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: 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, 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 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 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 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: 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 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 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: An ASG system for polygeneration with CC includes a devolatilizer that pyrolyzes solid fuel to produce char and gases. A burner adds exothermic heat by high-pressure sub-stoichiometric combustion, a mixing pot causes turbulent flow of the gases to heat received solid fuel, and a riser micronizes resulting friable char. A devolatilizer cyclone separates the micronized char by weight providing micronized char, steam and gases to a gasifier feed and oversized char to the mixing pot. An indirect fluid bed gasifier combustion loop includes a gasifier coupled to the gasifier feed, a steam input to provide oxygen for gasification and to facilitate sand-char separation, and an output for providing syngas. A burner provides POC to a mixing pot which provides hot sand with POC to a POC cyclone via a riser, where the POC cyclone separates sand and POC by weight and provides POC and sand for steam-carbon reaction.

Abstract: An ASG system for polygeneration with CC includes a devolatilizer that pyrolyzes solid fuel to produce char and gases. A burner adds exothermic heat by high-pressure sub-stoichiometric combustion, a mixing pot causes turbulent flow of the gases to heat received solid fuel, and a riser micronizes resulting friable char. A devolatilizer cyclone separates the micronized char by weight providing micronized char, steam and gases to a gasifier feed and oversized char to the mixing pot. An indirect fluid bed gasifier combustion loop includes a gasifier coupled to the gasifier feed, a steam input to provide oxygen for gasification and to facilitate sand-char separation, and an output for providing syngas. A burner provides POC to a mixing pot which provides hot sand with POC to a POC cyclone via a riser, where the POC cyclone separates sand and POC by weight and provides POC and sand for steam-carbon reaction.

Abstract: An ASG system for polygeneration with CC includes a devolatilizer that pyrolyzes solid fuel to produce char and gases. A burner adds exothermic heat by high-pressure sub-stoichiometric combustion, a mixing pot causes turbulent flow of the gases to heat received solid fuel, and a riser micronizes resulting friable char. A devolatilizer cyclone separates the micronized char by weight providing micronized char, steam and gases to a gasifier feed and oversized char to the mixing pot. An indirect fluid bed gasifier combustion loop includes a gasifier coupled to the gasifier feed, a steam input to provide oxygen for gasification and to facilitate sand-char separation, and an output for providing syngas. A burner provides POC to a mixing pot which provides hot sand with POC to a POC cyclone via a riser, where the POC cyclone separates sand and POC by weight and provides POC and sand for steam-carbon reaction.

Abstract: Various embodiments disclosed relate to cooling shale gas via reaction of methane, light hydrocarbons, or a combination thereof, with water. In various embodiments, the present invention provides a method of cooling syngas. The method includes contacting the hot syngas with methane or light hydrocarbons. The hot syngas includes water and has a temperature of about 800° C. to about 3000° C. The contacting is effective to endothermically react the methane or light hydrocarbons with the water in the hot syngas to form carbon monoxide and hydrogen and to provide a cooled syngas having a lower temperature than the hot syngas.

Abstract: Various embodiments disclosed relate to cooling shale gas via reaction of methane, light hydrocarbons, or a combination thereof, with water. In various embodiments, the present invention provides a method of cooling syngas. The method includes contacting the hot syngas with methane or light hydrocarbons. The hot syngas includes water and has a temperature of about 800° C. to about 3000° C. The contacting is effective to endothermically react the methane or light hydrocarbons with the water in the hot syngas to form carbon monoxide and hydrogen and to provide a cooled syngas having a lower temperature than the hot syngas.

Abstract: A method and apparatus are provided for improving water quality using a gasification system. Whereas water is normally a deterrent to the combustion process, water is beneficial to the gasification of carbonaceous materials. The method and apparatus uses this, and other aspects, to utilize several processes to improve water quality by means of gasification in new and beneficial ways.

Abstract: An apparatus and method for processing health care transactions through a common interface in a distributed computing environment using specialized remote procedure calls. The distributed computing environment includes a user interface tier for collecting user inputs and presenting transaction outputs, a data access tier for data storage and retrieval of health care transaction information, a transaction logic tier for applying a predetermined set of transaction procedures to user inputs and health care transaction information resulting in transaction output, an electronic network connecting the user interface tier, data access tier and transaction logic tier to each other and a communication interface for exchanging health care transaction information among the tiers. The communication interface includes an interface definition language generating transaction-specific communication codes whereby data is exchanged through a common interface structure regardless of the origin of the data.