Cerebral Approach to Track Malfunction of Assets in a Smart Power Grid Information System

Abstract Failure of assets at downstream level of Smart Power Grid being barely addressed, subsequently hoarding lots of superfluous human hours, depletion of valuable time and resources, inefficient and untimely rectification of problems leading to concerns of inefficient operations and hefty loss to the power grid organization in all its aspects. There is a need to address such failures in advance, through the use of prevailing information technological inclusion, implicating efficient operations benefiting the entire sector. With Knowledge Management Systems evolving at its growing needs to address critical issues and providing feasible solutions to the digitization of information already at high demand, we propose an analytical approach merged with the concepts of big data, to track historical data of assets and resources, to identify the possibilities of failure of assets in smart power grid infrastructure. The proposed system would identify the possible failure based on the past records of an assets performance and failures, not limited to, but also based on the expected life span of the assets. The issues will be archived for further sharing while in apposite needs and its solutions would be appropriately applied throughout the power business and its subsidiary. The data would be efficiently stored and archived in the form of digitized formats such as audio, video, images, comments, documents, feedback and other visually recognizable and multimedia formats. Various technological related electronics and gadget equipment’s such as tablets, mobile phones, laptops and other hand held devices could be easily utilized to support the work force teams towards an agile operation.