The Virtual Weather Station

  • Updated

What is a SMV?

The SMV (Virtual Weather Station) is a virtual sensor that provides you with reconstructed weather data for any geographical location — without any physical hardware to install.

It replaces the former Météo Vision option by adopting a format you already know: that of a standard Weenat sensor, with its own serial number, data page, position on the map and history.

Météo Vision (former)SMV (new)
Option activatable on a plotIndependent sensor with serial number
Low visibility, often misunderstoodOwn data page, visible on the map
Per plotLink it to as many plots as you wish
Strongly coupled to the plotMoveable, history always preserved

Automatic migration — If you were using Météo Vision, your existing plots have been automatically migrated to SMVs. Your data history is fully preserved.


Available data

MeasurementFrequencyTime step
Temperature (T) °CHourly (minimum delay 3 h)Hour / Day / Week / Month
Precipitation (RR) mm
Humidity (U) %

SMVs have neither a battery indicator nor a signal quality indicator. It is not possible to create alerts on a plot linked to a SMV.

Why is my data not yet available after creation?

Data is updated every hour with a minimum delay of 3 hours. If the SMV has just been created or positioned in an area without recent history, it is normal not to see data immediately. If the situation persists beyond 6 hours, contact support.


Create a SMV

  1. From the "+" button or from the "All sensors" list, press "Add a sensor", then select "SMV".
  2. Position the SMV on the map by placing it at the desired location (drag the map or enter a city name to re-centre the map). A location is required to confirm the creation.
  3. Confirm the creation. The SMV immediately receives a unique serial number. The data history starts from this moment — it is not possible to backdate.

SMV quota — You have 2 SMVs per organisation by default. A message will appear if you try to exceed this quota.


Move a SMV

You can move a SMV at any time from its settings page. Simply select a new position on the map.

When moving, the data history and links with plots are fully preserved. New data will reflect the new position from the next update (usual delay of 3 h).


Link a SMV to a plot

Linking allows a plot to receive weather data from the SMV. You can link from the plot creation flow or from the quick link module.

What is possible

  • Link a SMV to several plots simultaneously.
  • Unlink a SMV from a plot and link it to another.
  • Combine the history of a SMV with that of a physical station (before or after the linking period).

What is not possible

  • Link 2 SMVs to the same plot.
  • Link a SMV and a physical sensor to the same plot.
  • Backdate the SMV ↔ plot link.
  • Create alerts on a SMV or on a plot linked to a SMV (for now)

If a plot linked to a SMV is archived or deleted, the link is automatically broken. The SMV and its data are not affected.


Delete a SMV

Irreversible action — read carefully before continuing.

Deleting a SMV permanently erases its data history. 

Plots previously linked to SMVs do not lose the data history provided by the SMV during the linking period.

  1. Open the SMV settings page.
  2. Scroll down to the Danger zone area and press Delete the SMV.
  3. Confirm the deletion in the warning window. The SMV immediately disappears from the map, the sensor list and all linked plots.

Deletion frees up a slot in your quota, allowing you to create a new SMV.

It is not possible to archive a SMV — deletion is the only removal option available.


Request more SMVs

If you would like to have more than 2 SMVs, this is possible. To obtain more, click on the "+" button, then on "Get more stations" and finally on "Be contacted". An email with your details will be sent to our sales team who will get back to you.


Frequently asked questions

Why do I have more than 2 SMVs on my account?
Can I place a SMV on a river, lake or mountain?

Yes, a SMV can be positioned at any geographical point, including a body of water or a relief. The reconstructed data remains consistent with the weather conditions of the area.

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