Software for automated  inspection

Fast and safe data capture with drones, based on digital twins

Overhead Line Inspection

A collaboration with Axpo, eSmart Systems and Phase One.

This is how automated power line survey works

In the 1-minute video, we show you the process of generating well-structured line data quickly and safely.

Digital Line Inspection

Higher security of supply with area-wide transparency in a simple fashion.

Our Customers

Get your online-meeting!

Not convinced yet?

Continue for more information.

How well is the current status of your grid documented?

Line-example: 221 Towers | 8.467 Photos | 465 Annotations

What about the automation of your drone flight?

Mobirise

Flight Routes

We provide elaborated flight routes, based on Digital Twins

Mobirise

Cloud Upload

From drone to cloud with a single click. Our process intergrates automated naming of the captured photos (line, tower, arm, perspective)


We provide solutions to enable a fundamental shift from corrective to predictive maintenance

Today's Challenges For Grid Operators

Major parts of the power grid were built in the middle of the last century. Planned outage time frames for maintenance of power lines are increasingly getting shorter. Due to the rising energy demand, the lines are operated closer to their capacity limit. It is becoming more challenging for grid operators to provide maximal availability.  

The Solution

Our drone-app LINIAair supports grid operators to acquire data of their infrastructure by executing elaborated flight patterns. The integrated process transfers the data to a cloud platform, where it is visualized. Analysis is also performed on the platform. The information is used to make sure, the most urgent damages and threats are being detected in order to plan appropriate maintenance measures. 

Our Process

Acquisition

Autonomous acquisition of standardized data sets by our drone app LINIAair

Visualisation

Data visualisation on a cloud based platform

Analysis

Detection of damages and threats, either by manual Analysis, or in the future supported by AI-algorithms

Relevant Features

  • No manual drone operations because of autonomous data acquisition
  • Intergrated data processing - from drone to cloud
  • Intuitive user interface with a georeferenced cloud based platform

Your Benefits

  • Safe time and money of time consuming and unstructured manual drone flights
  • Complete, standardized set of data per mast and span 
  • Fast and solid basis for decision-making enabling predictive maintenance

Products

LINIAair

Automated

Manual drone operations are exhausting and repetitive. Our elaborated flight routes enable thourough data acquisition of all relevant power line parts.

Fast

The standardized flight patterns are executed up to 10 faster, than with manual operation.

Connected

Manual data handling belongs to the past. Our app uploads all data to the cloud platform.

Mobirise

Services

Line Inspection

Mobirise

Data acquisition

When was the last time, you have seen your lines from above? We acquire high quality data at competitive prices.

Mobirise

Data analysis

We analyse the data for you, to have an accurate update of the state of your lines.

Mobirise

Acceptance

Did a contractors perform a job at your lines and you want to examine, if it was executed according to your specifications?

We like to provide you with a documentation.

Connect

How to connect

Drop a line and we get back to you very quickly

About

Our Mission

Sustainably maintained power grids are an essential part of mastering the energy transition as a societal challenge.

With our software, we contribute to the success of an economically and ecologically sustainable energy supply.

Founders

We combine the knowhow of power line engineering and maintenance with software engineering and cloud computing.

Lorenzo
Arizzoli-Bulato

CEO

Bernhard
Lüthi

CTO

Partners und Promotions

Mobirise
Mobirise
Mobirise
Mobirise
Address

Axpo Grid AG
Parkstrasse 23
5401 Baden
Switzerland

Contact

E-Mail: info@linia.ch

Mobirise.com