Patentometric Analysis of AI Based Structural Health Monitoring
The worldwide construction sector is moving towards digitization due to the development of Industry 4.0. However, when it comes to digitizing building techniques, structural health monitoring, or SHM, it is still one factor that needs to be considered. Artificial Intelligence (AI) is a remarkable in...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Sciendo
2024-12-01
|
| Series: | Civil and Environmental Engineering |
| Subjects: | |
| Online Access: | https://doi.org/10.2478/cee-2024-0060 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832570339701293056 |
|---|---|
| author | Desai Pradnya Sandbhor Sayali Kaushik Amit Kant Patil Ajit Dabir Vaishnavi |
| author_facet | Desai Pradnya Sandbhor Sayali Kaushik Amit Kant Patil Ajit Dabir Vaishnavi |
| author_sort | Desai Pradnya |
| collection | DOAJ |
| description | The worldwide construction sector is moving towards digitization due to the development of Industry 4.0. However, when it comes to digitizing building techniques, structural health monitoring, or SHM, it is still one factor that needs to be considered. Artificial Intelligence (AI) is a remarkable invention in the construction sector. Artificial Intelligence can improve structural health monitoring and provide better solutions. Evaluating previous studies and current developments in AI-based structural health monitoring is essential to achieving this. Through a thorough Patentometric study using the industry-leading databases Espacenet and The Lens, the research seeks to present an analysis of AI in structural health monitoring. For analysis, patent information covering 2019 to 2023 is taken into account. The chosen data is evaluated for patents by nation and year, and the IPC and CPC codes for patents in artificial intelligence for structural health monitoring are also covered. The United States is currently at the forefront of patenting artificial intelligence AI-based structural health monitoring systems. This report presents an in-depth Patentometric analysis that enumerates state-of-the-art innovations. In addition to highlighting the previous art, it offers a route for strategic patenting with higher odds of publication and patent award. |
| format | Article |
| id | doaj-art-1dc2ca236c7f48098429313b77220df8 |
| institution | Kabale University |
| issn | 2199-6512 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Sciendo |
| record_format | Article |
| series | Civil and Environmental Engineering |
| spelling | doaj-art-1dc2ca236c7f48098429313b77220df82025-02-02T15:47:53ZengSciendoCivil and Environmental Engineering2199-65122024-12-0120281282310.2478/cee-2024-0060Patentometric Analysis of AI Based Structural Health MonitoringDesai Pradnya0Sandbhor Sayali1Kaushik Amit Kant2Patil Ajit3Dabir Vaishnavi4Research Scholar, Civil Engineering Department, Symbiosis Institute of Technology, Symbiosis International (Deemed University), Pune, IndiaAssociate Professor and Head, Civil Engineering Department, Symbiosis Institute of Technology, Symbiosis International (Deemed University), Pune, IndiaAssistant Professor, Department of Architecture and Built Environment, Northumbria University Newcastle, United KingdomAssistant Professor and Head Civil Engineering Department, DYPU, Pune, IndiaPrincipal Consultant, Green Cube Consulting LLC, Georgia, USAThe worldwide construction sector is moving towards digitization due to the development of Industry 4.0. However, when it comes to digitizing building techniques, structural health monitoring, or SHM, it is still one factor that needs to be considered. Artificial Intelligence (AI) is a remarkable invention in the construction sector. Artificial Intelligence can improve structural health monitoring and provide better solutions. Evaluating previous studies and current developments in AI-based structural health monitoring is essential to achieving this. Through a thorough Patentometric study using the industry-leading databases Espacenet and The Lens, the research seeks to present an analysis of AI in structural health monitoring. For analysis, patent information covering 2019 to 2023 is taken into account. The chosen data is evaluated for patents by nation and year, and the IPC and CPC codes for patents in artificial intelligence for structural health monitoring are also covered. The United States is currently at the forefront of patenting artificial intelligence AI-based structural health monitoring systems. This report presents an in-depth Patentometric analysis that enumerates state-of-the-art innovations. In addition to highlighting the previous art, it offers a route for strategic patenting with higher odds of publication and patent award.https://doi.org/10.2478/cee-2024-0060artificial intelligencepatentsstructural health monitoringndtnon destructive testing |
| spellingShingle | Desai Pradnya Sandbhor Sayali Kaushik Amit Kant Patil Ajit Dabir Vaishnavi Patentometric Analysis of AI Based Structural Health Monitoring Civil and Environmental Engineering artificial intelligence patents structural health monitoring ndt non destructive testing |
| title | Patentometric Analysis of AI Based Structural Health Monitoring |
| title_full | Patentometric Analysis of AI Based Structural Health Monitoring |
| title_fullStr | Patentometric Analysis of AI Based Structural Health Monitoring |
| title_full_unstemmed | Patentometric Analysis of AI Based Structural Health Monitoring |
| title_short | Patentometric Analysis of AI Based Structural Health Monitoring |
| title_sort | patentometric analysis of ai based structural health monitoring |
| topic | artificial intelligence patents structural health monitoring ndt non destructive testing |
| url | https://doi.org/10.2478/cee-2024-0060 |
| work_keys_str_mv | AT desaipradnya patentometricanalysisofaibasedstructuralhealthmonitoring AT sandbhorsayali patentometricanalysisofaibasedstructuralhealthmonitoring AT kaushikamitkant patentometricanalysisofaibasedstructuralhealthmonitoring AT patilajit patentometricanalysisofaibasedstructuralhealthmonitoring AT dabirvaishnavi patentometricanalysisofaibasedstructuralhealthmonitoring |