A processor implemented method for automating information extraction from piping and instrumentation diagrams, the method comprising: detecting, via one or more hardware processors, a plurality of components from one or more piping and instrumentation diagrams by providing the one or more piping and instrumentation diagrams as an input to a pre-trained CTPN Network, wherein the plurality of components comprise at least one of a pipeline, a pipeline code, an inlet and an outlet, a symbol and a text wherein detecting the pipeline code is preceded by filtering, from the one or more piping and instrumentation diagrams, one or more pipeline codes comprising a plurality of false positive pipeline codes, by implementing a Connectionist Text Proposal Network (CTPN) technique, wherein implementing the CTPN technique comprises utilizing the pre-trained CTPN Network on a scene-test dataset for detecting the pipeline codes from the one or more piping and instrumentation diagrams and generating a set of pipeline codes comprising a plurality of false positive pipeline codes, and wherein the step of detecting the symbol comprises learning, by implementing a Fully Convolutional Neural Network technique, a spatial location of one or more objects in the symbol; associating, via an association module, each of the detected plurality of components by implementing a Euclidean Distance technique, wherein the associating comprises mapping each of the detected plurality of components with at least one of an appropriate pipeline; and generating, based upon each of the associated plurality of components, a plurality of tree-shaped data structures by implementing a structuring technique, wherein each of the plurality of tree-shaped data structures capture a process flow of pipeline schematics corresponding to the one or more piping and instrumentation diagrams wherein each tree in the plurality of tree-shaped data structures comprises a root node, a leaf node and an intermediate node for capturing the process flow of pipeline schematics, wherein the detected outlet is treated as the root node, and wherein the detected inlet is treated as the leaf node, and wherein the detected pipeline corresponds to the intermediate node. detecting, via one or more hardware processors, a plurality of components from one or more piping and instrumentation diagrams by providing the one or more piping and instrumentation diagrams as an input to a pre-trained CTPN Network, wherein the plurality of components comprise at least one of a pipeline, a pipeline code, an inlet and an outlet, a symbol and a text wherein detecting the pipeline code is preceded by filtering, from the one or more piping and instrumentation diagrams, one or more pipeline codes comprising a plurality of false positive pipeline codes, by implementing a Connectionist Text Proposal Network (CTPN) technique, wherein implementing the CTPN technique comprises utilizing the pre-trained CTPN Network on a scene-test dataset for detecting the pipeline codes from the one or more piping and instrumentation diagrams and generating a set of pipeline codes comprising a plurality of false positive pipeline codes, and wherein the step of detecting the symbol comprises learning, by implementing a Fully Convolutional Neural Network technique, a spatial location of one or more objects in the symbol; associating, via an association module, each of the detected plurality of components by implementing a Euclidean Distance technique, wherein the associating comprises mapping each of the detected plurality of components with at least one of an appropriate pipeline; and generating, based upon each of the associated plurality of components, a plurality of tree-shaped data structures by implementing a structuring technique, wherein each of the plurality of tree-shaped data structures capture a process flow of pipeline schematics corresponding to the one or more piping and instrumentation diagrams wherein each tree in the plurality of tree-shaped data structures comprises a root node, a leaf node and an intermediate node for capturing the process flow of pipeline schematics, wherein the detected outlet is treated as the root node, and wherein the detected inlet is treated as the leaf node, and wherein the detected pipeline corresponds to the intermediate node.