Client Overview

Our client is one of the world’s leading embedded technology service providers

Client Overview

Business Challenge and Objectives

  • High dust deposition on insulators/transformers leads to a rise in insulator temperature, causing grid failure.
  • The grid failure in-turn results in revenue losses for the organization.
  • The client currently uses state-of-the-art automation systems to capture the images of insulator/transformers at the substations to monitor the dust deposition on them.
  • The client wanted to fetch and manage video feed data from 0.3 million towers.
  • The client also required an analytics ecosystem to trigger preventive cleaning alerts on-time to avoid grid failure.

The Solution

The TekLink provided a holistic solution considering the complexity of the factors involved in the grid functioning and other business needs.

  • Pre-processing (image scaling, background noise removal, and others) the real-time data and images, and offline data (manual, image feed, video streams).
  • Migration of the pre-processed data to the Data Warehouse.
  • Using predictive models for data training.
  • Building deep learning algorithms like convolution learning (CNN), using TensorFlow to categorize the clean and dirty images of the insulators.
  • Implementing a smart predictive system to provide regular updates and critical warnings for preventive maintenance.

Key Benefits


  • Efficient processing and categorizing the insulator image data feed.
  • Minimizing the consequential losses due to power supply downtime.
  • Improve preventive maintenance with the clearing alerts generated from analytical models.
  • Leverage AI in data processing to reduce error probabilities eliminating human intervention.

To learn more about this offering