A Cloud Based Framework for Identification of IoT Devices at Smart Home Using Supervised Machine Intelligence Model Article Swipe
Sourav Kumar Bhoi
,
Krishna Prasad K.
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.5281/zenodo.7053965
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.5281/zenodo.7053965
Purpose: Identification of Internet of Thing (IoT) devices in smart home is the most important function for a local server/controller to administer and control the home smoothly. The IoT devices continuously send and receive requests, acknowledgements, packets, etc. for efficient data communication and these communication patterns need to be classified. Design/Methodology/Approach: Therefore, to run the smart home smoothly, in this work a framework using cloud computing is proposed to identify the correct IoT device communicating with the local server based on supervised machine learning. The best supervised machine intelligence model will be installed at the local server to classify the devices on the basis of data communication patterns. Findings/Result: Simulation is performed using Orange 3.26 data analytics tool by considering an IoT devices data communication dataset collected from Kaggle data repository. From the simulation results it is observed that Random Forest (RF) shows better performance than existing supervised machine learning models in terms of classification accuracy (CA) to classify the IoT devices with high accuracy. Originality/Value: A cloud based framework is proposed for a smart home to identify the correct IoT device communicating with the local server based on supervised machine learning. Based on the data communication pattern of the IoT devices, an IoT device is accurately identified. Paper Type: Methodology Paper.
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.5281/zenodo.7053965
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4294885535
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4294885535Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.5281/zenodo.7053965Digital Object Identifier
- Title
-
A Cloud Based Framework for Identification of IoT Devices at Smart Home Using Supervised Machine Intelligence ModelWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-09-06Full publication date if available
- Authors
-
Sourav Kumar Bhoi, Krishna Prasad K.List of authors in order
- Landing page
-
https://doi.org/10.5281/zenodo.7053965Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.5281/zenodo.7053965Direct OA link when available
- Concepts
-
Cloud computing, Internet of Things, Computer science, Identification (biology), Machine learning, Artificial intelligence, Embedded system, Operating system, Biology, BotanyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4294885535 |
|---|---|
| doi | https://doi.org/10.5281/zenodo.7053965 |
| ids.doi | https://doi.org/10.5281/zenodo.7053965 |
| ids.openalex | https://openalex.org/W4294885535 |
| fwci | 0.0 |
| type | article |
| title | A Cloud Based Framework for Identification of IoT Devices at Smart Home Using Supervised Machine Intelligence Model |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | |
| biblio.first_page | |
| topics[0].id | https://openalex.org/T12222 |
| topics[0].field.id | https://openalex.org/fields/22 |
| topics[0].field.display_name | Engineering |
| topics[0].score | 0.8438000082969666 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2208 |
| topics[0].subfield.display_name | Electrical and Electronic Engineering |
| topics[0].display_name | IoT-based Smart Home Systems |
| topics[1].id | https://openalex.org/T10273 |
| topics[1].field.id | https://openalex.org/fields/17 |
| topics[1].field.display_name | Computer Science |
| topics[1].score | 0.7994999885559082 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/1705 |
| topics[1].subfield.display_name | Computer Networks and Communications |
| topics[1].display_name | IoT and Edge/Fog Computing |
| topics[2].id | https://openalex.org/T13038 |
| topics[2].field.id | https://openalex.org/fields/17 |
| topics[2].field.display_name | Computer Science |
| topics[2].score | 0.73089998960495 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/1710 |
| topics[2].subfield.display_name | Information Systems |
| topics[2].display_name | Internet of Things and AI |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C79974875 |
| concepts[0].level | 2 |
| concepts[0].score | 0.7808299660682678 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q483639 |
| concepts[0].display_name | Cloud computing |
| concepts[1].id | https://openalex.org/C81860439 |
| concepts[1].level | 2 |
| concepts[1].score | 0.738540530204773 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q251212 |
| concepts[1].display_name | Internet of Things |
| concepts[2].id | https://openalex.org/C41008148 |
| concepts[2].level | 0 |
| concepts[2].score | 0.700492799282074 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[2].display_name | Computer science |
| concepts[3].id | https://openalex.org/C116834253 |
| concepts[3].level | 2 |
| concepts[3].score | 0.6690713763237 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q2039217 |
| concepts[3].display_name | Identification (biology) |
| concepts[4].id | https://openalex.org/C119857082 |
| concepts[4].level | 1 |
| concepts[4].score | 0.42230409383773804 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q2539 |
| concepts[4].display_name | Machine learning |
| concepts[5].id | https://openalex.org/C154945302 |
| concepts[5].level | 1 |
| concepts[5].score | 0.41055500507354736 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[5].display_name | Artificial intelligence |
| concepts[6].id | https://openalex.org/C149635348 |
| concepts[6].level | 1 |
| concepts[6].score | 0.3540763854980469 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q193040 |
| concepts[6].display_name | Embedded system |
| concepts[7].id | https://openalex.org/C111919701 |
| concepts[7].level | 1 |
| concepts[7].score | 0.1479930579662323 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q9135 |
| concepts[7].display_name | Operating system |
| concepts[8].id | https://openalex.org/C86803240 |
| concepts[8].level | 0 |
| concepts[8].score | 0.0 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q420 |
| concepts[8].display_name | Biology |
| concepts[9].id | https://openalex.org/C59822182 |
| concepts[9].level | 1 |
| concepts[9].score | 0.0 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q441 |
| concepts[9].display_name | Botany |
| keywords[0].id | https://openalex.org/keywords/cloud-computing |
| keywords[0].score | 0.7808299660682678 |
| keywords[0].display_name | Cloud computing |
| keywords[1].id | https://openalex.org/keywords/internet-of-things |
| keywords[1].score | 0.738540530204773 |
| keywords[1].display_name | Internet of Things |
| keywords[2].id | https://openalex.org/keywords/computer-science |
| keywords[2].score | 0.700492799282074 |
| keywords[2].display_name | Computer science |
| keywords[3].id | https://openalex.org/keywords/identification |
| keywords[3].score | 0.6690713763237 |
| keywords[3].display_name | Identification (biology) |
| keywords[4].id | https://openalex.org/keywords/machine-learning |
| keywords[4].score | 0.42230409383773804 |
| keywords[4].display_name | Machine learning |
| keywords[5].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[5].score | 0.41055500507354736 |
| keywords[5].display_name | Artificial intelligence |
| keywords[6].id | https://openalex.org/keywords/embedded-system |
| keywords[6].score | 0.3540763854980469 |
| keywords[6].display_name | Embedded system |
| keywords[7].id | https://openalex.org/keywords/operating-system |
| keywords[7].score | 0.1479930579662323 |
| keywords[7].display_name | Operating system |
| language | en |
| locations[0].id | doi:10.5281/zenodo.7053965 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S4306400562 |
| locations[0].source.issn | |
| locations[0].source.type | repository |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | |
| locations[0].source.is_core | False |
| locations[0].source.is_in_doaj | False |
| locations[0].source.display_name | Zenodo (CERN European Organization for Nuclear Research) |
| locations[0].source.host_organization | https://openalex.org/I67311998 |
| locations[0].source.host_organization_name | European Organization for Nuclear Research |
| locations[0].source.host_organization_lineage | https://openalex.org/I67311998 |
| locations[0].license | cc-by |
| locations[0].pdf_url | |
| locations[0].version | |
| locations[0].raw_type | article-journal |
| locations[0].license_id | https://openalex.org/licenses/cc-by |
| locations[0].is_accepted | False |
| locations[0].is_published | |
| locations[0].raw_source_name | |
| locations[0].landing_page_url | https://doi.org/10.5281/zenodo.7053965 |
| indexed_in | datacite |
| authorships[0].author.id | https://openalex.org/A5044453219 |
| authorships[0].author.orcid | https://orcid.org/0000-0002-5173-3453 |
| authorships[0].author.display_name | Sourav Kumar Bhoi |
| authorships[0].countries | IN |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I19008122 |
| authorships[0].affiliations[0].raw_affiliation_string | Post-Doctoral Fellow, Institute of Computer Science and Information Science, Srinivas University, Mangaluru-575001, Karnataka, India |
| authorships[0].institutions[0].id | https://openalex.org/I19008122 |
| authorships[0].institutions[0].ror | https://ror.org/05fep3933 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I19008122 |
| authorships[0].institutions[0].country_code | IN |
| authorships[0].institutions[0].display_name | Mangalore University |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Sourav Kumar Bhoi |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | Post-Doctoral Fellow, Institute of Computer Science and Information Science, Srinivas University, Mangaluru-575001, Karnataka, India |
| authorships[1].author.id | https://openalex.org/A5113065872 |
| authorships[1].author.orcid | |
| authorships[1].author.display_name | Krishna Prasad K. |
| authorships[1].countries | IN |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I19008122 |
| authorships[1].affiliations[0].raw_affiliation_string | Associate Professor, Institute of Computer Science and Information Science, Srinivas University, Mangaluru-575001, Karnataka, India |
| authorships[1].institutions[0].id | https://openalex.org/I19008122 |
| authorships[1].institutions[0].ror | https://ror.org/05fep3933 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I19008122 |
| authorships[1].institutions[0].country_code | IN |
| authorships[1].institutions[0].display_name | Mangalore University |
| authorships[1].author_position | last |
| authorships[1].raw_author_name | Krishna Prasad K. |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Associate Professor, Institute of Computer Science and Information Science, Srinivas University, Mangaluru-575001, Karnataka, India |
| has_content.pdf | False |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://doi.org/10.5281/zenodo.7053965 |
| open_access.oa_status | green |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | A Cloud Based Framework for Identification of IoT Devices at Smart Home Using Supervised Machine Intelligence Model |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T06:51:31.235846 |
| primary_topic.id | https://openalex.org/T12222 |
| primary_topic.field.id | https://openalex.org/fields/22 |
| primary_topic.field.display_name | Engineering |
| primary_topic.score | 0.8438000082969666 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2208 |
| primary_topic.subfield.display_name | Electrical and Electronic Engineering |
| primary_topic.display_name | IoT-based Smart Home Systems |
| related_works | https://openalex.org/W4244478748, https://openalex.org/W4311097251, https://openalex.org/W4223488648, https://openalex.org/W2134969820, https://openalex.org/W2251605416, https://openalex.org/W4389340727, https://openalex.org/W4205786897, https://openalex.org/W3150465815, https://openalex.org/W2802581102, https://openalex.org/W1997222214 |
| cited_by_count | 0 |
| locations_count | 1 |
| best_oa_location.id | doi:10.5281/zenodo.7053965 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S4306400562 |
| best_oa_location.source.issn | |
| best_oa_location.source.type | repository |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | |
| best_oa_location.source.is_core | False |
| best_oa_location.source.is_in_doaj | False |
| best_oa_location.source.display_name | Zenodo (CERN European Organization for Nuclear Research) |
| best_oa_location.source.host_organization | https://openalex.org/I67311998 |
| best_oa_location.source.host_organization_name | European Organization for Nuclear Research |
| best_oa_location.source.host_organization_lineage | https://openalex.org/I67311998 |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | |
| best_oa_location.version | |
| best_oa_location.raw_type | article-journal |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by |
| best_oa_location.is_accepted | False |
| best_oa_location.is_published | False |
| best_oa_location.raw_source_name | |
| best_oa_location.landing_page_url | https://doi.org/10.5281/zenodo.7053965 |
| primary_location.id | doi:10.5281/zenodo.7053965 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S4306400562 |
| primary_location.source.issn | |
| primary_location.source.type | repository |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | |
| primary_location.source.is_core | False |
| primary_location.source.is_in_doaj | False |
| primary_location.source.display_name | Zenodo (CERN European Organization for Nuclear Research) |
| primary_location.source.host_organization | https://openalex.org/I67311998 |
| primary_location.source.host_organization_name | European Organization for Nuclear Research |
| primary_location.source.host_organization_lineage | https://openalex.org/I67311998 |
| primary_location.license | cc-by |
| primary_location.pdf_url | |
| primary_location.version | |
| primary_location.raw_type | article-journal |
| primary_location.license_id | https://openalex.org/licenses/cc-by |
| primary_location.is_accepted | False |
| primary_location.is_published | False |
| primary_location.raw_source_name | |
| primary_location.landing_page_url | https://doi.org/10.5281/zenodo.7053965 |
| publication_date | 2022-09-06 |
| publication_year | 2022 |
| referenced_works_count | 0 |
| abstract_inverted_index.a | 17, 61, 173 |
| abstract_inverted_index.an | 120, 202 |
| abstract_inverted_index.at | 93 |
| abstract_inverted_index.be | 48, 91 |
| abstract_inverted_index.by | 118 |
| abstract_inverted_index.in | 8, 58, 151 |
| abstract_inverted_index.is | 11, 66, 110, 136, 170, 205 |
| abstract_inverted_index.it | 135 |
| abstract_inverted_index.of | 2, 4, 104, 153, 198 |
| abstract_inverted_index.on | 80, 101, 188, 193 |
| abstract_inverted_index.to | 20, 47, 52, 68, 97, 157, 176 |
| abstract_inverted_index.IoT | 28, 72, 121, 160, 180, 200, 203 |
| abstract_inverted_index.The | 27, 84 |
| abstract_inverted_index.and | 22, 32, 42 |
| abstract_inverted_index.for | 16, 38, 172 |
| abstract_inverted_index.run | 53 |
| abstract_inverted_index.the | 12, 24, 54, 70, 76, 94, 99, 102, 132, 159, 178, 184, 194, 199 |
| abstract_inverted_index.(CA) | 156 |
| abstract_inverted_index.(RF) | 141 |
| abstract_inverted_index.3.26 | 114 |
| abstract_inverted_index.From | 131 |
| abstract_inverted_index.best | 85 |
| abstract_inverted_index.data | 40, 105, 115, 123, 129, 195 |
| abstract_inverted_index.etc. | 37 |
| abstract_inverted_index.from | 127 |
| abstract_inverted_index.high | 163 |
| abstract_inverted_index.home | 10, 25, 56, 175 |
| abstract_inverted_index.most | 13 |
| abstract_inverted_index.need | 46 |
| abstract_inverted_index.send | 31 |
| abstract_inverted_index.than | 145 |
| abstract_inverted_index.that | 138 |
| abstract_inverted_index.this | 59 |
| abstract_inverted_index.tool | 117 |
| abstract_inverted_index.will | 90 |
| abstract_inverted_index.with | 75, 162, 183 |
| abstract_inverted_index.work | 60 |
| abstract_inverted_index.(IoT) | 6 |
| abstract_inverted_index.</em> | 208 |
| abstract_inverted_index.Based | 192 |
| abstract_inverted_index.Thing | 5 |
| abstract_inverted_index.Type: | 210 |
| abstract_inverted_index.based | 79, 168, 187 |
| abstract_inverted_index.basis | 103 |
| abstract_inverted_index.cloud | 64 |
| abstract_inverted_index.local | 18, 77, 95, 185 |
| abstract_inverted_index.model | 89 |
| abstract_inverted_index.shows | 142 |
| abstract_inverted_index.smart | 9, 55, 174 |
| abstract_inverted_index.terms | 152 |
| abstract_inverted_index.these | 43 |
| abstract_inverted_index.using | 63, 112 |
| abstract_inverted_index.Forest | 140 |
| abstract_inverted_index.Kaggle | 128 |
| abstract_inverted_index.Orange | 113 |
| abstract_inverted_index.Random | 139 |
| abstract_inverted_index.better | 143 |
| abstract_inverted_index.device | 73, 181, 204 |
| abstract_inverted_index.models | 150 |
| abstract_inverted_index.server | 78, 96, 186 |
| abstract_inverted_index.control | 23 |
| abstract_inverted_index.correct | 71, 179 |
| abstract_inverted_index.dataset | 125 |
| abstract_inverted_index.devices | 7, 29, 100, 122, 161 |
| abstract_inverted_index.machine | 82, 87, 148, 190 |
| abstract_inverted_index.pattern | 197 |
| abstract_inverted_index.receive | 33 |
| abstract_inverted_index.results | 134 |
| abstract_inverted_index.Internet | 3 |
| abstract_inverted_index.accuracy | 155 |
| abstract_inverted_index.classify | 98, 158 |
| abstract_inverted_index.devices, | 201 |
| abstract_inverted_index.existing | 146 |
| abstract_inverted_index.function | 15 |
| abstract_inverted_index.identify | 69, 177 |
| abstract_inverted_index.learning | 149 |
| abstract_inverted_index.observed | 137 |
| abstract_inverted_index.packets, | 36 |
| abstract_inverted_index.patterns | 45 |
| abstract_inverted_index.proposed | 67, 171 |
| abstract_inverted_index.analytics | 116 |
| abstract_inverted_index.collected | 126 |
| abstract_inverted_index.computing | 65 |
| abstract_inverted_index.efficient | 39 |
| abstract_inverted_index.framework | 62, 169 |
| abstract_inverted_index.important | 14 |
| abstract_inverted_index.installed | 92 |
| abstract_inverted_index.learning. | 83, 191 |
| abstract_inverted_index.performed | 111 |
| abstract_inverted_index.requests, | 34 |
| abstract_inverted_index.smoothly, | 57 |
| abstract_inverted_index.smoothly. | 26 |
| abstract_inverted_index.accurately | 206 |
| abstract_inverted_index.administer | 21 |
| abstract_inverted_index.simulation | 133 |
| abstract_inverted_index.supervised | 81, 86, 147, 189 |
| abstract_inverted_index.Paper.</em> | 212 |
| abstract_inverted_index.considering | 119 |
| abstract_inverted_index.identified. | 207 |
| abstract_inverted_index.performance | 144 |
| abstract_inverted_index.repository. | 130 |
| abstract_inverted_index.continuously | 30 |
| abstract_inverted_index.intelligence | 88 |
| abstract_inverted_index.<strong>Paper | 209 |
| abstract_inverted_index.communicating | 74, 182 |
| abstract_inverted_index.communication | 41, 44, 106, 124, 196 |
| abstract_inverted_index.</em><em>cloud | 167 |
| abstract_inverted_index.</strong><em>A | 166 |
| abstract_inverted_index.<em>Therefore, | 51 |
| abstract_inverted_index.accuracy.</em> | 164 |
| abstract_inverted_index.classification | 154 |
| abstract_inverted_index.patterns.</em> | 107 |
| abstract_inverted_index.<strong>Purpose: | 0 |
| abstract_inverted_index.classified.</em> | 49 |
| abstract_inverted_index.acknowledgements, | 35 |
| abstract_inverted_index.server/controller | 19 |
| abstract_inverted_index.</strong><em>Simulation | 109 |
| abstract_inverted_index.</strong><em>Methodology | 211 |
| abstract_inverted_index.<strong>Findings/Result: | 108 |
| abstract_inverted_index.<strong>Originality/Value: | 165 |
| abstract_inverted_index.</strong><em>Identification | 1 |
| abstract_inverted_index.<strong>Design/Methodology/Approach</strong>: | 50 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 2 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/9 |
| sustainable_development_goals[0].score | 0.4300000071525574 |
| sustainable_development_goals[0].display_name | Industry, innovation and infrastructure |
| citation_normalized_percentile.value | 0.08913248 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |