Journal article Open Access

Smart Crop Monitor using Internet of Things, Cloud, Machine Learning and Android App

Yamini U.; Taha Sufiyan; Thankam Paul; Suyash Gupta; R. Chinnaiyan


DataCite XML Export

<?xml version='1.0' encoding='utf-8'?>
<resource xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://datacite.org/schema/kernel-4" xsi:schemaLocation="http://datacite.org/schema/kernel-4 http://schema.datacite.org/meta/kernel-4.1/metadata.xsd">
  <identifier identifierType="URL">https://zenodo.org/record/5591758</identifier>
  <creators>
    <creator>
      <creatorName>Yamini U.</creatorName>
      <affiliation>Department of Information Science and Engineering, CMR  Institute of Technology, Bengaluru, Karnataka, India</affiliation>
    </creator>
    <creator>
      <creatorName>Taha Sufiyan</creatorName>
      <affiliation>Department of Information Science and Engineering, CMR  Institute of Technology, Bengaluru, Karnataka, India</affiliation>
    </creator>
    <creator>
      <creatorName>Thankam Paul</creatorName>
      <affiliation>Department of Information Science and Engineering, CMR  Institute of Technology, Bengaluru, Karnataka, India</affiliation>
    </creator>
    <creator>
      <creatorName>Suyash Gupta</creatorName>
      <affiliation>Department of Information Science and Engineering, CMR  Institute of Technology, Bengaluru, Karnataka, India</affiliation>
    </creator>
    <creator>
      <creatorName>R. Chinnaiyan</creatorName>
      <affiliation>Associate Professor, Department of Information  Science and Engineering, CMR Institute of Technology, Bengaluru, India</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Smart Crop Monitor using Internet of Things,  Cloud, Machine Learning and Android App</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2020</publicationYear>
  <subjects>
    <subject>Smart Crop Monitoring, IoT, Machine Learning, Cloud, Android.</subject>
    <subject subjectScheme="issn">2249-8958</subject>
    <subject subjectScheme="handle">C6090029320/2020©BEIESP</subject>
  </subjects>
  <contributors>
    <contributor contributorType="Sponsor">
      <contributorName>Blue Eyes Intelligence Engineering  &amp; Sciences Publication(BEIESP)</contributorName>
      <affiliation>Publisher</affiliation>
    </contributor>
  </contributors>
  <dates>
    <date dateType="Issued">2020-02-29</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="JournalArticle"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/5591758</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="ISSN" relationType="IsCitedBy" resourceTypeGeneral="JournalArticle">2249-8958</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.35940/ijeat.C6090.029320</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;This paper describes a Smart Crop Monitoring system implemented using Internet of Things (IoT) for sensing environmental conditions and forwarding the data, Machine Learning to generate decisions for crop management based on the data, Cloud for storage and an Android application interface for operation of the system.&lt;/p&gt;</description>
  </descriptions>
</resource>
36
13
views
downloads
Views 36
Downloads 13
Data volume 11.6 MB
Unique views 36
Unique downloads 13

Share

Cite as