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Unleashing the Power of Geometry: Arcanor's Advanced Location-Based Capabilities

Arcanor's unique capability to perform complex geometric computations sets it apart from others in the market. Our technology allows us to simulate any location anywhere in the world, providing our clients with unparalleled accuracy and precision. This capability is made possible by our ability to store and compute geometries in a database, which is a considerably more complex process than computing single pairs of coordinates.

To put it into perspective, traditional location analysis methods often rely on a point-radius approach, where a location is represented by a single point and its surrounding area is defined by a radius. This method is limited and often lacks precision. Arcanor, on the other hand, uses a polygon approach, where a location is defined by its boundaries, providing a much more accurate representation of the area.

By leveraging this technology, Arcanor provides its clients with the ability to analyze locations in a more comprehensive and sophisticated way. This allows companies to gain a deeper understanding of their market and customers, enabling them to make more informed decisions and drive growth. So if you are looking for a platform that provides advanced location analysis capabilities, look no further than Arcanor.


The use of radius method in location-based data analysis can have several potential harms, such as:

  1. Inaccuracy: The point-radius method assumes that all activities within a certain radius are relevant, which can lead to inaccurate results.

  2. Bias: This method can also introduce bias into the data, as it tends to favor larger areas and underrepresent smaller ones.

  3. Overgeneralization: The use of a single radius value for an entire area can lead to overgeneralization and a loss of detail in the data.

  4. Limited Customization: The point-radius method offers limited customization options and does not account for specific shape, size or location of a geographic area.

  5. Unrepresentative Samples: The method can also result in unrepresentative samples, as it may exclude areas that are not within the radius but are still relevant to the analysis.

By utilizing advanced geometric computations, Arcanor can overcome these limitations and provide more accurate, representative and customizable location-based data analysis.


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