Abstract: Conventionally, root cause analysis and process documentation in process industries has been manually performed resulting in time consuming effort, cost, and human resources. Moreover, in the event of failure, looking at such document and searching for possible root causes is practically impossible in the interest of time and cost associated. Systems and methods of the present disclosure systematically curate knowledge of industrial process(es) from various sources and generate process ontology via meta model(s). Root cause graph (RCG) is created wherein the RCG corresponds to process and root cause and failure modes in the process. The RCG is then transformed to machine instructions which are executed for root cause analysis in real time. The created graphs/knowledge also help in identifying conflicting knowledge or redundant knowledge. Present disclosure enables root cause analysis as soon as a failure occurs or as the systems show or indicate a tendency towards failure.

Abstract: This disclosure generally relates to method and system for asset inspection using unmanned aerial vehicles. Regular inspection of assets in any environment is time consuming and involves physical risk and injury to the property. The method includes receiving a plurality of input images of an asset using unmanned aerial vehicle and generates a 3D point cloud based on overlapped images identified from the plurality of input images of the asset being inspected. Further, anomalies are detected and defects are observed in the one or more objects of interests based on the change observed in each 2D image frame from the plurality 2D image frames in a specific view with an identical objects of interest of the 2D image frame. A pyramidal view map is created for the plurality 2D image frames by mapping each pixel of the plurality 2D image frames with the plurality of input images.

Abstract: This disclosure generally relates to method and system for asset inspection using unmanned aerial vehicles. Regular inspection of assets in any environment is time consuming and involves physical risk and injury to the property. The method includes receiving a plurality of input images of an asset using unmanned aerial vehicle and generates a 3D point cloud based on overlapped images identified from the plurality of input images of the asset being inspected. Further, anomalies are detected and defects are observed in the one or more objects of interests based on the change observed in each 2D image frame from the plurality 2D image frames in a specific view with an identical objects of interest of the 2D image frame. A pyramidal view map is created for the plurality 2D image frames by mapping each pixel of the plurality 2D image frames with the plurality of input images.

Abstract: Systems and methods for auto-generating a control and monitoring solution for smart and robotics environments. The traditional systems and methods provide solutions for the smart and robotics environments by manually generating codes but none of them provide for auto-generation of the control and monitoring solutions and the corresponding coordination logics. Embodiments of the present disclosure provide for auto-generating the control and monitoring solution by capturing a set of domain knowledge and information on capabilities of a plurality of devices by an accumulator module (201), auto-generating a controlled coordination logic based upon the set of domain knowledge and the capabilities information by a control logic synthesizer module (202) and auto-generating, by an implementation module (203), the control and monitoring solution for the smart and robotics environments based upon the coordination control logic.

Abstract: Systems and methods for auto-generating a control and monitoring solution for smart and robotics environments. The traditional systems and methods provide solutions for the smart and robotics environments by manually generating codes but none them provide for auto-generation of the control and monitoring solutions and the corresponding coordination logics. Embodiments of the present disclosure provide for auto-generating the control and monitoring solution by capturing a set of domain knowledge and information on capabilities of a plurality of devices by an accumulator module (201), auto-generating a controlled coordination logic based upon the set of domain knowledge and the capabilities information by a control logic synthesizer module (202) and auto-generating, by an implementation module (203), the control and monitoring solution for the smart and robotics environments based upon the coordination control logic.