The advent of smart grid in the power infrastructure of the nations has provisioned a proactive and highly efficient power management at the generation end and user end as well. The smart meters being a fundamental part of the grid system are responsible for the intermittent sharing of usage data that further assists the utility for decision making. However, the inclusion of digital technology accompanies some major challenges like data security, data loss and communication issues etc. Smart meters are lightweight devices hence susceptible to errors frequently and therefore can cause loss of data. If the unavailability of usage data is significantly high, this can be problematic for the utility in context with further power generation and distribution decisions. This article presents a comprehensive discussion of the fault-tolerant aggregation models for the smart grid environment. A thorough investigation of the most recent research on handling of unavailable data is provided. Finally, the paper identifies the major challenges and future research possibilities for an efficiently fault-tolerant aggregation in the smart grid environment.

A novel scheme is proposed to process the real-time images according to requirements, captured in a computer web camera. By making use of open source computer vision library (OpenCV) and applying its in-built functions, we can easily detect human faces and then match them against the training sets (face images stored in the database) to recognize a human’s identity. Image handling and processing are done using basic library methods. These library functions are able to capture images from a webcam, create windows to hold the images at run time, save them in the database and process them to check exact likeness. CascadeClassifier is used for face detection, and HaarCascade is used for this purpose. FaceRecognizer class is used for face recognition. EigenFaces, FisherFaces and Local Binary Patterns are the basic methods that can be used for this. Images are stored in form of a CSV database.