Abstract: A method includes obtaining a fault prediction model for building equipment, predicting, with the fault prediction model, both (i) whether a fault will occur during a first prediction bin and (ii) whether a fault will occur during a second prediction bin, performing a first mitigating action for the building equipment if the fault is predicted to occur during the first prediction bin, and performing a second mitigating action for the building equipment if the fault is predicted to occur during the second prediction bin.

Abstract: A system includes a plurality of devices of building equipment, an additional device of building equipment, and a computing system. The computing system is configured to process data from the plurality of devices to extract common features of the plurality of devices, train a global model based on the common features, obtain additional data from the additional device, adapt the global model for the additional device based on the additional data to obtain an adapted model for the additional device, predict a status of the additional device using the adapted model, and affect an operation of the additional device based on the status.

Abstract: A building system including one or more storage devices storing instructions thereon that, when executed by one or more processors, cause the one or more processors to receive an indication to execute an artificial intelligence (AI) agent, execute the AI agent based on the digital twin to generate an inference or a prediction, cause a graphical model of the building including graphical representations of the entities to include information based on the inference or the prediction, and cause a display device of a user device to display the graphical model.

Abstract: A building system can operate to receive an indication from a user device of a user to query a digital twin of one or more buildings, the digital twin including entities including buildings, equipment, spaces, or data of the one or more buildings, the equipment, or the spaces, the digital twin including relationships between the entities. The building system can operate to receive building data from the digital twin by querying the digital twin based on the indication received from the user device. The building system can operate to generate an analytics model based on the building data, wherein the analytics model is trained based on the building data and deploy the analytics model to operate based on data of the one or more buildings and generate one or more analytic results based on the data of the one or more buildings.

Abstract: A building system of a building operates to receive historical data values of the plurality of data points for a plurality of historical times, execute an artificial intelligence to generate a plurality of inference values of a data point for a plurality of future times based on the historical data values, generate user interface data causing a user device to display a graphic representation of the building including a selectable element providing selections of the plurality of historical times and the plurality of future times, receive a selection from the user device via the selectable element of a future time of the plurality of future times, and cause the user device to display the graphic representation of the building with a plurality of states based on the future data values.

Abstract: A building system including one or more storage devices storing instructions thereon that, when executed by one or more processors, cause the one or more processors to receive an indication to execute an artificial intelligence (AI) agent, execute the AI agent based on the digital twin to generate an inference or a prediction, cause a graphical model of the building including graphical representations of the entities to include information based on the inference or the prediction, and cause a display device of a user device to display the graphical model.

Abstract: A building system of a building operates to store a digital twin of the building in the one or more storage devices, wherein a virtual indicator is related to an entity of the building by the digital twin. The building system operates to receive telemetry data for a piece of building equipment of the building for the data point, generate the virtual indicator from the telemetry data, and cause a graphic representation of the building to display the virtual indicator within the graphic representation of the building.

Abstract: A building system of a building operates to receive historical data values of the plurality of data points for a plurality of historical times. The building system operates to execute an artificial intelligence to generate a plurality of different operating scenarios for operating equipment of the building for the plurality of historical times and simulate a plurality of values of data points of the building for the plurality of historical times based on the plurality of different operating scenarios and the historical data values. The building system operates to cause a user device to display a graphic representation of the building and a selectable element of a historical time of the plurality of historical times.

Abstract: A building system of a building operates to store a digital twin of the building in the one or more storage devices, wherein the digital twin further includes an artificial intelligence configured to generate a plurality of inference values of a data point for a plurality of future times, the data point related to the building by the interrelationship of the digital twin. The building system operates to generate a recommendation based on the plurality of inference values for the data point for the plurality of future times, the recommendation recommending making one or more updates to the building, and cause a graphic representation of the building to display an indication of the recommendation.

Abstract: A building system of a building operates to receive historical data values of the plurality of data points for a plurality of historical times, receive a selection of a proposed update to the building, the proposed update changing control of the building or physical characteristics of the building at a past time, a current time, or a future time, execute an artificial intelligence to generate a plurality of inference values of the plurality of data points for the plurality of historical times or a plurality of future times based on the historical data values and the proposed update, and generate user interface data causing a user device to display a graphic representation of the building with a plurality of states at the plurality of future times or the plurality of historical times.

Abstract: A building system can operate to receive a requirement to implement an artificial intelligence (AI) service. The requirement can include an indication of a type of an entity, wherein the AI service is configured to generate an analytic for the entity of the type of the entity or a control setting for the entity of the type of the entity. The requirement can include a data element that the AI service is configured to operate on to generate the analytic or the control setting. The building system can operate to determine that the building system meets the requirement to implement the AI service responsive to a determination that a digital twin of the building system includes the entity of the entity type and the data element and implement the AI service responsive to a determination that the building system meets the requirement.

Abstract: The present disclosure provides a data transmission method, a terminal, and a network side device. The data transmission method includes: before an air interface signaling connection is established, sending a data message carrying state transition data to a network side device; receiving a response message returned by the network side device in response to the data message, a data transmission indication included in the response message; when the data transmission indication indicates transmitting, sending an uplink data packet to the network side device.

Abstract: A method for generating a graph data structure comprises receiving, by one or more processors, data associated with a building, generating one or more space nodes in the graph data structure corresponding to spaces within the building based on the data, generating one or more asset nodes in the graph data structure corresponding to assets within the building based on the data, associating sensor data with the one or more asset nodes based on the data, classifying the sensor data based on the data, and generating a relationship between at least two of the one or more space nodes, the one or more asset nodes, and the classified sensor data.

Abstract: A method for commissioning a building comprises identifying a building asset within a digital representation of a building having one or more parameters describing relationships of the building asset within the building, controlling one or more other building assets included within the digital representation to change an environmental parameter of the building, monitoring a response of at least one of the building asset or one of the one or more other building assets to the change in the environmental parameter, generating a parameter for the digital representation associated with the building asset based on the monitoring, and updating the digital representation using the parameter.

Abstract: A method for augmenting a building model comprises receiving a first building model associated with at least a portion of a building and having a first format, receiving a second building modeling associated with the portion of the building and having a second format, comparing the first building model to the second building model to identify at least one element in the first building model not included in the second building model, and updating the second building model to include the identified at least one element.

Abstract: A method of labeling building data comprises receiving, by a labeling system, a plurality of strings relating to data associated with a building, wherein the plurality of strings are received from one or more building devices, segregating the plurality of strings based on at least one semantic element included in the plurality of strings, clustering the plurality of strings based on at least one related element shared by at least a portion of the plurality of strings, labeling at least some of the plurality of strings based on the segregated and clustered plurality of strings, and generating a digital representation of the building using the labeled strings.

Abstract: A method for visualizing a building model comprises retrieving an identifier associated with a digital representation of a building asset from a digital representation representing at least a portion of a building, retrieving, using the identifier, a graphical representation of the asset from a building model having a different format than the digital representation, and rendering the graphical representation on a display device.

Abstract: Embodiments of the present disclosure provide methods and devices for transmitting SI. The method includes: when the terminal transmits an other SI request, determining a transmission mode of an other SI request according to configuration information, which is pre-stored by the terminal or configured by a base station; and transmitting the other SI request to the base station according to the transmission mode. The other SI request is used to request for at least one type of other SI and the transmission mode includes transmitting the other SI request via msg1 or msg3.

Abstract: A building system including one or more memory devices configured to store instructions thereon, that, when executed by one or more processors, cause the one or more processors to generate building recommendations based on recommendation requests with a model of a first model type when less than a predefined amount of model training data is available and receive feedback data on the recommendation requests generated by the model of the first model type. The instructions cause the one or more processors to transition from generating the building recommendations by the model of the first model type to a second model of a second model type by comparing performance of the first model type to the second model type based on the feedback data.

Abstract: Disclosed are a pentacyclic triterpene compound as shown in general formula (I) and a preparation method therefor. The compound has an effective antagonistic effect on FXR receptors.