the geolocation of devices remotely. As a result, the design is to achieve all of its goals in terms of water use; total running costs decreased labour, energy consumption, and productivity. It is found that proposed Radial Function Network achieved 0.7734f accuracy, 0.9834 of sensitivity, 0.8955 of hit rate and 0.77 of caching rate. en_US
dc.language.iso en_US en_US
dc.publisher Elsevier en_US
dc.subject Irrigation management en_US
dc.subject Radial function network en_US
dc.subject Agriculture en_US
dc.subject Renewable energy sources en_US
dc.subject Wireless sensor network en_US
dc.title IOT based smart irrigation management system for environmental sustainability in India en_US
dc.type Article en_US


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  • Research Articles [903]
    THESE ARE RESEARCH ARTICLES OF ACADEMIC STAFF, PUBLISHED IN JOURNALS AND PROCEEDINGS ELSWHERE

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