• Contact Us close
  • Home
  • Welcome to Alteia keyboard_arrow_right
    Key Concepts keyboard_arrow_right
    What is Alteia What is Ground Sampling Distance GSD How is Accuracy defined in mapping drone Dataset Definition
    Getting Started keyboard_arrow_right
    Quick Guide to the Alteia Interface Ground Control Points GCP Best Practices Coordinate Reference Systems Local Coordinates Recommendation while creating a high precision project User Roles and Permissions Terms of Use of Alteia Viewing Approved Term of Use
    Platform Administration keyboard_arrow_right
    Credit Use Monitoring
    Release Notes keyboard_arrow_right
    2021 Changelog 2019-2020 Changelog
  • The Alteia Platform keyboard_arrow_right
    Fuse
    Build
    Deploy
  • Applications by Industry keyboard_arrow_right
    Agriculture and Forestry
    Mining and Aggregates
    Civil Engineering and Construction keyboard_arrow_right
    3D Reconstruction of Assets and Buildings BIM Use Case Examples CAD Files Support Import French Cadastre
    Security and Defense keyboard_arrow_right
    Mission Use Case
    Power and Utilities
  • For Developers keyboard_arrow_right
    SDK & API keyboard_arrow_right
    Introduction to the Alteia SDK for Developers SDK Use Case Examples
US
FR
Contact Us
  • Home
  • Welcome to Alteia keyboard_arrow_right
    Key Concepts keyboard_arrow_right
    What is Alteia What is Ground Sampling Distance GSD How is Accuracy defined in mapping drone Dataset Definition
    Getting Started keyboard_arrow_right
    Quick Guide to the Alteia Interface Ground Control Points GCP Best Practices Coordinate Reference Systems Local Coordinates Recommendation while creating a high precision project User Roles and Permissions Terms of Use of Alteia Viewing Approved Term of Use
    Platform Administration keyboard_arrow_right
    Credit Use Monitoring
    Release Notes keyboard_arrow_right
    2021 Changelog 2019-2020 Changelog
  • The Alteia Platform keyboard_arrow_right
    Fuse
    Build
    Deploy
  • Applications by Industry keyboard_arrow_right
    Agriculture and Forestry
    Mining and Aggregates
    Civil Engineering and Construction keyboard_arrow_right
    3D Reconstruction of Assets and Buildings BIM Use Case Examples CAD Files Support Import French Cadastre
    Security and Defense keyboard_arrow_right
    Mission Use Case
    Power and Utilities
  • For Developers keyboard_arrow_right
    SDK & API keyboard_arrow_right
    Introduction to the Alteia SDK for Developers SDK Use Case Examples
  • Home
  • keyboard_arrow_right For Developers
  • keyboard_arrow_right SDK & API

SDK Use Case Examples

In this article we give some examples of Custom Analytics realizations using the Alteia Python SDK, over the digital twin of an asset reconstructed in Alteia.

Best Fuel Path for Vehicles in Mines & Quarries

This case illustrates how to integrate industrial machine data with site geospatial data.

“A quarry manager wants to use the most efficient routes on his site to move material from point A to point B” (typically, from the loading area in the pit to the crusher)".

How to solve this optimization issue ?

Using a modelization of the fuel consumption of trucks, and the 3D geospatial data resulting from the modelization of a quarry, it was possible to compute and display as a layer in Alteia the best trajectory along available haul roads that minimizes the overall fuel consumption between two points A and B. Let's examine the successive steps to this result.
Step 1 is to use Alteia built-in analytics for generating the quarry haul roads as an input to this fuel map computation :

  • Raw images are captured by drones
  • Drones images are processed in 2D or 3D in Alteia (they could be processed outside and ingested as well)
  • Alteia detects and extracts the haul roads

Step 2 is to define the fuel consumption between any points, using :

  • Vehicle-related data : e.g. rolling resistance, load
  • Drone-related data : lengths and elevation differences directly computed from the 3D model hosted in Alteia
def fuel_consumption(load, length, delta_z): 
return max(C_h*(1-RR)*(20000+load)/20000*length + C_v*(20000+load)
/20000*delta_z,0)

Step 3 is the development of a small Python script using the SDK. This script :

  • defines the KPI to be generated (fuel consumption)
  • calls the haul roads pattern as an input
  • calls the SDK functions
  • generates a visual map (.tiff)

In conclusion, it was possible to simulate the fuel cost associated to a certain positioning of the crusher versus the loading area


Was this article helpful?

sentiment_satisfied

Yes

sentiment_dissatisfied

No

RELATED QUESTIONS

  • Introduction to the Alteia SDK for Developers arrow_forward

Was this article helpful?

sentiment_satisfied

Yes

sentiment_dissatisfied

No

RELATED QUESTIONS

  • Introduction to the Alteia SDK for Developers arrow_forward

Sorry, we didn't find any relevant articles for you.

Please fill out the contact form below and we will reply as soon as possible.




Take the next step.

Request a demo or schedule a meeting to discuss your digital transformation ambitions.

Contact Us

Connect with us.

The world of Ai changes fast. Keep up to date with the Alteia platform by signing up to our newsletter :

Thank you for your message.

© 2021 Alteia. All rights reserved

LEGAL NOTICE
PRIVACY POLICY

© 2021 Alteia. All rights reserved

facebook logo
twitter logo
linkedin logo