And when it comes to generating inventory elements automatically or semi-automatically, artificial intelligence ensures the Jakarto platform performs above and beyond.
Jakarto collects HD geographic data, processes it, and renders it in 3D.
It creates what’s called a digital twin, a virtual replica of a specific city or landscape. The technology is made possible thanks to Jakarto’s mobile mapping units, which capture the data.
Using its cameras and LiDARS, Jakarto creates georeferenced imagery and 3D point clouds.
Next, it uses AI-based processing methods to transform raw data into intelligent, ready-to-use data.
Artificial intelligence consists of algorithms that, when well designed and trained, answer their own questions instead of deferring to experts.
Jakarto uses AI to detect specific objects in its geospatial datasets and map them.
The AI advantage? It saves considerable time and money. The process is automated, and the algorithm runs continually, letting us humans focus on more important tasks.
The 3D data that we capture represent reality at an instant T and are translated by point clouds.
Once collected, Jakarto’s 3D data is translated into point cloud form, representing a snapshot of reality. Next, thanks to an algorithm, objects and their positions can be identified with precision.
A 3-stage process
Jakarto cross-references its data with a pre-existing or in-house database.
Its experts manually recognize objects and create point clouds for them.
Data preparation phase
Jakarto provides the algorithm with raw 3D data samples along with results indicating what these samples are meant to represent.
The more annotated examples given to the machine, the more it learns how to identify the common characteristics that separate one object from another.
The training phase
Next, Jakarto uses a computational graph to attempt to categorize the 3D data. Its team compares the model’s results to the expected outcomes and shows both datasets to the algorithm.
By seeing its own errors, the algorithm learns how to self-correct and improve.
The model backup phase
The model application phase
Jakarto then uses the model to translate new data never seen by the algorithm.
The machine now does a human’s job