Kernel Metadata Declaration — on demand
ISO 26324 asks a DOI Registration Agency to produce a Kernel Metadata Declaration for every DOI it issues. Give any DOI: its public record becomes a record in the Smart Scholars DOI Metadata Format 1.0, checked against every rule, and declared as the Kernel XML.
✓ Meets every rule of the format
The record below is complete and every controlled value is a DOI Attribute Value Set 2.3 spelling. The Declaration on the right follows DOIMetadataKernel.xsd element by element.
What the DOI identifies
SMART CROP PROTECTION SYSTEM USING DEEP LEARNING
10.46243/jst.2024.v9.i11.pp01-20 · JournalArticle — an article in a journal · Digital · Visual · Language · en
Published 2024
Part of Journal of Science & Technology · ISSN 2456-5660 · vol. 09 · no. 11 · pp. 01–20
Principal agents
- G G. Jyothi (author → Author)
- M.Anilkumar (author → Author)
- G.Apoorva (author → Author)
- B.Manikanta (author → Author)
- M.Dhanraj (author → Author)
- Longman Publishers (publisher → Publisher)
Also in the record, outside the Kernel: the abstract, the licence, 4 links, 15 references. Source: Crossref (member 25296), registered 2026-09-24, last deposited 2026-09-27.
System metadata — ISO 26324:2025, Annex B · DOI Handbook 10.1
Each element by the standard's name and the Handbook's (in grey), read off the record.
| DOI Name DOI name | 10.46243/jst.2024.v9.i11.pp01-20 |
| Referent Type referentType | Creation |
| Referent Sub-Type referentSubType | JournalArticle — an article in a journal |
| Referent Name(s) referentName(s) | SMART CROP PROTECTION SYSTEM USING DEEP LEARNING (PrincipalTitle, en) |
| Basic Metadata basicMetadata | author: G G. Jyothi author: M.Anilkumar author: G.Apoorva author: B.Manikanta author: M.Dhanraj publisher: Longman Publishers published: 2024 part of: Journal of Science & Technology · ISSN 2456-5660 · vol. 09 · no. 11 · pp. 01–20 language: en form: Digital · Visual · Language |
| Referent Identifier(s) alternateIdentifier(s) | none besides the DOI |
| Registration Authority registrationAuthorityCode | Crossref — issued by Crossref (member 25296); held here as a copy |
| Created Date issueDate | 2026-09-24 |
| relatedIdentifiers | none needed — the descriptive metadata is in this record |
The record
{
"format": "smartscholars-doi-metadata/1.0",
"doi": "10.46243/jst.2024.v9.i11.pp01-20",
"referent": "Creation",
"type": "JournalArticle",
"structural_type": "Digital",
"modes": [
"Visual"
],
"characters": [
"Language"
],
"titles": [
{
"value": "SMART CROP PROTECTION SYSTEM USING DEEP LEARNING",
"type": "PrincipalTitle",
"lang": "en"
}
],
"identifiers": [
{
"type": "DOI",
"value": "10.46243/jst.2024.v9.i11.pp01-20"
}
],
"agents": [
{
"role": "author",
"name": {
"given": "",
"family": "G G. Jyothi"
},
"sequence": "first"
},
{
"role": "author",
"name": {
"given": "",
"family": "M.Anilkumar"
},
"sequence": "additional"
},
{
"role": "author",
"name": {
"given": "",
"family": "G.Apoorva"
},
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{
"role": "author",
"name": {
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"family": "B.Manikanta"
},
"sequence": "additional"
},
{
"role": "author",
"name": {
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"family": "M.Dhanraj"
},
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},
{
"role": "publisher",
"name": {
"org": "Longman Publishers"
}
}
],
"dates": {
"published": "2024",
"date_type": "PublicationDate",
"online": "2024"
},
"language": "en",
"container": {
"type": "Journal",
"titles": [
{
"value": "Journal of Science & Technology",
"type": "PrincipalTitle"
}
],
"identifiers": [
{
"type": "ISSN",
"value": "2456-5660",
"medium": "electronic"
}
],
"volume": "09",
"issue": "11",
"pages": {
"first": "01",
"last": "20"
}
},
"links": [
{
"url": "https://www.jst.org.in/index.php/pub/article/view/1063",
"return_type": "text/html",
"primary": true
},
{
"url": "https://www.jst.org.in/index.php/pub/article/download/1063/924",
"purpose": "text-mining",
"return_type": "application/pdf"
},
{
"url": "https://www.jst.org.in/index.php/pub/article/download/1063/4021",
"purpose": "text-mining",
"return_type": "application/xml"
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{
"url": "https://www.jst.org.in/index.php/pub/article/view/1063/924",
"purpose": "similarity-checking"
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],
"abstract": {
"value": "Agriterrorism with regard to animal damage greatly affects the crop yield for farmers, resulting to some of them recording large losses. Farm animals like buffaloes, cows, goats and birds trespass in the fields trample the crops and this can only be destructive for farmers since they cannot constantly protect their shambas. Measures such as the use of barriers, wire fences, or personnel vigilance yield most of the time insufficient results. In addition to scarecrows, which enemies can easily bypass with many animals, farmers also employ human effigies.To control these problems, we introduce an AI-based Scarecrow system using video processing in real- time for crop protection from wildlife. The system uses a camera to record videos and analyzes them with YOLOv3, an object detection model together with OpenCV and the COCO names database. If any animal or bird is identified, then the system produces a sound alerting the animal not to invade the compound. Moreover, if an animal has been sensed for more than one minute consecutively, the system will alert the farmer sending him/her an e-mail and dialing the farmer`s phone number. This approach thus provides an efficient and automated way of protecting crops than depending on deterrent measures.",
"lang": "en"
},
"license": {
"url": "https://creativecommons.org/licenses/by/4.0/",
"start": "2024-01-01",
"applies_to": "vor"
},
"references": [
{
"key": "ref1",
"unstructured": "M. A. Hossain, A. Haque, and M. Z. Hossain, “Smart agriculture monitoring and animal intrusion detection using AI,” Journal of Agricultural Informatics, vol. 11, no. 2, pp. 35- 42, 2021"
},
{
"key": "ref2",
"unstructured": "J. K. Patel and M. C. Gupta, “AI-based animal detection for crop protection,” IEEE Access, vol. 9, pp. 47538-47550, 2020"
},
{
"key": "ref3",
"unstructured": "R. Sharma and S. Kumar, “The role of IoT and AI in modern farming,” International Journal of Emerging Trends in Engineering Research, vol. 8, no. 4, pp. 1192-1201, 2020"
},
{
"key": "ref4",
"unstructured": "S. N. Singh and V. Singh, “A review on AIdriven solutions for smart farming,” Agricultural Engineering International: CIGR Journal, vol. 21, no. 3, pp. 105-117, 2019"
},
{
"key": "ref5",
"unstructured": "A. P. Mahesh and K. S. Rao, “Machine learning approaches for animal intrusion detection and crop protection,” International Journal of Advanced Science and Technology, vol. 29, no. 5, pp. 4025-4036, 2020"
},
{
"key": "ref6",
"unstructured": "P. Zhang and D. Huang, “Application of AI in sustainable agriculture: A comprehensive review,” Sustainable Computing: Informatics and Systems, vol. 32, pp. 100524, 2022"
},
{
"key": "ref7",
"unstructured": "M. Chakraborty and P. Ghosh, “AI and IoT integration in smart crop protection systems,” Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 1, pp. 234-240, 2021"
},
{
"key": "ref8",
"doi": "10.1002/9781394175376.ch12",
"unstructured": "Swathi, A., V. Swathi, Shilpa Choudhary, and Munish Kumar. “Wearable Gait Authentication: A Framework for Secure User Identification in Healthcare.” Optimized Predictive Models in Healthcare Using Machine Learning (2024): 195-214"
},
{
"key": "ref9",
"doi": "10.1002/9781394175512.ch8",
"unstructured": "Gowroju, Swathi, Shilpa Choudhary, Sandhya Raajaani, and Regula Srilakshmi. “Semantic Segmentation of Aerial Images Using Pixel Wise Segmentation.” Advances in Aerial Sensing and Imaging (2024): 145-164"
},
{
"key": "ref10",
"doi": "10.1002/9781394175512.ch11",
"unstructured": "Gowroju, Swathi, Shilpa Choudhary, Medipally Rishitha, Singanaboina Tejaswi, Lankala Shashank Reddy, and Mallepally Sujith Reddy. “Drone-Assisted Image Forgery Detection Using Generative Adversarial Net-Based Module.” Advances in Aerial Sensing and Imaging (2024): 245-266"
},
{
"key": "ref11",
"doi": "10.4018/979-8-3693-3253-5.ch008",
"unstructured": "Gowroju, Swathi, and Saurabh Karling. “Multinational Enterprises’ Digital Transformation, Sustainability, and Purpose: A Holistic View.” In Driving Decentralization and Disruption With Digital Technologies, pp. 108- 123. IGI Global, 2024"
},
{
"key": "ref12",
"doi": "10.1002/9781119785491.ch11",
"unstructured": "Gowroju, Swathi, V. Swathi, and Ankita Tiwari. “Handwriting and Speech-Based Secured Multimodal Biometrics Identification Technique.” Multimodal Biometric and Machine Learning Technologies: Applications for Computer Vision (2023): 227-250"
},
{
"key": "ref13",
"doi": "10.2174/9789815124514123010008",
"unstructured": "Gowroju, Swathi, V. Swathi, J. Narasimha Murthy, and D. Sai Kamesh. “Real-Time Object Detection and Localization for Autonomous Driving.” Handbook of Artificial Intelligence (2023): 112"
},
{
"key": "ref14",
"doi": "10.1002/9781394186570.ch6",
"unstructured": "Gowroju, Swathi, G. Mounika, D. Bhavana, Shaik Abdul Latheef, and A. Abhilash. “Artificial Intelligence–Based Active Virtual Voice Assistant.” Explainable Machine Learning Models and Architectures (2023): 81-103"
},
{
"key": "ref15",
"doi": "10.1002/9781394168002.ch8",
"unstructured": "Gowroju, Swathi, and N. Santhosh Ramchander. “Applications of Drones—A Review.” Drone Technology: Future Trends and Practical Applications (2023): 183-206"
}
],
"record": {
"registrant": "Longman Publishers",
"registered": "2026-09-24",
"updated": "2026-09-27",
"issue_number": 1,
"source": "crossref-api",
"source_agency": "Crossref (member 25296)"
}
}The Kernel Metadata Declaration
DOIMetadataKernel.xsd · namespace http://www.doi.org/2010/DOISchema · Attribute Value Sets 2.3 · draft — the agency's DOI name is filled in on accreditation
<?xml version="1.0" encoding="UTF-8"?>
<!-- DRAFT declaration: Smart Scholars is not yet a DOI Registration Agency. registrationAgencyDoiName is a marker (10.0/ is no RA's prefix) and is filled in on accreditation. -->
<kernelMetadata xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.doi.org/2010/DOISchema https://www.doi.org/doi_schemas/DOIMetadataKernel.xsd" xmlns="http://www.doi.org/2010/DOISchema">
<referentDoiName>10.46243/jst.2024.v9.i11.pp01-20</referentDoiName>
<primaryReferentType>Creation</primaryReferentType>
<registrationAgencyDoiName>10.0/smart-scholars-draft</registrationAgencyDoiName>
<issueDate>2026-10-04</issueDate>
<issueNumber>1</issueNumber>
<referentCreation>
<name primaryLanguage="en">
<value>SMART CROP PROTECTION SYSTEM USING DEEP LEARNING</value>
<type>PrincipalTitle</type>
</name>
<identifier>
<nonUriValue>10.46243/jst.2024.v9.i11.pp01-20</nonUriValue>
<uri returnType="text/html" doesContentNegotiation="true">https://doi.org/10.46243/jst.2024.v9.i11.pp01-20</uri>
<type>DOI</type>
</identifier>
<identifier>
<uri returnType="text/html">https://www.jst.org.in/index.php/pub/article/view/1063</uri>
<type>URI</type>
</identifier>
<identifier>
<uri>https://www.jst.org.in/index.php/pub/article/download/1063/924</uri>
<type>URI</type>
</identifier>
<identifier>
<uri returnType="application/xml">https://www.jst.org.in/index.php/pub/article/download/1063/4021</uri>
<type>URI</type>
</identifier>
<identifier>
<uri>https://www.jst.org.in/index.php/pub/article/view/1063/924</uri>
<type>URI</type>
</identifier>
<structuralType>Digital</structuralType>
<mode>Visual</mode>
<character>Language</character>
<type>JournalArticle</type>
<principalAgent>
<name>
<value>G G. Jyothi</value>
<type>PrincipalName</type>
</name>
<role>Author</role>
</principalAgent>
<principalAgent>
<name>
<value>M.Anilkumar</value>
<type>PrincipalName</type>
</name>
<role>Author</role>
</principalAgent>
<principalAgent>
<name>
<value>G.Apoorva</value>
<type>PrincipalName</type>
</name>
<role>Author</role>
</principalAgent>
<principalAgent>
<name>
<value>B.Manikanta</value>
<type>PrincipalName</type>
</name>
<role>Author</role>
</principalAgent>
<principalAgent>
<name>
<value>M.Dhanraj</value>
<type>PrincipalName</type>
</name>
<role>Author</role>
</principalAgent>
<principalAgent>
<name>
<value>Longman Publishers</value>
<type>PrincipalName</type>
</name>
<role>Publisher</role>
</principalAgent>
<linkedCreation>
<name>
<value>Journal of Science & Technology</value>
<type>PrincipalTitle</type>
</name>
<identifier>
<nonUriValue>2456-5660</nonUriValue>
<type>ISSN</type>
</identifier>
<referentCreationRole>Part</referentCreationRole>
<referentCreationSequenceIdentifier>
<value>09</value>
<type>VolumeNumber</type>
</referentCreationSequenceIdentifier>
<referentCreationSequenceIdentifier>
<value>11</value>
<type>IssueNumber</type>
</referentCreationSequenceIdentifier>
<referentCreationSequenceIdentifier>
<value>01-20</value>
<type>PageNumber</type>
</referentCreationSequenceIdentifier>
</linkedCreation>
<language>en</language>
<languageOfReferentContent>
<language>en</language>
<languageOfReferentContentType>Original</languageOfReferentContentType>
</languageOfReferentContent>
<creationDate>
<date>2024</date>
<creationDateType>PublicationDate</creationDateType>
</creationDate>
</referentCreation>
</kernelMetadata>
