Application of Artificial Intelligence Through Python for Recognition by Typing, Voice and Image in the Structural Analysis of the Behavior of Prestressed Concrete Beams of a Multifamily Building

Structural analysis of the behavior of prestressed concrete beams in a building involves evaluating how these beams support loads and behave under different conditions. This includes examining the distribution of forces, deformations, stresses and any other factors that may affect its integrity and safety. Its analysis is essential to ensure the structural stability of the building and make informed decisions about its maintenance, repair or improvement. This study proposes the application of Artificial Intelligence (AI) through the Visual Studio Code (VS Code) code editor with Python programming language for 3 types of recognition, by typing, voice and image. This research focuses on the structural analysis of prestressed concrete beams of a multifamily building located in Lima through the representation of Bending Moment Diagrams (DMF) and Shear Force Diagrams (DFC). According to the results obtained, the same diagrams are observed for each type of recognition, but the image diagram is more optimal because it recognizes and analyzes the element in less time, since it is only necessary to type the name with which it was previously saved, and recognized in the VS Code library, this being approximately 43% faster compared to the traditional manual typing method.