Where the money lies: Waste management

When it comes to waste collection, we are not even aware of how deep we are getting into the information system, especially when geolocation is involved!
Think it’s simple?
So let me ask you what amount of plastic waste was collected on Street XY at house number 22 during the month of April?

How much is the average per tenant in that building?

So to start with, processing GIS data for analysis in Tableau.

In the GIS system we have 3 information:
1) A building as a polygon
2) the house number as a point
3) Zone as a polygon
I used the Manifold System to prepare GIS data, although it could also be done with QGIS or some other tool.
The information about the building and the zone had to be transferred to the house number data, the zone data from the zone to the building, and the initial data aggregation was made. This is very simple in Manifold because the quality of data transfer and aggregation is solved. It is important to attribute GIS data to avoid the use of slow operations that can be performed slowly.
When this is done, we connect to the database and start doing the tasks in Tableau.

When it comes to waste management, it is important to choose quality indicators such as:

  • How much of what type of waste is collected over a period of time
  • How many times containers have been emptied
  • How much waste is collected per capita
  • Is there a correlation between the volume collected and the cost of the removal service
  • Is there a correlation between residential buildings and single-family homes in terms of the amount of volume collected per capita
Waste Management

From such a set of data, we can now see the direct results of the analysis, and come to the right conclusion!

Waste in details

In few day i will put whole dashboard on Tableau public, and you will find it easy using: https://public.tableau.com/profile/geobiviz#!/

If you have any question, please let me know!

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