AI-Blueprint: A Real-Time System for Automated Identification and Analysis of Electrical Blueprints

In recent years, technologies such as Artificial Intelligence have been of great help in driving smart production in industry. However, some links with high complexity and flexibility still rely on manual labor. This paper focuses on the design process of electrical equipment. Based on the realistic needs of enterprises, we design a real-time system for automated recognition and analysis of blueprints of electrical equipment, AI-Blueprint. It automatically extracts multi-modal information from the user’s blueprints, comprehends it, and quickly matches it with the best-standardized schemes in the enterprise database. On average, each blueprint is processed in as little as ${1 . 2 3}$ seconds, which significantly reduces labor costs. We carefully designed several specific modules to build our system, including the Document Element Detector, Diagram Extractor, Table Extractor, and Feature Extractor. To achieve good performance and fast response of AI-Blueprint, we proposed some innovative algorithms and tested their impact on the system performance under different parameters. Numerous experiments have shown that AI-Blueprint can accurately understand information such as circuit diagrams and tables in electrical equipment blueprints, and recognize and classify them precisely and quickly.