Classification of Actual Sensor Network Deployments in Research Studies from 2013 to 2017
Technologies, such as Wireless Sensor Networks (WSN) and Internet of Things (IoT), have captured the imagination of researchers, businesses, and general public, due to breakthroughs in embedded system development, sensing technologies, and ubiquitous connectivity in recent years. That resulted in th...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-09-01
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| Series: | Data |
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| Online Access: | https://www.mdpi.com/2306-5729/5/4/93 |
| _version_ | 1797552165994102784 |
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| author | Janis Judvaitis Artis Mednis Valters Abolins Ansis Skadins Didzis Lapsa Raimonds Rava Maksims Ivanovs Krisjanis Nesenbergs |
| author_facet | Janis Judvaitis Artis Mednis Valters Abolins Ansis Skadins Didzis Lapsa Raimonds Rava Maksims Ivanovs Krisjanis Nesenbergs |
| author_sort | Janis Judvaitis |
| collection | DOAJ |
| description | Technologies, such as Wireless Sensor Networks (WSN) and Internet of Things (IoT), have captured the imagination of researchers, businesses, and general public, due to breakthroughs in embedded system development, sensing technologies, and ubiquitous connectivity in recent years. That resulted in the emergence of an enormous, difficult-to-navigate body of work related to WSN and IoT. In an ongoing research effort to highlight trends and developments in these technologies and to see whether they are actually deployed rather than subjects of theoretical research with presumed potential use cases, we gathered and codified a dataset of scientific publications from a five-year period from 2013 to 2017 involving actual sensor network deployments, which will serve as a basis for future in-depth analysis of the field. In the first iteration, 15,010 potentially relevant articles were identified in SCOPUS and Web of Science databases; after two iterations, 3059 actual sensor network deployments were extracted from those articles and classified in a consistent way according to different categories, such as type of nodes, field of application, communication types, etc. We publish the resulting dataset with the intent that its further analysis may identify prospective research fields and future trends in WSN and IoT. |
| first_indexed | 2024-03-10T15:57:02Z |
| format | Article |
| id | doaj.art-a0bf42ef16f045a4a16534325d0aef17 |
| institution | Directory Open Access Journal |
| issn | 2306-5729 |
| language | English |
| last_indexed | 2024-03-10T15:57:02Z |
| publishDate | 2020-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Data |
| spelling | doaj.art-a0bf42ef16f045a4a16534325d0aef172023-11-20T15:37:08ZengMDPI AGData2306-57292020-09-01549310.3390/data5040093Classification of Actual Sensor Network Deployments in Research Studies from 2013 to 2017Janis Judvaitis0Artis Mednis1Valters Abolins2Ansis Skadins3Didzis Lapsa4Raimonds Rava5Maksims Ivanovs6Krisjanis Nesenbergs7Institute of Electronics and Computer Science, 14 Dzerbenes St., LV-1006 Riga, LatviaInstitute of Electronics and Computer Science, 14 Dzerbenes St., LV-1006 Riga, LatviaInstitute of Electronics and Computer Science, 14 Dzerbenes St., LV-1006 Riga, LatviaInstitute of Electronics and Computer Science, 14 Dzerbenes St., LV-1006 Riga, LatviaInstitute of Electronics and Computer Science, 14 Dzerbenes St., LV-1006 Riga, LatviaInstitute of Electronics and Computer Science, 14 Dzerbenes St., LV-1006 Riga, LatviaInstitute of Electronics and Computer Science, 14 Dzerbenes St., LV-1006 Riga, LatviaInstitute of Electronics and Computer Science, 14 Dzerbenes St., LV-1006 Riga, LatviaTechnologies, such as Wireless Sensor Networks (WSN) and Internet of Things (IoT), have captured the imagination of researchers, businesses, and general public, due to breakthroughs in embedded system development, sensing technologies, and ubiquitous connectivity in recent years. That resulted in the emergence of an enormous, difficult-to-navigate body of work related to WSN and IoT. In an ongoing research effort to highlight trends and developments in these technologies and to see whether they are actually deployed rather than subjects of theoretical research with presumed potential use cases, we gathered and codified a dataset of scientific publications from a five-year period from 2013 to 2017 involving actual sensor network deployments, which will serve as a basis for future in-depth analysis of the field. In the first iteration, 15,010 potentially relevant articles were identified in SCOPUS and Web of Science databases; after two iterations, 3059 actual sensor network deployments were extracted from those articles and classified in a consistent way according to different categories, such as type of nodes, field of application, communication types, etc. We publish the resulting dataset with the intent that its further analysis may identify prospective research fields and future trends in WSN and IoT.https://www.mdpi.com/2306-5729/5/4/93WSNIoTdeploymentreview |
| spellingShingle | Janis Judvaitis Artis Mednis Valters Abolins Ansis Skadins Didzis Lapsa Raimonds Rava Maksims Ivanovs Krisjanis Nesenbergs Classification of Actual Sensor Network Deployments in Research Studies from 2013 to 2017 Data WSN IoT deployment review |
| title | Classification of Actual Sensor Network Deployments in Research Studies from 2013 to 2017 |
| title_full | Classification of Actual Sensor Network Deployments in Research Studies from 2013 to 2017 |
| title_fullStr | Classification of Actual Sensor Network Deployments in Research Studies from 2013 to 2017 |
| title_full_unstemmed | Classification of Actual Sensor Network Deployments in Research Studies from 2013 to 2017 |
| title_short | Classification of Actual Sensor Network Deployments in Research Studies from 2013 to 2017 |
| title_sort | classification of actual sensor network deployments in research studies from 2013 to 2017 |
| topic | WSN IoT deployment review |
| url | https://www.mdpi.com/2306-5729/5/4/93 |
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