Spaces in your IoT project

Spaces are a powerful tool to organize your data structure in Dimension Four and are thus giving you a multitude of options when designing your system.

Below we will run you through an example of using spaces to get your project oranized.

Let’s assume you are collecting temperature data from a number of physical buildings and all the rooms in those buildings.

First we create a main space for all of your buildings and name it «Buildings». Secondly we create a space for each building («Building Address X») and define the parent space for these as «Buildings». 

Further you could even define each room in the building in a similar way as a space with parent space as «Building Address X».

Then you add points in the appropriate places - most likely in the space that fits the location best, i.e. temperature sensor as Point Temperature in Buildings/Building Address 2/Kitchen.

You could know have a data structure looking like this:

Space: «Buildings» 
Space: «Building Address 1»
Space: «Kitchen»
Point: "KitchenCorner"
Signal: {temperature: "22"}
Point: "KitchenDoor"
Signal: {temperature: "21"}
Space: «Office»
Point: "OfficeSouthWall"
Signal: {temperature: "19"}
Point: "OfficeDoor"
Signal: {temperature: "18"}
Space: «Building Address 2»
Space: «Kitchen»
Point: "KitchenCorner"
Signal: {temperature: "22"}
Point: "KitchenDoor"
Signal: {temperature: "21"}
Space: «Office»
Point: "OfficeSouthWall"
Signal: {temperature: "19"}
Point: "OfficeDoor"
Signal: {temperature: "18"}

As you see this becomes a very logical structure for your data analysts and front-end developers to work with. All accessible through our GraphQL API´s 

astronaut

Ready to get started?