Automated Verification of Structural Engineering Assembly using Convolution Neural Network
1Dr. S. Padmashree*, Professor, Department of Electronics and Communication Engineering, GSSS Institute of Engineering and Technology for Women, Mysuru, India.
2Sushma S J, Associate Professor, Department of Electronics and Communication Engineering, GSSS Institute of Engineering and Technology for Women, Mysuru, India.
Manuscript received on June 08, 2020. | Revised Manuscript received on June 25, 2020. | Manuscript published on June 30, 2020. | PP: 1319-1323 | Volume-9 Issue-5, June 2020. | Retrieval Number: C6124029320/2020©BEIESP | DOI: 10.35940/ijeat.C6124.069520
Open Access | Ethics and Policies | Cite | Mendeley
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Artificial Intelligence has mostly penetrated in every field of technology and our lifestyle in numerous ways. The contribution of AI in the field of Civil engineering which mainly focuses on planning, design and construction is enormous. The main objective of this work is to develop a system that will automate the process of detecting errors in the engineering plans or drawings of structures. The work adapts convolution neural network technique with the help of Inception V3 model to automate detecting of multiple errors using Artificial Intelligence. AI technique has proven to be more effective, accurate and less time consuming against the existing manual verification technique.
Keywords: Artificial Intelligence, Structural assembly, Deep Learning, Convolution Neural Network