TY - JOUR
T1 - Patentometric Analysis of AI Based Structural Health Monitoring
AU - Desai, Pradnya
AU - Sandbhor, Sayali
AU - Kaushik, Amit Kant
AU - Patil, Ajit
AU - Dabir, Vaishnavi
PY - 2024/12/17
Y1 - 2024/12/17
N2 - 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.
AB - 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.
KW - Structural Health Monitoring
KW - Patents
KW - Artificial Intelligence
KW - NDT
KW - Non Destructive Testing
UR - http://www.scopus.com/inward/record.url?scp=85213345303&partnerID=8YFLogxK
U2 - 10.2478/cee-2024-0060
DO - 10.2478/cee-2024-0060
M3 - Article
SN - 1336-5835
VL - 20
SP - 812
EP - 823
JO - Civil and Environmental Engineering
JF - Civil and Environmental Engineering
IS - 2
ER -
