Transformative Trends: A Progressive Examination of P&ID Advancements

Abstract

This compilation of research studies showcases sig- nificant strides in engineering diagram recognition and digi- tization across diverse domains, addressing intricate diagram categories like Piping and Instrumentation Diagrams (P&IDs), scene text in images, and point symbols on scanned topographic maps. Employing a versatile array of methodologies, encompass- ing deep learning, neural networks, digital image processing, and innovative algorithmic fusion, these studies consistently surmount the challenges posed by complex visual data. These methods consistently attain remarkable levels of accuracy and efficiency, bolstering applications ranging from plant design to information extraction, symbol recognition, text detection, and line extraction. While certain papers meticulously detail their algorithmic under- pinnings and techniques, others present holistic frameworks for the comprehensive digitization of intricate engineering drawings. Collectively, these research endeavors underscore the burgeoning influence of advanced technology in enhancing the efficiency, precision, and automation of multifaceted tasks across diverse industries, from manufacturing to geographic information sys- tems. These insights pave the way for future advancements, opening new horizons in the realms of engineering and document digitization.