A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Structural Damage Identification from Video Footage Using Artificial Intelligence
https://orcid.org/http://orcid.org/0000-0003-2884-3969
https://orcid.org/http://orcid.org/0000-0001-6028-1228
https://orcid.org/http://orcid.org/0000-0003-4230-7580
https://orcid.org/http://orcid.org/0000-0002-8480-0595
One of the major advancements in the field of civil engineering from the past few years is intelligent infrastructures. These structures will have the ability of sensing and will be accurately able to respond to the changes in the environment and external damages. To be able to keep up with the advancements we need to detect the damages to monitor the health of the structure. This research study aims to develop an efficient damage detection method using video of the damaged structure taken by mobile or camera mounted on a drone to replace the human visual inspection using Artificial Intelligence. For this system, an AI-based application is developed that will be able to recognize the damages accurately in the bounding box or targeted limiting area via a portable camera. An artificial neural network will be used to train the model and to classify the images obtained from video footage. As a case study and validation, a real damaged bridge video footage is considered.
Structural Damage Identification from Video Footage Using Artificial Intelligence
https://orcid.org/http://orcid.org/0000-0003-2884-3969
https://orcid.org/http://orcid.org/0000-0001-6028-1228
https://orcid.org/http://orcid.org/0000-0003-4230-7580
https://orcid.org/http://orcid.org/0000-0002-8480-0595
One of the major advancements in the field of civil engineering from the past few years is intelligent infrastructures. These structures will have the ability of sensing and will be accurately able to respond to the changes in the environment and external damages. To be able to keep up with the advancements we need to detect the damages to monitor the health of the structure. This research study aims to develop an efficient damage detection method using video of the damaged structure taken by mobile or camera mounted on a drone to replace the human visual inspection using Artificial Intelligence. For this system, an AI-based application is developed that will be able to recognize the damages accurately in the bounding box or targeted limiting area via a portable camera. An artificial neural network will be used to train the model and to classify the images obtained from video footage. As a case study and validation, a real damaged bridge video footage is considered.
Structural Damage Identification from Video Footage Using Artificial Intelligence
https://orcid.org/http://orcid.org/0000-0003-2884-3969
https://orcid.org/http://orcid.org/0000-0001-6028-1228
https://orcid.org/http://orcid.org/0000-0003-4230-7580
https://orcid.org/http://orcid.org/0000-0002-8480-0595
One of the major advancements in the field of civil engineering from the past few years is intelligent infrastructures. These structures will have the ability of sensing and will be accurately able to respond to the changes in the environment and external damages. To be able to keep up with the advancements we need to detect the damages to monitor the health of the structure. This research study aims to develop an efficient damage detection method using video of the damaged structure taken by mobile or camera mounted on a drone to replace the human visual inspection using Artificial Intelligence. For this system, an AI-based application is developed that will be able to recognize the damages accurately in the bounding box or targeted limiting area via a portable camera. An artificial neural network will be used to train the model and to classify the images obtained from video footage. As a case study and validation, a real damaged bridge video footage is considered.
Structural Damage Identification from Video Footage Using Artificial Intelligence
Lecture Notes in Civil Engineering
Rizzo, Piervincenzo (editor) / Milazzo, Alberto (editor) / Beeram, Sree Keerthe (author) / Kadarla, Sushmita (author) / Kalapatapu, Prafulla (author) / Pasupuleti, Venkata Dilip Kumar (author)
European Workshop on Structural Health Monitoring ; 2022 ; Palermo, Italy
2022-06-16
10 pages
Article/Chapter (Book)
Electronic Resource
English
Damage detection , Image processing , Artificial intelligence , Structural cracks , Spalling , Visual inspection , Artificial neural network Engineering , Building Repair and Maintenance , Cyber-physical systems, IoT , Industrial and Production Engineering , Monitoring/Environmental Analysis , Analytical Chemistry
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