Multi-object simplification is the core to the accuracy of user-submitted content in the PROWL system. Using this approach, poor data submissions can be corrected or rejected, leading to a higher quality of data content.
Using AI, polygons are enumerated based on a number of variables to ensure that invalid polygons are excluded, and that outlying datapoints are pruned. The variables that are used to inform the AI in it’s evaluation of polygons and datapoints include;
- The trust level of the source user – how many valid objects they have submitted in the past
- The trust level of the source data – such as from a mapping company vs a council
- The number of correlations between existing user-submitted polygons
- The potential for GPS inaccuracies that may skew data consistently in one direction
- Relationships between the submitted data and external sources of data – such as topography or 3rd party 3D model data sources
- The source of the user-submitted data; was it from a drone’s sensors, through flight planning software, through the web form, through 3D modelling software etc.
- Extrapolation of the polygon model shape based on the categorisation type – a long, thin object used to represent a wire type, as opposed to a block object representing a building type.
- AI interpretation of interpolations and extrapolations of the likely location of objects and data
- Other patent-pending approaches and analysis methods