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Dublin Core
The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.
Title
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Conference Papers
Conference Paper
Faculty Publications- Conference Papers
Dublin Core
The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.
Title
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Internet of Things and Machine Learning based Intelligent Irrigation System for Agriculture
Subject
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Internet of Things (IoT); IoT in Agriculture; Irrigation System; Machine Learning
Description
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Irrigated agriculture methods need a significant volume of water, and causes water waste. It is critically necessary to install an efficient watering system and lessen the volume of water wasted on this tiresome chore. It is a huge benefit of the computer vision (ML) - the Internet of Everything (Ot) era to construct expert machines that carry out this work successfully with little human endeavour. This work suggests an Embedded device Fluid ounces suggestion method for efficient water use with little farm involvement. In the agricultural field, IoT sensors are set up to capture important atmospheric and surface data. The obtained information is sent to and stored on a cloud-based server, where machine learning techniques are used to evaluate the information and recommend treatment to the farmers. This recommender system has an internal development process that makes the solution resilient and flexible. The test demonstrates that the suggested method operates admirably on the agricultural dataset from the National Institutes of Technology (Kit) Bhubaneswar as well as the information that we obtained. 2022 IEEE.
Creator
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Alanya-Arango J.; Alanya-Beltran J.; Ravichandran S.K.; Singh B.; Sasi A.; Gangodkar D.
Source
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Proceedings of 5th International Conference on Contemporary Computing and Informatics, IC3I 2022, pp. 67-72.
Publisher
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Institute of Electrical and Electronics Engineers Inc.
Date
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2022-01-01
Identifier
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<a href="https://doi.org/10.1109/IC3I56241.2022.10073254" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/IC3I56241.2022.10073254</a>
<br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85151959209&doi=10.1109%2FIC3I56241.2022.10073254&partnerID=40&md5=ed98ba1bab5831895f8f9d9320bc1a73" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85151959209&doi=10.1109%2fIC3I56241.2022.10073254&partnerID=40&md5=ed98ba1bab5831895f8f9d9320bc1a73</a>
Rights
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Restricted Access
Relation
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ISBN: 979-835039826-7
Format
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Online
Language
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English
Type
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Conference paper
Coverage
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Alanya-Arango J., Ministerio de Desarrollo Agrarioy Riego Del Per(MIDAGRI), Peru; Alanya-Beltran J., Universidad Tecnolica Del Per Department of Electronic, Peru; Ravichandran S.K., Christ University, Department of Computer Science and Engineering, Karnataka, Bangalore, India; Singh B., I.K.Gujral Punjab Technical University, Punjab, Kapurthala, India; Sasi A., Presidency University, Itgalpur Rajanakunte, Department of CSE, Bangalore, Karnataka, Yelahanka, India; Gangodkar D., Graphic Era Deemed to Be University, Department of CSE, Uttarakhand, Dehradun, India