Development of Smart Pillbox Using 3D Printing Technology and Convolutional Neural Network Image Recognition Article Swipe
Kun-Li Tsai
,
Ben-Yi Liau
,
Yu-Ming Hung
,
Gwo-Jeng Yu
,
Yao‐Chin Wang
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.18494/sam.2020.2632
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.18494/sam.2020.2632
CNN) Safety in taking medicine is important in health care.In this study, we propose a complete concept of an active smart pillbox, which comprises a main control unit, a pill dispenser unit, and an application software (app) for the automatic dispensing of medicine.The smart pillbox employs convolutional neural network image recognition and 3D printing technology.We adopt an Arduino-based platform to control the rotation and stopping of the motor to dispense the required quantity of pills as the first step towards a fully automated process.A smartphone can be connected to the smart pillbox by Bluetooth and be used to set the parameters of the system.This pillbox can be used at home and allows users to set the medication time and pill type from their smartphone using an app.Moreover, it can remind users to take their medicine.The device is very promising for use in home care and clinical practice.
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.18494/sam.2020.2632
- https://myukk.org/SM2017/sm_pdf/SM2227.pdf
- OA Status
- gold
- Cited By
- 5
- References
- 1
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3029491159
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W3029491159Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.18494/sam.2020.2632Digital Object Identifier
- Title
-
Development of Smart Pillbox Using 3D Printing Technology and Convolutional Neural Network Image RecognitionWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-05-29Full publication date if available
- Authors
-
Kun-Li Tsai, Ben-Yi Liau, Yu-Ming Hung, Gwo-Jeng Yu, Yao‐Chin WangList of authors in order
- Landing page
-
https://doi.org/10.18494/sam.2020.2632Publisher landing page
- PDF URL
-
https://myukk.org/SM2017/sm_pdf/SM2227.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://myukk.org/SM2017/sm_pdf/SM2227.pdfDirect OA link when available
- Concepts
-
Convolutional neural network, Computer science, Artificial intelligence, Artificial neural network, Image (mathematics), Computer vision, Pattern recognition (psychology)Top concepts (fields/topics) attached by OpenAlex
- Cited by
-
5Total citation count in OpenAlex
- Citations by year (recent)
-
2024: 1, 2022: 4Per-year citation counts (last 5 years)
- References (count)
-
1Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W3029491159 |
|---|---|
| doi | https://doi.org/10.18494/sam.2020.2632 |
| ids.doi | https://doi.org/10.18494/sam.2020.2632 |
| ids.mag | 3029491159 |
| ids.openalex | https://openalex.org/W3029491159 |
| fwci | 0.72855272 |
| type | article |
| title | Development of Smart Pillbox Using 3D Printing Technology and Convolutional Neural Network Image Recognition |
| biblio.issue | 5 |
| biblio.volume | 32 |
| biblio.last_page | 1907 |
| biblio.first_page | 1907 |
| topics[0].id | https://openalex.org/T12111 |
| topics[0].field.id | https://openalex.org/fields/22 |
| topics[0].field.display_name | Engineering |
| topics[0].score | 0.7422999739646912 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2209 |
| topics[0].subfield.display_name | Industrial and Manufacturing Engineering |
| topics[0].display_name | Industrial Vision Systems and Defect Detection |
| topics[1].id | https://openalex.org/T12707 |
| topics[1].field.id | https://openalex.org/fields/22 |
| topics[1].field.display_name | Engineering |
| topics[1].score | 0.6960999965667725 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2214 |
| topics[1].subfield.display_name | Media Technology |
| topics[1].display_name | Vehicle License Plate Recognition |
| topics[2].id | https://openalex.org/T11666 |
| topics[2].field.id | https://openalex.org/fields/31 |
| topics[2].field.display_name | Physics and Astronomy |
| topics[2].score | 0.6639999747276306 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/3107 |
| topics[2].subfield.display_name | Atomic and Molecular Physics, and Optics |
| topics[2].display_name | Color Science and Applications |
| is_xpac | False |
| apc_list.value | 99360 |
| apc_list.currency | JPY |
| apc_list.value_usd | 748 |
| apc_paid.value | 99360 |
| apc_paid.currency | JPY |
| apc_paid.value_usd | 748 |
| concepts[0].id | https://openalex.org/C81363708 |
| concepts[0].level | 2 |
| concepts[0].score | 0.8012967109680176 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q17084460 |
| concepts[0].display_name | Convolutional neural network |
| concepts[1].id | https://openalex.org/C41008148 |
| concepts[1].level | 0 |
| concepts[1].score | 0.5833906531333923 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[1].display_name | Computer science |
| concepts[2].id | https://openalex.org/C154945302 |
| concepts[2].level | 1 |
| concepts[2].score | 0.4819478988647461 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[2].display_name | Artificial intelligence |
| concepts[3].id | https://openalex.org/C50644808 |
| concepts[3].level | 2 |
| concepts[3].score | 0.42219752073287964 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q192776 |
| concepts[3].display_name | Artificial neural network |
| concepts[4].id | https://openalex.org/C115961682 |
| concepts[4].level | 2 |
| concepts[4].score | 0.4193708896636963 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q860623 |
| concepts[4].display_name | Image (mathematics) |
| concepts[5].id | https://openalex.org/C31972630 |
| concepts[5].level | 1 |
| concepts[5].score | 0.4191087484359741 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q844240 |
| concepts[5].display_name | Computer vision |
| concepts[6].id | https://openalex.org/C153180895 |
| concepts[6].level | 2 |
| concepts[6].score | 0.385275274515152 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q7148389 |
| concepts[6].display_name | Pattern recognition (psychology) |
| keywords[0].id | https://openalex.org/keywords/convolutional-neural-network |
| keywords[0].score | 0.8012967109680176 |
| keywords[0].display_name | Convolutional neural network |
| keywords[1].id | https://openalex.org/keywords/computer-science |
| keywords[1].score | 0.5833906531333923 |
| keywords[1].display_name | Computer science |
| keywords[2].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[2].score | 0.4819478988647461 |
| keywords[2].display_name | Artificial intelligence |
| keywords[3].id | https://openalex.org/keywords/artificial-neural-network |
| keywords[3].score | 0.42219752073287964 |
| keywords[3].display_name | Artificial neural network |
| keywords[4].id | https://openalex.org/keywords/image |
| keywords[4].score | 0.4193708896636963 |
| keywords[4].display_name | Image (mathematics) |
| keywords[5].id | https://openalex.org/keywords/computer-vision |
| keywords[5].score | 0.4191087484359741 |
| keywords[5].display_name | Computer vision |
| keywords[6].id | https://openalex.org/keywords/pattern-recognition |
| keywords[6].score | 0.385275274515152 |
| keywords[6].display_name | Pattern recognition (psychology) |
| language | en |
| locations[0].id | doi:10.18494/sam.2020.2632 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S139116023 |
| locations[0].source.issn | 0914-4935, 2435-0869 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 0914-4935 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | True |
| locations[0].source.display_name | Sensors and Materials |
| locations[0].source.host_organization | https://openalex.org/P4360969191 |
| locations[0].source.host_organization_name | MYU K.K. |
| locations[0].source.host_organization_lineage | https://openalex.org/P4360969191 |
| locations[0].source.host_organization_lineage_names | MYU K.K. |
| locations[0].license | cc-by |
| locations[0].pdf_url | https://myukk.org/SM2017/sm_pdf/SM2227.pdf |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | https://openalex.org/licenses/cc-by |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | Sensors and Materials |
| locations[0].landing_page_url | https://doi.org/10.18494/sam.2020.2632 |
| indexed_in | crossref, doaj |
| authorships[0].author.id | https://openalex.org/A5033868700 |
| authorships[0].author.orcid | |
| authorships[0].author.display_name | Kun-Li Tsai |
| authorships[0].countries | TW |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I4210091577 |
| authorships[0].affiliations[0].raw_affiliation_string | Department of Emergency Medicine, Kuang Tien General Hospital, Taichung City 433, Taiwan |
| authorships[0].institutions[0].id | https://openalex.org/I4210091577 |
| authorships[0].institutions[0].ror | https://ror.org/001yjqf23 |
| authorships[0].institutions[0].type | healthcare |
| authorships[0].institutions[0].lineage | https://openalex.org/I4210091577 |
| authorships[0].institutions[0].country_code | TW |
| authorships[0].institutions[0].display_name | Kuang Tien General Hospital |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Kun-Li Tsai |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | Department of Emergency Medicine, Kuang Tien General Hospital, Taichung City 433, Taiwan |
| authorships[1].author.id | https://openalex.org/A5084310586 |
| authorships[1].author.orcid | https://orcid.org/0000-0002-6857-8656 |
| authorships[1].author.display_name | Ben-Yi Liau |
| authorships[1].countries | TW |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I95858998 |
| authorships[1].affiliations[0].raw_affiliation_string | Department of Biomedical Engineering, Hungkuang University, Taichung City 433, Taiwan |
| authorships[1].institutions[0].id | https://openalex.org/I95858998 |
| authorships[1].institutions[0].ror | https://ror.org/02f2vsx71 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I95858998 |
| authorships[1].institutions[0].country_code | TW |
| authorships[1].institutions[0].display_name | Hungkuang University |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Ben-Yi Liau |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Department of Biomedical Engineering, Hungkuang University, Taichung City 433, Taiwan |
| authorships[2].author.id | https://openalex.org/A5071566456 |
| authorships[2].author.orcid | |
| authorships[2].author.display_name | Yu-Ming Hung |
| authorships[2].countries | TW |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I95858998 |
| authorships[2].affiliations[0].raw_affiliation_string | Department of Biomedical Engineering, Hungkuang University, Taichung City 433, Taiwan |
| authorships[2].institutions[0].id | https://openalex.org/I95858998 |
| authorships[2].institutions[0].ror | https://ror.org/02f2vsx71 |
| authorships[2].institutions[0].type | education |
| authorships[2].institutions[0].lineage | https://openalex.org/I95858998 |
| authorships[2].institutions[0].country_code | TW |
| authorships[2].institutions[0].display_name | Hungkuang University |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Yu-Ming Hung |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | Department of Biomedical Engineering, Hungkuang University, Taichung City 433, Taiwan |
| authorships[3].author.id | https://openalex.org/A5025827998 |
| authorships[3].author.orcid | |
| authorships[3].author.display_name | Gwo-Jeng Yu |
| authorships[3].countries | TW |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I91951123 |
| authorships[3].affiliations[0].raw_affiliation_string | Department of Computer Science and Information Engineering, Cheng Shiu University, Kaohsiung City 833, Taiwan |
| authorships[3].institutions[0].id | https://openalex.org/I91951123 |
| authorships[3].institutions[0].ror | https://ror.org/011bdtx65 |
| authorships[3].institutions[0].type | education |
| authorships[3].institutions[0].lineage | https://openalex.org/I91951123 |
| authorships[3].institutions[0].country_code | TW |
| authorships[3].institutions[0].display_name | Cheng Shiu University |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Gwo-Jeng Yu |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | Department of Computer Science and Information Engineering, Cheng Shiu University, Kaohsiung City 833, Taiwan |
| authorships[4].author.id | https://openalex.org/A5012371587 |
| authorships[4].author.orcid | https://orcid.org/0000-0001-7949-7977 |
| authorships[4].author.display_name | Yao‐Chin Wang |
| authorships[4].countries | TW |
| authorships[4].affiliations[0].institution_ids | https://openalex.org/I91951123 |
| authorships[4].affiliations[0].raw_affiliation_string | Department of Computer Science and Information Engineering, Cheng Shiu University, Kaohsiung City 833, Taiwan |
| authorships[4].institutions[0].id | https://openalex.org/I91951123 |
| authorships[4].institutions[0].ror | https://ror.org/011bdtx65 |
| authorships[4].institutions[0].type | education |
| authorships[4].institutions[0].lineage | https://openalex.org/I91951123 |
| authorships[4].institutions[0].country_code | TW |
| authorships[4].institutions[0].display_name | Cheng Shiu University |
| authorships[4].author_position | last |
| authorships[4].raw_author_name | Yao-Chin Wang |
| authorships[4].is_corresponding | False |
| authorships[4].raw_affiliation_strings | Department of Computer Science and Information Engineering, Cheng Shiu University, Kaohsiung City 833, Taiwan |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://myukk.org/SM2017/sm_pdf/SM2227.pdf |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Development of Smart Pillbox Using 3D Printing Technology and Convolutional Neural Network Image Recognition |
| has_fulltext | True |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T12111 |
| primary_topic.field.id | https://openalex.org/fields/22 |
| primary_topic.field.display_name | Engineering |
| primary_topic.score | 0.7422999739646912 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2209 |
| primary_topic.subfield.display_name | Industrial and Manufacturing Engineering |
| primary_topic.display_name | Industrial Vision Systems and Defect Detection |
| related_works | https://openalex.org/W4293226380, https://openalex.org/W4313906399, https://openalex.org/W4321487865, https://openalex.org/W2811106690, https://openalex.org/W4239306820, https://openalex.org/W2947043951, https://openalex.org/W2318112981, https://openalex.org/W4312417841, https://openalex.org/W4225147082, https://openalex.org/W2778653980 |
| cited_by_count | 5 |
| counts_by_year[0].year | 2024 |
| counts_by_year[0].cited_by_count | 1 |
| counts_by_year[1].year | 2022 |
| counts_by_year[1].cited_by_count | 4 |
| locations_count | 1 |
| best_oa_location.id | doi:10.18494/sam.2020.2632 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S139116023 |
| best_oa_location.source.issn | 0914-4935, 2435-0869 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 0914-4935 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | True |
| best_oa_location.source.display_name | Sensors and Materials |
| best_oa_location.source.host_organization | https://openalex.org/P4360969191 |
| best_oa_location.source.host_organization_name | MYU K.K. |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4360969191 |
| best_oa_location.source.host_organization_lineage_names | MYU K.K. |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | https://myukk.org/SM2017/sm_pdf/SM2227.pdf |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | Sensors and Materials |
| best_oa_location.landing_page_url | https://doi.org/10.18494/sam.2020.2632 |
| primary_location.id | doi:10.18494/sam.2020.2632 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S139116023 |
| primary_location.source.issn | 0914-4935, 2435-0869 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 0914-4935 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | True |
| primary_location.source.display_name | Sensors and Materials |
| primary_location.source.host_organization | https://openalex.org/P4360969191 |
| primary_location.source.host_organization_name | MYU K.K. |
| primary_location.source.host_organization_lineage | https://openalex.org/P4360969191 |
| primary_location.source.host_organization_lineage_names | MYU K.K. |
| primary_location.license | cc-by |
| primary_location.pdf_url | https://myukk.org/SM2017/sm_pdf/SM2227.pdf |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | Sensors and Materials |
| primary_location.landing_page_url | https://doi.org/10.18494/sam.2020.2632 |
| publication_date | 2020-05-29 |
| publication_year | 2020 |
| referenced_works | https://openalex.org/W6630334170 |
| referenced_works_count | 1 |
| abstract_inverted_index.a | 14, 24, 28, 80 |
| abstract_inverted_index.3D | 52 |
| abstract_inverted_index.an | 18, 33, 56, 125 |
| abstract_inverted_index.as | 75 |
| abstract_inverted_index.at | 108 |
| abstract_inverted_index.be | 86, 95, 106 |
| abstract_inverted_index.by | 92 |
| abstract_inverted_index.in | 2, 7, 141 |
| abstract_inverted_index.is | 5, 136 |
| abstract_inverted_index.it | 127 |
| abstract_inverted_index.of | 17, 41, 65, 73, 101 |
| abstract_inverted_index.to | 59, 68, 88, 97, 113, 131 |
| abstract_inverted_index.we | 12 |
| abstract_inverted_index.and | 32, 51, 63, 94, 110, 118, 144 |
| abstract_inverted_index.can | 85, 105, 128 |
| abstract_inverted_index.for | 37, 139 |
| abstract_inverted_index.set | 98, 114 |
| abstract_inverted_index.the | 38, 61, 66, 70, 76, 89, 99, 102, 115 |
| abstract_inverted_index.use | 140 |
| abstract_inverted_index.CNN) | 0 |
| abstract_inverted_index.care | 143 |
| abstract_inverted_index.from | 121 |
| abstract_inverted_index.home | 109, 142 |
| abstract_inverted_index.main | 25 |
| abstract_inverted_index.pill | 29, 119 |
| abstract_inverted_index.step | 78 |
| abstract_inverted_index.take | 132 |
| abstract_inverted_index.this | 10 |
| abstract_inverted_index.time | 117 |
| abstract_inverted_index.type | 120 |
| abstract_inverted_index.used | 96, 107 |
| abstract_inverted_index.very | 137 |
| abstract_inverted_index.(app) | 36 |
| abstract_inverted_index.adopt | 55 |
| abstract_inverted_index.first | 77 |
| abstract_inverted_index.fully | 81 |
| abstract_inverted_index.image | 49 |
| abstract_inverted_index.motor | 67 |
| abstract_inverted_index.pills | 74 |
| abstract_inverted_index.smart | 20, 43, 90 |
| abstract_inverted_index.their | 122, 133 |
| abstract_inverted_index.unit, | 27, 31 |
| abstract_inverted_index.users | 112, 130 |
| abstract_inverted_index.using | 124 |
| abstract_inverted_index.which | 22 |
| abstract_inverted_index.Safety | 1 |
| abstract_inverted_index.active | 19 |
| abstract_inverted_index.allows | 111 |
| abstract_inverted_index.device | 135 |
| abstract_inverted_index.health | 8 |
| abstract_inverted_index.neural | 47 |
| abstract_inverted_index.remind | 129 |
| abstract_inverted_index.study, | 11 |
| abstract_inverted_index.taking | 3 |
| abstract_inverted_index.care.In | 9 |
| abstract_inverted_index.concept | 16 |
| abstract_inverted_index.control | 26, 60 |
| abstract_inverted_index.employs | 45 |
| abstract_inverted_index.network | 48 |
| abstract_inverted_index.pillbox | 44, 91, 104 |
| abstract_inverted_index.propose | 13 |
| abstract_inverted_index.towards | 79 |
| abstract_inverted_index.clinical | 145 |
| abstract_inverted_index.complete | 15 |
| abstract_inverted_index.dispense | 69 |
| abstract_inverted_index.medicine | 4 |
| abstract_inverted_index.pillbox, | 21 |
| abstract_inverted_index.platform | 58 |
| abstract_inverted_index.printing | 53 |
| abstract_inverted_index.quantity | 72 |
| abstract_inverted_index.required | 71 |
| abstract_inverted_index.rotation | 62 |
| abstract_inverted_index.software | 35 |
| abstract_inverted_index.stopping | 64 |
| abstract_inverted_index.Bluetooth | 93 |
| abstract_inverted_index.automated | 82 |
| abstract_inverted_index.automatic | 39 |
| abstract_inverted_index.comprises | 23 |
| abstract_inverted_index.connected | 87 |
| abstract_inverted_index.dispenser | 30 |
| abstract_inverted_index.important | 6 |
| abstract_inverted_index.practice. | 146 |
| abstract_inverted_index.process.A | 83 |
| abstract_inverted_index.promising | 138 |
| abstract_inverted_index.dispensing | 40 |
| abstract_inverted_index.medication | 116 |
| abstract_inverted_index.parameters | 100 |
| abstract_inverted_index.smartphone | 84, 123 |
| abstract_inverted_index.application | 34 |
| abstract_inverted_index.recognition | 50 |
| abstract_inverted_index.system.This | 103 |
| abstract_inverted_index.medicine.The | 42, 134 |
| abstract_inverted_index.Arduino-based | 57 |
| abstract_inverted_index.app.Moreover, | 126 |
| abstract_inverted_index.convolutional | 46 |
| abstract_inverted_index.technology.We | 54 |
| cited_by_percentile_year.max | 97 |
| cited_by_percentile_year.min | 90 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 5 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/9 |
| sustainable_development_goals[0].score | 0.47999998927116394 |
| sustainable_development_goals[0].display_name | Industry, innovation and infrastructure |
| citation_normalized_percentile.value | 0.76626068 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |