An optimal energy utilization model for precision agriculture in WSNs using multi-objective clustering and deep learning Article Swipe
V. Pandiyaraju
,
Sannasi Ganapathy
,
N. Mohith
,
A. Kannan
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1016/j.jksuci.2023.101803
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1016/j.jksuci.2023.101803
Wireless Sensor Networks (WSNs) play a crucial role in Precision Agriculture by providing real-time data on various environmental parameters like temperature, humidity, soil moisture, etc. However, the efficient utilization of energy in the sensor nodes of WSNs is a major challenge that needs to be addressed. To address this issue, a new multi-objective clustering approach is introduced in this work for grouping the sensor nodes of WSNs. Moreover, a multi-objective hybrid optimisation technique called Election based Aquila Optimizer (EAO) which is the combination of Aquila Optimizer (AO) and the Election-Based Optimisation Algorithm (EBOA) is proposed in this work to make sure that the Cluster Head (CH) selection process in WSNs to identify the best CH. In addition, the proposed method incorporates the newly developed optimization technique with convolutional neural network (CNN) as an Optimized CNN (O-CNN) to improve the clustering algorithm's precision and also enhance the training accuracy and testing accuracy. The proposed approach is evaluated through experiments and proved as better than other approaches by obtaining 99.23% as classification accuracy, 76.92% as throughput, 99% as packet delivery ratio, 98.24% as network lifetime and 50% as maximum energy consumption and it resolves a significant difficulty in precision agriculture.
Related Topics
Concepts
Wireless sensor network
Cluster analysis
Computer science
Energy consumption
Throughput
Network packet
Data mining
Efficient energy use
Process (computing)
Precision agriculture
Energy (signal processing)
Real-time computing
Artificial intelligence
Wireless
Agriculture
Computer network
Engineering
Mathematics
Biology
Electrical engineering
Operating system
Ecology
Statistics
Telecommunications
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.jksuci.2023.101803
- OA Status
- hybrid
- Cited By
- 38
- References
- 51
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4387745802
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4387745802Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1016/j.jksuci.2023.101803Digital Object Identifier
- Title
-
An optimal energy utilization model for precision agriculture in WSNs using multi-objective clustering and deep learningWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-10-18Full publication date if available
- Authors
-
V. Pandiyaraju, Sannasi Ganapathy, N. Mohith, A. KannanList of authors in order
- Landing page
-
https://doi.org/10.1016/j.jksuci.2023.101803Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
hybridOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.1016/j.jksuci.2023.101803Direct OA link when available
- Concepts
-
Wireless sensor network, Cluster analysis, Computer science, Energy consumption, Throughput, Network packet, Data mining, Efficient energy use, Process (computing), Precision agriculture, Energy (signal processing), Real-time computing, Artificial intelligence, Wireless, Agriculture, Computer network, Engineering, Mathematics, Biology, Electrical engineering, Operating system, Ecology, Statistics, TelecommunicationsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
38Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 27, 2024: 11Per-year citation counts (last 5 years)
- References (count)
-
51Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4387745802 |
|---|---|
| doi | https://doi.org/10.1016/j.jksuci.2023.101803 |
| ids.doi | https://doi.org/10.1016/j.jksuci.2023.101803 |
| ids.openalex | https://openalex.org/W4387745802 |
| fwci | 10.03884884 |
| type | article |
| title | An optimal energy utilization model for precision agriculture in WSNs using multi-objective clustering and deep learning |
| biblio.issue | 10 |
| biblio.volume | 35 |
| biblio.last_page | 101803 |
| biblio.first_page | 101803 |
| topics[0].id | https://openalex.org/T10616 |
| topics[0].field.id | https://openalex.org/fields/11 |
| topics[0].field.display_name | Agricultural and Biological Sciences |
| topics[0].score | 0.9857000112533569 |
| topics[0].domain.id | https://openalex.org/domains/1 |
| topics[0].domain.display_name | Life Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/1110 |
| topics[0].subfield.display_name | Plant Science |
| topics[0].display_name | Smart Agriculture and AI |
| topics[1].id | https://openalex.org/T13567 |
| topics[1].field.id | https://openalex.org/fields/17 |
| topics[1].field.display_name | Computer Science |
| topics[1].score | 0.911899983882904 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/1702 |
| topics[1].subfield.display_name | Artificial Intelligence |
| topics[1].display_name | AI and Multimedia in Education |
| funders[0].id | https://openalex.org/F4320319346 |
| funders[0].ror | |
| funders[0].display_name | Vellore Institute of Technology, Chennai |
| is_xpac | False |
| apc_list.value | 1350 |
| apc_list.currency | USD |
| apc_list.value_usd | 1350 |
| apc_paid.value | 1350 |
| apc_paid.currency | USD |
| apc_paid.value_usd | 1350 |
| concepts[0].id | https://openalex.org/C24590314 |
| concepts[0].level | 2 |
| concepts[0].score | 0.7598148584365845 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q336038 |
| concepts[0].display_name | Wireless sensor network |
| concepts[1].id | https://openalex.org/C73555534 |
| concepts[1].level | 2 |
| concepts[1].score | 0.7360547780990601 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q622825 |
| concepts[1].display_name | Cluster analysis |
| concepts[2].id | https://openalex.org/C41008148 |
| concepts[2].level | 0 |
| concepts[2].score | 0.7282240986824036 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[2].display_name | Computer science |
| concepts[3].id | https://openalex.org/C2780165032 |
| concepts[3].level | 2 |
| concepts[3].score | 0.6096657514572144 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q16869822 |
| concepts[3].display_name | Energy consumption |
| concepts[4].id | https://openalex.org/C157764524 |
| concepts[4].level | 3 |
| concepts[4].score | 0.5951054096221924 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q1383412 |
| concepts[4].display_name | Throughput |
| concepts[5].id | https://openalex.org/C158379750 |
| concepts[5].level | 2 |
| concepts[5].score | 0.5598829984664917 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q214111 |
| concepts[5].display_name | Network packet |
| concepts[6].id | https://openalex.org/C124101348 |
| concepts[6].level | 1 |
| concepts[6].score | 0.5235047936439514 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q172491 |
| concepts[6].display_name | Data mining |
| concepts[7].id | https://openalex.org/C2742236 |
| concepts[7].level | 2 |
| concepts[7].score | 0.5195887088775635 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q924713 |
| concepts[7].display_name | Efficient energy use |
| concepts[8].id | https://openalex.org/C98045186 |
| concepts[8].level | 2 |
| concepts[8].score | 0.5040265917778015 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q205663 |
| concepts[8].display_name | Process (computing) |
| concepts[9].id | https://openalex.org/C120217122 |
| concepts[9].level | 3 |
| concepts[9].score | 0.5024092197418213 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q740083 |
| concepts[9].display_name | Precision agriculture |
| concepts[10].id | https://openalex.org/C186370098 |
| concepts[10].level | 2 |
| concepts[10].score | 0.4171590209007263 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q442787 |
| concepts[10].display_name | Energy (signal processing) |
| concepts[11].id | https://openalex.org/C79403827 |
| concepts[11].level | 1 |
| concepts[11].score | 0.3862447142601013 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q3988 |
| concepts[11].display_name | Real-time computing |
| concepts[12].id | https://openalex.org/C154945302 |
| concepts[12].level | 1 |
| concepts[12].score | 0.349656343460083 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[12].display_name | Artificial intelligence |
| concepts[13].id | https://openalex.org/C555944384 |
| concepts[13].level | 2 |
| concepts[13].score | 0.2292715609073639 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q249 |
| concepts[13].display_name | Wireless |
| concepts[14].id | https://openalex.org/C118518473 |
| concepts[14].level | 2 |
| concepts[14].score | 0.190296471118927 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q11451 |
| concepts[14].display_name | Agriculture |
| concepts[15].id | https://openalex.org/C31258907 |
| concepts[15].level | 1 |
| concepts[15].score | 0.17336338758468628 |
| concepts[15].wikidata | https://www.wikidata.org/wiki/Q1301371 |
| concepts[15].display_name | Computer network |
| concepts[16].id | https://openalex.org/C127413603 |
| concepts[16].level | 0 |
| concepts[16].score | 0.13764721155166626 |
| concepts[16].wikidata | https://www.wikidata.org/wiki/Q11023 |
| concepts[16].display_name | Engineering |
| concepts[17].id | https://openalex.org/C33923547 |
| concepts[17].level | 0 |
| concepts[17].score | 0.08505499362945557 |
| concepts[17].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[17].display_name | Mathematics |
| concepts[18].id | https://openalex.org/C86803240 |
| concepts[18].level | 0 |
| concepts[18].score | 0.0 |
| concepts[18].wikidata | https://www.wikidata.org/wiki/Q420 |
| concepts[18].display_name | Biology |
| concepts[19].id | https://openalex.org/C119599485 |
| concepts[19].level | 1 |
| concepts[19].score | 0.0 |
| concepts[19].wikidata | https://www.wikidata.org/wiki/Q43035 |
| concepts[19].display_name | Electrical engineering |
| concepts[20].id | https://openalex.org/C111919701 |
| concepts[20].level | 1 |
| concepts[20].score | 0.0 |
| concepts[20].wikidata | https://www.wikidata.org/wiki/Q9135 |
| concepts[20].display_name | Operating system |
| concepts[21].id | https://openalex.org/C18903297 |
| concepts[21].level | 1 |
| concepts[21].score | 0.0 |
| concepts[21].wikidata | https://www.wikidata.org/wiki/Q7150 |
| concepts[21].display_name | Ecology |
| concepts[22].id | https://openalex.org/C105795698 |
| concepts[22].level | 1 |
| concepts[22].score | 0.0 |
| concepts[22].wikidata | https://www.wikidata.org/wiki/Q12483 |
| concepts[22].display_name | Statistics |
| concepts[23].id | https://openalex.org/C76155785 |
| concepts[23].level | 1 |
| concepts[23].score | 0.0 |
| concepts[23].wikidata | https://www.wikidata.org/wiki/Q418 |
| concepts[23].display_name | Telecommunications |
| keywords[0].id | https://openalex.org/keywords/wireless-sensor-network |
| keywords[0].score | 0.7598148584365845 |
| keywords[0].display_name | Wireless sensor network |
| keywords[1].id | https://openalex.org/keywords/cluster-analysis |
| keywords[1].score | 0.7360547780990601 |
| keywords[1].display_name | Cluster analysis |
| keywords[2].id | https://openalex.org/keywords/computer-science |
| keywords[2].score | 0.7282240986824036 |
| keywords[2].display_name | Computer science |
| keywords[3].id | https://openalex.org/keywords/energy-consumption |
| keywords[3].score | 0.6096657514572144 |
| keywords[3].display_name | Energy consumption |
| keywords[4].id | https://openalex.org/keywords/throughput |
| keywords[4].score | 0.5951054096221924 |
| keywords[4].display_name | Throughput |
| keywords[5].id | https://openalex.org/keywords/network-packet |
| keywords[5].score | 0.5598829984664917 |
| keywords[5].display_name | Network packet |
| keywords[6].id | https://openalex.org/keywords/data-mining |
| keywords[6].score | 0.5235047936439514 |
| keywords[6].display_name | Data mining |
| keywords[7].id | https://openalex.org/keywords/efficient-energy-use |
| keywords[7].score | 0.5195887088775635 |
| keywords[7].display_name | Efficient energy use |
| keywords[8].id | https://openalex.org/keywords/process |
| keywords[8].score | 0.5040265917778015 |
| keywords[8].display_name | Process (computing) |
| keywords[9].id | https://openalex.org/keywords/precision-agriculture |
| keywords[9].score | 0.5024092197418213 |
| keywords[9].display_name | Precision agriculture |
| keywords[10].id | https://openalex.org/keywords/energy |
| keywords[10].score | 0.4171590209007263 |
| keywords[10].display_name | Energy (signal processing) |
| keywords[11].id | https://openalex.org/keywords/real-time-computing |
| keywords[11].score | 0.3862447142601013 |
| keywords[11].display_name | Real-time computing |
| keywords[12].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[12].score | 0.349656343460083 |
| keywords[12].display_name | Artificial intelligence |
| keywords[13].id | https://openalex.org/keywords/wireless |
| keywords[13].score | 0.2292715609073639 |
| keywords[13].display_name | Wireless |
| keywords[14].id | https://openalex.org/keywords/agriculture |
| keywords[14].score | 0.190296471118927 |
| keywords[14].display_name | Agriculture |
| keywords[15].id | https://openalex.org/keywords/computer-network |
| keywords[15].score | 0.17336338758468628 |
| keywords[15].display_name | Computer network |
| keywords[16].id | https://openalex.org/keywords/engineering |
| keywords[16].score | 0.13764721155166626 |
| keywords[16].display_name | Engineering |
| keywords[17].id | https://openalex.org/keywords/mathematics |
| keywords[17].score | 0.08505499362945557 |
| keywords[17].display_name | Mathematics |
| language | en |
| locations[0].id | doi:10.1016/j.jksuci.2023.101803 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S2764955546 |
| locations[0].source.issn | 1319-1578, 2213-1248 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | False |
| locations[0].source.issn_l | 1319-1578 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | True |
| locations[0].source.display_name | Journal of King Saud University - Computer and Information Sciences |
| locations[0].source.host_organization | https://openalex.org/P4310320990 |
| locations[0].source.host_organization_name | Elsevier BV |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310320990 |
| locations[0].source.host_organization_lineage_names | Elsevier BV |
| locations[0].license | cc-by-nc-nd |
| locations[0].pdf_url | |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | https://openalex.org/licenses/cc-by-nc-nd |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | Journal of King Saud University - Computer and Information Sciences |
| locations[0].landing_page_url | https://doi.org/10.1016/j.jksuci.2023.101803 |
| locations[1].id | pmh:oai:doaj.org/article:8a326ddd02264b5a86686d5d6214a1f3 |
| locations[1].is_oa | False |
| locations[1].source.id | https://openalex.org/S4306401280 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | False |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | DOAJ (DOAJ: Directory of Open Access Journals) |
| locations[1].source.host_organization | |
| locations[1].source.host_organization_name | |
| locations[1].license | |
| locations[1].pdf_url | |
| locations[1].version | submittedVersion |
| locations[1].raw_type | article |
| locations[1].license_id | |
| locations[1].is_accepted | False |
| locations[1].is_published | False |
| locations[1].raw_source_name | Journal of King Saud University: Computer and Information Sciences, Vol 35, Iss 10, Pp 101803- (2023) |
| locations[1].landing_page_url | https://doaj.org/article/8a326ddd02264b5a86686d5d6214a1f3 |
| indexed_in | crossref, doaj |
| authorships[0].author.id | https://openalex.org/A5060650234 |
| authorships[0].author.orcid | |
| authorships[0].author.display_name | V. Pandiyaraju |
| authorships[0].countries | IN |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I876193797 |
| authorships[0].affiliations[0].raw_affiliation_string | School of Computer Science and Engineering, Vellore Institute of Technology, Chennai |
| authorships[0].institutions[0].id | https://openalex.org/I876193797 |
| authorships[0].institutions[0].ror | https://ror.org/00qzypv28 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I876193797 |
| authorships[0].institutions[0].country_code | IN |
| authorships[0].institutions[0].display_name | Vellore Institute of Technology University |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | V. Pandiyaraju |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | School of Computer Science and Engineering, Vellore Institute of Technology, Chennai |
| authorships[1].author.id | https://openalex.org/A5108977851 |
| authorships[1].author.orcid | |
| authorships[1].author.display_name | Sannasi Ganapathy |
| authorships[1].countries | IN |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I876193797 |
| authorships[1].affiliations[0].raw_affiliation_string | Centre for Cyber-Physical Systems & School of Computer Science and Engineering, Vellore Institute of Technology, Chennai |
| authorships[1].institutions[0].id | https://openalex.org/I876193797 |
| authorships[1].institutions[0].ror | https://ror.org/00qzypv28 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I876193797 |
| authorships[1].institutions[0].country_code | IN |
| authorships[1].institutions[0].display_name | Vellore Institute of Technology University |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Sannasi Ganapathy |
| authorships[1].is_corresponding | True |
| authorships[1].raw_affiliation_strings | Centre for Cyber-Physical Systems & School of Computer Science and Engineering, Vellore Institute of Technology, Chennai |
| authorships[2].author.id | https://openalex.org/A5019208159 |
| authorships[2].author.orcid | |
| authorships[2].author.display_name | N. Mohith |
| authorships[2].countries | IN |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I876193797 |
| authorships[2].affiliations[0].raw_affiliation_string | School of Computer Science and Engineering, Vellore Institute of Technology, Chennai |
| authorships[2].institutions[0].id | https://openalex.org/I876193797 |
| authorships[2].institutions[0].ror | https://ror.org/00qzypv28 |
| authorships[2].institutions[0].type | education |
| authorships[2].institutions[0].lineage | https://openalex.org/I876193797 |
| authorships[2].institutions[0].country_code | IN |
| authorships[2].institutions[0].display_name | Vellore Institute of Technology University |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | N. Mohith |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | School of Computer Science and Engineering, Vellore Institute of Technology, Chennai |
| authorships[3].author.id | https://openalex.org/A5017525339 |
| authorships[3].author.orcid | https://orcid.org/0000-0002-3564-395X |
| authorships[3].author.display_name | A. Kannan |
| authorships[3].countries | IN |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I876193797 |
| authorships[3].affiliations[0].raw_affiliation_string | School of Computer Science and Engineering, Vellore Institute of Technology, Vellore |
| authorships[3].institutions[0].id | https://openalex.org/I876193797 |
| authorships[3].institutions[0].ror | https://ror.org/00qzypv28 |
| authorships[3].institutions[0].type | education |
| authorships[3].institutions[0].lineage | https://openalex.org/I876193797 |
| authorships[3].institutions[0].country_code | IN |
| authorships[3].institutions[0].display_name | Vellore Institute of Technology University |
| authorships[3].author_position | last |
| authorships[3].raw_author_name | A. Kannan |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | School of Computer Science and Engineering, Vellore Institute of Technology, Vellore |
| has_content.pdf | False |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://doi.org/10.1016/j.jksuci.2023.101803 |
| open_access.oa_status | hybrid |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | An optimal energy utilization model for precision agriculture in WSNs using multi-objective clustering and deep learning |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10616 |
| primary_topic.field.id | https://openalex.org/fields/11 |
| primary_topic.field.display_name | Agricultural and Biological Sciences |
| primary_topic.score | 0.9857000112533569 |
| primary_topic.domain.id | https://openalex.org/domains/1 |
| primary_topic.domain.display_name | Life Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/1110 |
| primary_topic.subfield.display_name | Plant Science |
| primary_topic.display_name | Smart Agriculture and AI |
| related_works | https://openalex.org/W2136583354, https://openalex.org/W2111238207, https://openalex.org/W2381688409, https://openalex.org/W2760721665, https://openalex.org/W1975451135, https://openalex.org/W2107954672, https://openalex.org/W3148968234, https://openalex.org/W2097971044, https://openalex.org/W2890570089, https://openalex.org/W330130819 |
| cited_by_count | 38 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 27 |
| counts_by_year[1].year | 2024 |
| counts_by_year[1].cited_by_count | 11 |
| locations_count | 2 |
| best_oa_location.id | doi:10.1016/j.jksuci.2023.101803 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S2764955546 |
| best_oa_location.source.issn | 1319-1578, 2213-1248 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | False |
| best_oa_location.source.issn_l | 1319-1578 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | True |
| best_oa_location.source.display_name | Journal of King Saud University - Computer and Information Sciences |
| best_oa_location.source.host_organization | https://openalex.org/P4310320990 |
| best_oa_location.source.host_organization_name | Elsevier BV |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310320990 |
| best_oa_location.source.host_organization_lineage_names | Elsevier BV |
| best_oa_location.license | cc-by-nc-nd |
| best_oa_location.pdf_url | |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by-nc-nd |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | Journal of King Saud University - Computer and Information Sciences |
| best_oa_location.landing_page_url | https://doi.org/10.1016/j.jksuci.2023.101803 |
| primary_location.id | doi:10.1016/j.jksuci.2023.101803 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S2764955546 |
| primary_location.source.issn | 1319-1578, 2213-1248 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | False |
| primary_location.source.issn_l | 1319-1578 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | True |
| primary_location.source.display_name | Journal of King Saud University - Computer and Information Sciences |
| primary_location.source.host_organization | https://openalex.org/P4310320990 |
| primary_location.source.host_organization_name | Elsevier BV |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310320990 |
| primary_location.source.host_organization_lineage_names | Elsevier BV |
| primary_location.license | cc-by-nc-nd |
| primary_location.pdf_url | |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by-nc-nd |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | Journal of King Saud University - Computer and Information Sciences |
| primary_location.landing_page_url | https://doi.org/10.1016/j.jksuci.2023.101803 |
| publication_date | 2023-10-18 |
| publication_year | 2023 |
| referenced_works | https://openalex.org/W6901700945, https://openalex.org/W3156892891, https://openalex.org/W2951128604, https://openalex.org/W2899776773, https://openalex.org/W6795828236, https://openalex.org/W4283123110, https://openalex.org/W6949721422, https://openalex.org/W2802808115, https://openalex.org/W6761189470, https://openalex.org/W1460294274, https://openalex.org/W3134059133, https://openalex.org/W2794548315, https://openalex.org/W6785154775, https://openalex.org/W6751608033, https://openalex.org/W4206363175, https://openalex.org/W2897510474, https://openalex.org/W3120936939, https://openalex.org/W2893164490, https://openalex.org/W2589333926, https://openalex.org/W4291474825, https://openalex.org/W3138726304, https://openalex.org/W2917334714, https://openalex.org/W6749240716, https://openalex.org/W3000638380, https://openalex.org/W2895281821, https://openalex.org/W3003262233, https://openalex.org/W1560339406, https://openalex.org/W6757371817, https://openalex.org/W3003266005, https://openalex.org/W6760628173, https://openalex.org/W2540599045, https://openalex.org/W4283377946, https://openalex.org/W2908370604, https://openalex.org/W6840732693, https://openalex.org/W2912292549, https://openalex.org/W6776272561, https://openalex.org/W2987761081, https://openalex.org/W6838583535, https://openalex.org/W3169999658, https://openalex.org/W2973344609, https://openalex.org/W2792001075, https://openalex.org/W2920003185, https://openalex.org/W2932453485, https://openalex.org/W2905391650, https://openalex.org/W2801531781, https://openalex.org/W3020164405, https://openalex.org/W4288367244, https://openalex.org/W4280649213, https://openalex.org/W2981655926, https://openalex.org/W3094297360, https://openalex.org/W3167963175 |
| referenced_works_count | 51 |
| abstract_inverted_index.a | 5, 38, 50, 68, 192 |
| abstract_inverted_index.In | 115 |
| abstract_inverted_index.To | 46 |
| abstract_inverted_index.an | 132 |
| abstract_inverted_index.as | 131, 160, 168, 172, 175, 180, 185 |
| abstract_inverted_index.be | 44 |
| abstract_inverted_index.by | 11, 165 |
| abstract_inverted_index.in | 8, 31, 57, 95, 108, 195 |
| abstract_inverted_index.is | 37, 55, 80, 93, 154 |
| abstract_inverted_index.it | 190 |
| abstract_inverted_index.of | 29, 35, 65, 83 |
| abstract_inverted_index.on | 15 |
| abstract_inverted_index.to | 43, 98, 110, 136 |
| abstract_inverted_index.50% | 184 |
| abstract_inverted_index.99% | 174 |
| abstract_inverted_index.CH. | 114 |
| abstract_inverted_index.CNN | 134 |
| abstract_inverted_index.The | 151 |
| abstract_inverted_index.and | 87, 142, 148, 158, 183, 189 |
| abstract_inverted_index.for | 60 |
| abstract_inverted_index.new | 51 |
| abstract_inverted_index.the | 26, 32, 62, 81, 88, 102, 112, 117, 121, 138, 145 |
| abstract_inverted_index.(AO) | 86 |
| abstract_inverted_index.(CH) | 105 |
| abstract_inverted_index.Head | 104 |
| abstract_inverted_index.WSNs | 36, 109 |
| abstract_inverted_index.also | 143 |
| abstract_inverted_index.best | 113 |
| abstract_inverted_index.data | 14 |
| abstract_inverted_index.etc. | 24 |
| abstract_inverted_index.like | 19 |
| abstract_inverted_index.make | 99 |
| abstract_inverted_index.play | 4 |
| abstract_inverted_index.role | 7 |
| abstract_inverted_index.soil | 22 |
| abstract_inverted_index.sure | 100 |
| abstract_inverted_index.than | 162 |
| abstract_inverted_index.that | 41, 101 |
| abstract_inverted_index.this | 48, 58, 96 |
| abstract_inverted_index.with | 126 |
| abstract_inverted_index.work | 59, 97 |
| abstract_inverted_index.(CNN) | 130 |
| abstract_inverted_index.(EAO) | 78 |
| abstract_inverted_index.WSNs. | 66 |
| abstract_inverted_index.based | 75 |
| abstract_inverted_index.major | 39 |
| abstract_inverted_index.needs | 42 |
| abstract_inverted_index.newly | 122 |
| abstract_inverted_index.nodes | 34, 64 |
| abstract_inverted_index.other | 163 |
| abstract_inverted_index.which | 79 |
| abstract_inverted_index.(EBOA) | 92 |
| abstract_inverted_index.(WSNs) | 3 |
| abstract_inverted_index.76.92% | 171 |
| abstract_inverted_index.98.24% | 179 |
| abstract_inverted_index.99.23% | 167 |
| abstract_inverted_index.Aquila | 76, 84 |
| abstract_inverted_index.Sensor | 1 |
| abstract_inverted_index.better | 161 |
| abstract_inverted_index.called | 73 |
| abstract_inverted_index.energy | 30, 187 |
| abstract_inverted_index.hybrid | 70 |
| abstract_inverted_index.issue, | 49 |
| abstract_inverted_index.method | 119 |
| abstract_inverted_index.neural | 128 |
| abstract_inverted_index.packet | 176 |
| abstract_inverted_index.proved | 159 |
| abstract_inverted_index.ratio, | 178 |
| abstract_inverted_index.sensor | 33, 63 |
| abstract_inverted_index.(O-CNN) | 135 |
| abstract_inverted_index.Cluster | 103 |
| abstract_inverted_index.address | 47 |
| abstract_inverted_index.crucial | 6 |
| abstract_inverted_index.enhance | 144 |
| abstract_inverted_index.improve | 137 |
| abstract_inverted_index.maximum | 186 |
| abstract_inverted_index.network | 129, 181 |
| abstract_inverted_index.process | 107 |
| abstract_inverted_index.testing | 149 |
| abstract_inverted_index.through | 156 |
| abstract_inverted_index.various | 16 |
| abstract_inverted_index.Election | 74 |
| abstract_inverted_index.However, | 25 |
| abstract_inverted_index.Networks | 2 |
| abstract_inverted_index.Wireless | 0 |
| abstract_inverted_index.accuracy | 147 |
| abstract_inverted_index.approach | 54, 153 |
| abstract_inverted_index.delivery | 177 |
| abstract_inverted_index.grouping | 61 |
| abstract_inverted_index.identify | 111 |
| abstract_inverted_index.lifetime | 182 |
| abstract_inverted_index.proposed | 94, 118, 152 |
| abstract_inverted_index.resolves | 191 |
| abstract_inverted_index.training | 146 |
| abstract_inverted_index.Algorithm | 91 |
| abstract_inverted_index.Moreover, | 67 |
| abstract_inverted_index.Optimized | 133 |
| abstract_inverted_index.Optimizer | 77, 85 |
| abstract_inverted_index.Precision | 9 |
| abstract_inverted_index.accuracy, | 170 |
| abstract_inverted_index.accuracy. | 150 |
| abstract_inverted_index.addition, | 116 |
| abstract_inverted_index.challenge | 40 |
| abstract_inverted_index.developed | 123 |
| abstract_inverted_index.efficient | 27 |
| abstract_inverted_index.evaluated | 155 |
| abstract_inverted_index.humidity, | 21 |
| abstract_inverted_index.moisture, | 23 |
| abstract_inverted_index.obtaining | 166 |
| abstract_inverted_index.precision | 141, 196 |
| abstract_inverted_index.providing | 12 |
| abstract_inverted_index.real-time | 13 |
| abstract_inverted_index.selection | 106 |
| abstract_inverted_index.technique | 72, 125 |
| abstract_inverted_index.addressed. | 45 |
| abstract_inverted_index.approaches | 164 |
| abstract_inverted_index.clustering | 53, 139 |
| abstract_inverted_index.difficulty | 194 |
| abstract_inverted_index.introduced | 56 |
| abstract_inverted_index.parameters | 18 |
| abstract_inverted_index.Agriculture | 10 |
| abstract_inverted_index.algorithm's | 140 |
| abstract_inverted_index.combination | 82 |
| abstract_inverted_index.consumption | 188 |
| abstract_inverted_index.experiments | 157 |
| abstract_inverted_index.significant | 193 |
| abstract_inverted_index.throughput, | 173 |
| abstract_inverted_index.utilization | 28 |
| abstract_inverted_index.Optimisation | 90 |
| abstract_inverted_index.agriculture. | 197 |
| abstract_inverted_index.incorporates | 120 |
| abstract_inverted_index.optimisation | 71 |
| abstract_inverted_index.optimization | 124 |
| abstract_inverted_index.temperature, | 20 |
| abstract_inverted_index.convolutional | 127 |
| abstract_inverted_index.environmental | 17 |
| abstract_inverted_index.Election-Based | 89 |
| abstract_inverted_index.classification | 169 |
| abstract_inverted_index.multi-objective | 52, 69 |
| cited_by_percentile_year.max | 100 |
| cited_by_percentile_year.min | 99 |
| corresponding_author_ids | https://openalex.org/A5108977851 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 4 |
| corresponding_institution_ids | https://openalex.org/I876193797 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/2 |
| sustainable_development_goals[0].score | 0.47999998927116394 |
| sustainable_development_goals[0].display_name | Zero hunger |
| citation_normalized_percentile.value | 0.99181408 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |