Abstract: A building system can include one or more storage devices storing instructions thereon, that, when executed by one or more processors, cause the one or more processors to generate a building graph, the building graph including nodes representing entities of a building and edges between the nodes, the edges representing relationships between the entities. The building system can execute an artificial intelligence service, the artificial intelligence service to receive at least one of data describing the entities, at least one node of the nodes, or at least one edge of the edges as an input and output a correlator type that identifies that a first entity type of a first entity of the entities impacts a second entity type of a second entity of the entities. The building system can update the building graph to include data representing a correlator based on the correlator type.

Abstract: Systems and methods are disclosed relating to building management systems with goal-based sensor plan generation. For example, a method can include receiving data relating to a layout of a space of a building and/or one or more sensors of the building. The method can further include determining, using an artificial intelligence (AI) model, a goal for the space. The method can further include autonomously generating, using the AI model, a proposed sensor plan for the space based on the data and the goal without requiring manual user intervention. The method can further include providing the proposed sensor plan to a user.

Abstract: Systems and methods are disclosed relating to building management systems with sustainability improvement for a building. For example, a system can include at least one machine learning model configured using training data that includes at least one of unstructured data or structured data regarding sustainability of buildings. The system can provide inputs, such as prompts, to the at least one machine learning model regarding a sustainability performance of the building, and generate, according to the inputs, responses regarding the sustainability performance of the building, such as responses for detecting factors and/or sources contributing to the sustainability performance of the building.

Abstract: A method of operating a building includes recommending, by one or more processors, an action for the building responsive to a user query, predicting, by the one or more processors, a plurality of entities affected by the action. The plurality of entities are associated with a plurality of separate domain systems and the plurality of separate domain systems use a plurality of different data formats. The method also includes generating, by the one or more processors using at least one generative AI model, a plurality of control outputs in the plurality of different data formats and affecting operations of the plurality of separate domain systems by providing the plurality of control outputs in the plurality of different data formats to the plurality of separate domain systems.

Abstract: Systems and methods are disclosed relating to building management systems with building equipment servicing. For example, a system can include at least one machine learning model configured using training data that includes at least one of unstructured data or structured data regarding items of equipment. The system can provide inputs, such as prompts, to the at least one machine learning model regarding an item of equipment, and generate, according to the inputs, responses regarding the item of equipment, such as responses for detecting a cause of an issue of the item of equipment, performing a service operation corresponding to the cause, or guiding a user through the service operation.

Abstract: A method including training, by one or more processors, a generative AI model using a plurality of first service requests handled by technicians for servicing building equipment. The generative AI model may be trained to predict root causes of a plurality of first problems corresponding to the plurality of first service requests. The method may include receiving, by the one or more processors, a second service request for servicing building equipment. The method may include predicting, by the one or more processors using the generative AI model, a root cause of a second problem corresponding to the second service request based on characteristics of the second service request and one or more patterns or trends identified from the plurality of first service requests using the generative AI model.

Abstract: Systems and methods for building management utilizing adaptive edge processing are disclosed. The building system can store gateway components on storage devices. The gateway components can facilitate communication with a cloud platform and facilitate communication with a physical building device. The building system can identify a computing system of the building that is in communication with the physical building device. The physical building device can store one or more data samples. The building system can deploy the gateway components to the computing system responsive to identifying that the computing system is in communication with the physical building device. The gateway components can cause the computing system to communicate with the physical building device to receive the one or more data samples and cause the computing system to communicate the one or more data samples to the cloud platform.

Abstract: A method including training, by one or more processors, a generative AI model using a plurality of first unstructured service reports corresponding to a plurality of first service requests handled by technicians for servicing building equipment. The plurality of first unstructured service reports include unstructured data not conforming to a predetermined format or conforming to a plurality of different predetermined formats. The method includes receiving, by the processors, a second service request for servicing building equipment. The method includes generating, by the processors using the generative AI model, a user interface prompting a user to provide information about a problem leading to the second service request as unstructured data not conforming to the predetermined format or conforming to the plurality of different predetermined formats.

Abstract: A method includes receiving, by one or more processors, an unstructured service report corresponding to a service request handled by one or more technicians for servicing building equipment. The unstructured service report may include unstructured data not conforming to a predetermined format or conforming to a plurality of different predetermined formats. The method may include extracting, by the one or more processors, a set of standards from one or more technical documents associated with the building equipment. The method may include automatically generating, by the one or more processors using a generative AI model, a structured service report in the predetermined format for delivery to a customer associated with the building equipment. Generating the structured service report may include standardizing the structured service report to comply with the set of standards extracted from the one or more technical documents associated with the building equipment.

Abstract: A method includes training, by one or more processors, a generative AI model using a plurality of first service requests handled by technicians for servicing building equipment and outcome data indicating outcomes of the plurality of first service requests. The generative AI model may be trained to identify one or more patterns or trends between characteristics of the plurality of first service requests and the outcomes of the plurality of first service requests. The method may include receiving a second service request for servicing building equipment. The method may include automatically determining, using the generative AI model, one or more responses to the second service request based on characteristics of the second service request and the one or more patterns or trends between the characteristics of the plurality of first service requests and the outcomes of the plurality of first service requests identified using the generative AI model.

Abstract: A method includes receiving, by one or more processors, an unstructured service report corresponding to a service request handled by one or more technicians for servicing building equipment. The unstructured service report may include unstructured data not conforming to a predetermined format or conforming to a plurality of different predetermined formats. The method may include automatically generating, by the one or more processors using a generative AI model, a structured service report in the predetermined format for delivery to a customer associated with the building equipment. The structured service report may include additional content generated by the generative AI model and not provided within the unstructured service report.

Abstract: A method includes receiving, by one or more processors, a plurality of first unstructured service reports corresponding to a plurality of first service requests handled by technicians for servicing building equipment. The plurality of first unstructured service reports may include unstructured data not conforming to a predetermined format or conforming to a plurality of different predetermined formats. The method may include training, by the one or more processors, a generative AI model using the plurality of first unstructured service reports. The method may include performing, by the one or more processors using the trained generative AI model, one or more actions with respect a second service request subsequent to training the generative AI model.

Abstract: A method includes receiving, by one or more processors, unstructured service data corresponding to one or more service requests handled by technicians for servicing building equipment of a building. The method may include detecting, by the one or more processors, an identifier of the building equipment, a space of the building, or a customer associated with the building using the unstructured service data. The method may include retrieving, by the one or more processors based on the identifier of the building equipment, the space, or the customer, additional data associated with the building equipment, the space, or the customer from one or more additional data sources separate from the unstructured service data. The method may include training, by the one or more processors, a generative AI model using training data including the unstructured service data and the additional data.

Abstract: A method including training, by one or more processors, a generative AI model using first operating data from building equipment and a plurality of first service reports indicating a plurality of first problems associated with the building equipment. The method may include predicting, by the one or more processors using the generative AI model, one or more future problems likely to occur with the building equipment based on second operating data from the building equipment. The method may include automatically initiating, by the one or more processors, one or more actions to prevent the one or more future problems from occurring or mitigate an effect of the one or more future problems.

Abstract: A method includes training, by one or more processors, a generative AI model using training data including a plurality of first service requests indicating a plurality of first problems associated with building equipment and a plurality of first actions performed in response to the plurality of first service requests. The method may include receiving, by the one or more processors, a second service request indicating a second problem associated with building equipment. The method may include automatically determining, by the one or more processors using the generative AI model, one or more second actions to perform based on characteristics of the second service request. The method may include automatically initiating, by the one or more processors, the one or more second actions to address the second problem associated with the building equipment.

Abstract: Systems and methods to generate new equipment models and/or connectors to integrate the new equipment models are described herein. Generation of new equipment models can include retrieving information from one or more publicly accessible data sources.

Abstract: A method includes providing a plurality of units building equipment operable to directly affect one or more physical conditions of a building, connecting the plurality of units of building equipment to a communication network, and automatically establishing, by the plurality of units of building equipment, communications between the plurality of units of building equipment and an off-premise server via the communication network. Such communications are preferably not routed through any controllers external to the plurality of units of building equipment.

Abstract: A distributed transaction ledger (e.g. a blockchain) is used to track and validate changes in a building management system such as a building automation system, access control system, or security/surveillance system. The building management system 100 includes a series of distributed devices connected to a peer-to-peer validation network. The distributed devices generate transaction information during normal operation and broadcast the transaction information to the validation network. The validation network maintains a distributed transaction ledger for the building management system, for example, by validating the transaction information and distributing the transaction information across the validation network according to consensus criteria to be stored locally in multiple instances by nodes of the validation network, which can be dedicated computing devices and/or validator distributed devices.

Abstract: Systems and methods for building management utilizing adaptive edge processing are disclosed. The building system can store gateway components on storage devices. The gateway components can facilitate communication with a cloud platform and facilitate communication with a physical building device. The building system can identify a computing system of the building that is in communication with the physical building device. The physical building device can store one or more data samples. The building system can deploy the gateway components to the computing system responsive to identifying that the computing system is in communication with the physical building device. The gateway components can cause the computing system to communicate with the physical building device to receive the one or more data samples and cause the computing system to communicate the one or more data samples to the cloud platform.

Abstract: A system includes a unit of building equipment serving a building and including a heating, ventilation, or cooling component and onboard circuitry configured to execute a configuration routine stored on the circuitry which automatically configures parameters of the rooftop unit based on the signals received from sensors and devices at the building. The system also includes a cloud system communicably connectable to the onboard circuitry and configured to influence the configuration routine.