Automating Utilities Feature Recognition Using Artificial Intelligence


GISonLine, in partnership with the Wrocław University of Technology, are working towards developing AI algorithms and methodologies used for processing, analyzing, and identifying electrical utility traction lines from imagery collected using UAV and aircraft platforms. 

The Impact

The AI based image recognition techniques can perform object detection and object recognition that significantly automates the process of using high resolutions imagery to perform utility asset inventory and issue (faults) management.

The Outcome

The initial benefits of the project are related to the optimization and automation of business processes used for feature identification of electrical traction lines derived from image sources. In addition, the AI image algorithms will be integrated into the GISonLine product (INSPECTonLine) to provide network inventory & asset management capabilities associated with inspecting and managing utility networks.

Phases of the project include:

  1. Analysis of source data and materials (drone & aerial platform data)
  2. Definition & characteristics of objects to be analyzed
  3. Development of  traction line recognition algorithms
  4. Improving & learning from the algorithms and feature identification
  5. Analysis of the solution to apply towards maintaining overhead contact lines
  6. Implementation of the algorithms into INSPECTonLine





Energy & Utilities
Survey & Inspection
Consumer Applications



Technology stack

Artificial Intelligence

GRIDonLine is a comprehensive GIS Utilities Asset Management (AM) system designed to scale from small to large enterprise utility networks.

INSPECTonLine is a cloud-based geospatial platform designed to manage your inspection and drone (UAV) operations and streamline your quality assurance processes.

ARonLine is an Augmented Reality mobile application that transforms your CAD and GIS utilities data into amazing Augmented Reality (AR) visualizations.

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