Using Drone Data Collections To Identify Medium Voltage (MV) Railway Assets (PKP Energetyka)

Using Drone Data Collections To Identify Medium Voltage (MV) Railway Assets (PKP Energetyka)

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Case studies

Using Drone Data Collections To Identify Medium Voltage (MV) Railway Assets (PKP Energetyka)

Client

Industry

Energy & Utilities
Survey & Inspection
Transportation

Region

Europe

Technology

Phoenix Unmanned Aerial Vehicle (UAV)
Griffin multi-Rotor Unmanned Aerial Vehicle (UAV)
ESRI ArcGIS

Client:  PKP Energetyka
Location: Podłęże-Bochnia, Poland

GISonLine completed a research and development project in support of PKP Energetyka’s Medium Voltage (MV) utility networks by conducting an asset inventory using drone data captures for the newly renovated section (20 km) of the Podłęże-Bochnia railway line. 

Successful results of the research and data capture efforts supported PKP Energetyka interests in the topic of using drones for the inventory and inspection processes associated with utilities enterprise asset management.

The Impact 

Based on the drone identification and inventory of electrical utility assets, the newly renovated section of railway line was captured using two different types of UAV’s: the Phoenix UAV and the Griffin multi-Rotor platforms.

Both drone systems were equipped with high-resolution cameras producing high quality images and videos to support the production of orthophoto maps with a resolution of 1 cm / pixel, a numerical model of land cover, and point cloud data for the visualization of the area in a 3D environment.  

The Outcome

GISonLine successfully conducted the aerial data capture covering the 20 kilometers area of railway electrical networks and provided to PKP Energetyka core deliverables:

  • High-resolution orthophoto maps
  • Point Cloud Data
  • 3D Models
  • High-resolution images & video of utility network assets
  • Geodatabase of utility  objects
  • Comprehensive report on the use of drones for inspecting utility networks

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Using Ground Penetrating Radar to Map & Visualize Underground Utility Networks (Bad Bevensen, Germany)

Using Ground Penetrating Radar to Map & Visualize Underground Utility Networks (Bad Bevensen, Germany)

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Case studies

Using Ground Penetrating Radar to Map & Visualize Underground Utility Networks (Bad Bevensen, Germany)

Client

Industry

Energy & Utilities
Survey & Inspection
Transportation

Region

Europe

Technology

Ground Penetrating Radar (GPR)
AutoCAD

Client: Exact
Location: Bad Bevensen, Germany

In support of its survey and inspection partnership, GISonline conducted an underground detection survey to create multi-disciplinary digital maps of the underground utilities network covering an area of ​​approximately 1 Kilometer in the Bad Bevensen region of Germany. The project included integrating data from a comprehensive soil surveys associated with sections of the project area for the visualization of buried utilities and soil types.

The Impact

The project had a significant impact on determining the course and the depth of the existing underground utility network using detection methods such as Ground Penetrating Radar (GPR).

The Outcome

GISonLine successfully conducted the underground detection survey of the project site and utility lines and produced key sets of deliverables:

  •  GRP survey detection of underground obstacles and objects
  • Preparation and delivery of underground utility maps
  • Integration of existing documentation related to the project site
  • Delivery of all CAD mapping data and files

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Using Artificial Intelligence to Automate Utilities Asset Inspection & Inventory

Using Artificial Intelligence to Automate Utilities Asset Inspection & Inventory

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Case studies

Using Artificial Intelligence to Automate Utilities Asset Inspection & Inventory

Client

Industry

Energy & Utilities
Survey & Inspection
Consumer Applications

Region

Worldwide

Technology

Artificial Intelligence

Overview

GISonLine, in partnership with the Wrocław University of Technology, are working closely on a project designed to use Artificial Intelligence (AI) and machine learning to process and analyze high resolution imagery to automate utility inspection and asset management workflows.

Integrating AI into the inspection & asset management processes has the potential for significant costs savings and benefits. By using AI and machine learning techniques, utility asset managers and inspectors have the ability to automate the process of identifying and inventorying utility objects and to use the AI algorithms to flag assets recognized as having visible defects or faults.

The Impact

GISonLine is specifically focusing on creating AI algorithms and image pattern recognition for the processing of digital images of railway traction lines obtained from drone and UAV platforms. Traction lines and their connected utility objects are used in support of overhead contact lines associated with electrical power distribution for railway networks.

The formalized process will utilize machine learning techniques to detect and identify the railway traction lines and connected network objects. A primary goal is to train the system for pattern recognition to detect and flag visible defects (faults) found along the traction lines and to automatically alert personnel and inspectors of the issues and maintenance needed.

The Outcome

GISonLine’s objective is to integrate the AI and machine learning technology into its INSPECTonLine cloud-based application.

The INSPECTonLine product will enable asset managers and inspectors with the ability to automate the processes associated with utility asset inventories & inspections and provide a formalized method for detecting and alerting personnel of utility defects that require closer inspection.

Phases of the project include:

1. Analysis of source data and materials (drone & aerial platform data)
2. Definition & characteristics of utility objects to be analyzed
3. Development of traction line recognition algorithms
4. Pattern recognition and feature/fault identification
5. Analysis of the solution for maintaining railway overhead contact lines
6. Integration of the algorithms into the INSPECTonline application

 

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Supporting the Expansion of Amazon’s Fulfillment Centers with Aerial & Underground Detection Mapping

Supporting the Expansion of Amazon’s Fulfillment Centers with Aerial & Underground Detection Mapping

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Case studies

Supporting the Expansion of Amazon’s Fulfillment Centers with Aerial & Underground Detection Mapping

Client

Industry

Energy & Utilities
Survey & Inspection

Region

Europe

Technology

GPR – Lecia DS2000
Detector – Leica Ultra Advanced
GNSS solution – Leica CS20/GS16
Drone DJI – Phantom 4 Pro V2.0
CAD, GPR and Pix4D software

Client: Amazon
Location: Krosno Odrzańskie, Poland

An Amazon fulfillment center is a logistics warehouse where incoming orders are received, stored, packed, and shipped out to customers. Planning for the expansion and construction of a fulfillment center requires comprehensive preparation and understanding of site conditions, underground assets, and environmental factors. Understanding exactly what lies beneath the ground prior to any construction and excavation is a key component to planning and safety.

GISonLine was pleased to participate in the project for underground detection and mapping surveys in support of future investments by Amazon. The surveys were carried out to update cartographic maps , perform geodetic measurements of the topography, and detection and mapping of underground utility lines.

The Impact

To provide a thorough understanding of the area, which encompassed 5 hectares (approximately 12 acres), GISonLine collected aerial photogrammetry pictures using drone platforms with a 4K high-resolution camera. Orthophoto maps of the entire area were established producing a 1.5cm terrain model representing land surface elevations to visualize relief. An underground detection survey was carried out using Ground Penetrating Radar (GPR) to establish a set of 2D maps identifying the underground utilities within the targeted areas of interests.

The Outcome

GISonLine successfully completed the underground detection surveys and site mapping delivering to Amazon a comprehensive and up-to-date model of the type and location of sub-surface utilities (ex: electrical, water, gas) and detailed mapping and imagery of site assets to support Amazon’s planning and expansion of fulfillment centers. The project deliverables included:

  • High Resolution Aerial Imagery
  • Orthophoto Maps
  • Digital Terrain Model
  • 2D maps outlining the type and location of underground utilities

 

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3D Modeling of Underground Utilities Near Norwegian Opera House (Oslo, Norway)

3D Modeling of Underground Utilities Near Norwegian Opera House (Oslo, Norway)

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Case studies

3D Modeling of Underground Utilities Near Norwegian Opera House (Oslo, Norway)

Client

Industry

Energy & Utilities
Survey & Inspection

Region

Europe

Technology

GPR – Lecia DS2000
Detector – Leica Ultra Advanced
GNSS solution – Leica CS20/GS16
CAD and GPR software

Client: Exact
Location: Oslo, Norway

GISonLine carried out underground detection surveys near the Norwegian opera house in the center of Oslo. The purpose of the survey was to identify and map the underground utilities and assets in support of construction associated with a new apartment estate.

The Impact

Ground Penetrating Radar (GPR) technology was used for the sub-surface detection and identification of underground utilities. GISonLine performed post-processing of the GPR data to establish detailed 3D models of utility objects that were detected below the surface.

The Outcome

GISonLine successfully completed the underground detection surveys and provided key deliverables in the form of 2D maps, CAD drawings, and 3D models that supported the visualization on the type and location of underground utilities. The survey results and deliverables directly supported the planning, safety, and construction of the newly designed apartment estate.

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