BUILDING AUTOMATION SYSTEMS WITH REGIONAL INTELLIGENCE

1 . A method for troubleshooting a building automation system, comprising:

selecting an artificial intelligence tool from a set of available artificial intelligence tools based on the geographic region of the building automation system;

ranking troubleshooting options for the building automation system by applying the artificial intelligence tool to data associated with the building automation system; and

implementing at least a first troubleshooting option, the first troubleshooting option ranked higher than a remainder of the troubleshooting options by the artificial intelligence tool.

2 . The method of claim 1 , further comprising ignoring one or more of the troubleshooting options based on the geographic region of the building automation system.

3 . The method of claim 1 , wherein implementing at the least the first troubleshooting option comprises automatically adjusting operation of building equipment operated by the building automation system.

4 . The method of claim 1 , wherein implementing at the least the first troubleshooting option comprises adjusting an installation of one or more devices of the building automation system.

5 . The method of claim 1 , wherein implementing at the least the first troubleshooting option comprises changing configuration parameters of one or more devices of the building automation system.

6 . The method of claim 1 , further comprises displaying the first troubleshooting option to a user via a mobile application.

7 . The method of claim 1 , wherein selecting the artificial intelligence tool is further based on a domain of building equipment to be troubleshot.

8 . The method of claim 1 , comprising training the available artificial intelligence tools are associated with different geographic regions and trained on different data sets associated with the different geographic regions.

9 . The method of claim 1 , wherein the available artificial intelligence tools comprise:

a first artificial intelligence tool comprising a first generative artificial intelligence model fine-tuned or augmented using first training data from a first geographic region;

a second artificial intelligence tool comprising a second generative artificial intelligence model fine-tuned or augmented using second training data from a second geographic region.

10 . One or more non-transitory computer-readable media storing instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising:

selecting, based on a location, an artificial intelligence tool from a set of available artificial intelligence tools associated with a plurality of geographic regions, the available artificial intelligence tools trained using different training data associated with the different geographic regions;

ranking troubleshooting options by applying the artificial intelligence tool to data associated with the location; and

causing implementation of at least a first troubleshooting option, the first troubleshooting option ranked higher than a remainder of the troubleshooting options by the artificial intelligence tool.

11 . The one or more non-transitory computer-readable media of claim 10 , wherein the location corresponds to a building, and wherein the troubleshooting options comprise maintenance or service tasks for building equipment serving the building.

12 . The one or more non-transitory computer-readable media of claim 10 , wherein the available artificial intelligence tools comprise:

a first artificial intelligence tool comprising a generative artificial intelligence model and a first augmentation function; and

a second artificial intelligence tool comprising the generative artificial intelligence model and second augmentation function.

13 . The one or more non-transitory computer-readable media of claim 10 , wherein selecting the artificial intelligence tool is further based on a domain of building equipment to be troubleshot

14 . The one or more non-transitory computer-readable media of claim 10 , wherein causing implementation of at the least the first troubleshooting option comprises automatically adjusting operation of building equipment at the location.

15 . A method, comprising:

communicating building automation information with a plurality of building automation systems located in a plurality of geographic regions;

automatically adjusting the building automation information in accordance with different regional terminology used by the plurality of building automation systems; and

controlling building equipment with at least a first building automation system of the plurality of building automation systems based on:

inputs provided by a first user in a first geographic region using a first regional terminology associated with the first geographic region; and

inputs provides by a second user in a second geographic region using a second regional terminology associated with the second geographic region.

16 . The method of claim 8 , wherein the first building automation system and the first user are located at the first geographic region and the second user is located at the second geographic region.

17 . The method of claim 8 , wherein the first user is associated with the first building automation system and the second user provides support for the plurality of building automation systems.

18 . The method of claim 8 , wherein automatically adjusting the building automation information in accordance with the different regional terminology comprises applying a machine learning model to the building automation information.

19 . The method of claim 11 , further comprising:

prompting, via the plurality of building automation systems, users at the plurality of geographic regions to answer questions relating to the different regional terminology used by the users; and

training the machine learning model based on answers to the questions.

20 . The method of claim 8 , wherein automatically adjusting the building automation information in accordance with the different regional terminology used by the plurality of building automation systems comprises normalizing point labels for data provided by the plurality of building automation systems to facilitate analysis of aggregations of the data from the plurality of building automation systems.