Patents by Inventor Prashanthi Sudhakar

Prashanthi Sudhakar has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 12242937
    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.
    Type: Grant
    Filed: January 22, 2024
    Date of Patent: March 4, 2025
    Assignee: Tyco Fire & Security GmbH
    Inventors: Julie J. Brown, Young M. Lee, Rajiv Ramanasankaran, Sastry KM Malladi, Michael Tenbrock, Levent Tinaz, Samuel A Girard, David S. Elario, Juliet A Pagliaro Herman, Miguel Galvez, Trent M. Swanson, John F. Kuchler, Deepak Budhiraja, Daniela M. Natali, Josip Lazarevski, Scott Deering, Gary W. Gavin, Kristen Sheppard-Guzelaydin, James Young, Prashanthi Sudhakar, Kaleb Luedtke, Karl F. Reichenberger, Wenwen Zhao, Adam R. Grabowski, Lauren C. Dern, Nicole A. Madison, Dana S. Petersen, Nevin L. Forry, Pedriant Pena, Ghassan R. Hamoudeh, Ryan G. Danielson
  • Publication number: 20240402664
    Abstract: Systems and methods are disclosed relating to democratizing entity data utilizing machine learning models and/or generative AI. A system can include one or more processors configured to receive a prompt identifying an item of equipment for service. The one or more processors can generate, using at least one machine learning model and based on the prompt, a completion representing a service action to perform for the item of equipment, the at least one machine learning model configured using training data including a plurality of unstructured data elements corresponding to items of equipment. The one or more processors can present the completion using at least one of a display device or an audio output device.
    Type: Application
    Filed: May 30, 2024
    Publication date: December 5, 2024
    Inventors: Prashanthi Sudhakar, Vineet Binodshanker Sinha, Gregory A. Makowski, Julie Joanne Brown
  • Publication number: 20240403343
    Abstract: A building management system (BMS) can include one or more memory devices storing instructions thereon that can, when executed by one or more processors, cause the one or more processors to receive a plurality of information, generate a data model to represent the plurality of information in a common format associated with the BMS, execute a pre-processing routine, receive a query that corresponds to a building associated with the BMS, identify a given vector embedding of a plurality of vector embeddings that correlates to first information associated with the building, generate a response to the query that includes at least one of a graphical representation of the first information associated with the building or a textual summary of the first information associated with the building.
    Type: Application
    Filed: May 29, 2024
    Publication date: December 5, 2024
    Inventors: Rajiv Ramanasankaran, Sastry KM Malladi, Trent M. Swanson, Miguel Galvez, Gregory A. Makowski, Prashanthi Sudhakar
  • Publication number: 20240402662
    Abstract: An action generation method includes receiving, by one or more processors via a conversational interface, a query from a user, receiving, by the one or more processors, building subsystem data for one or more building subsystems in a building, retrieving, by the one or more processors, subject matter expert data, determining, by the one or more processors, an anomaly of the one or more building subsystems, based on the subject matter expert data and the building subsystem data, generating, by the one or more processors, a recommendation to resolve the anomaly based on fault detection and diagnostic (FDD) data related to a fault determined in the one or more building subsystems, and generating, by the one or more processors using a generative large language model, a response to the query based on the recommendation, the FDD data, and the subject matter expert data.
    Type: Application
    Filed: May 29, 2024
    Publication date: December 5, 2024
    Inventors: Rajiv Ramanasankaran, Sastry KM Malladi, Trent M. Swanson, Miguel Galvez, Gregory A. Makowski, Prashanthi Sudhakar
  • Publication number: 20240393753
    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.
    Type: Application
    Filed: May 23, 2024
    Publication date: November 28, 2024
    Inventors: James Young, Gregory A. Makowski, Michael J. Wenzel, Prashanthi Sudhakar, Vineet Binodshanker Sinha, Trent M. Swanson, Miguel Galvez
  • Publication number: 20240394444
    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.
    Type: Application
    Filed: May 24, 2024
    Publication date: November 28, 2024
    Inventors: Trent M. Swanson, Miguel Galvez, Vineet Binodshanker Sinha, Kaleb Luedtke, Prashanthi Sudhakar, John T. Pierson
  • Publication number: 20240377792
    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.
    Type: Application
    Filed: May 10, 2024
    Publication date: November 14, 2024
    Inventors: Julie J. Brown, Young M. Lee, Rajiv Ramanasankaran, Sastry KM Malladi, Michael Tenbrock, Levent Tinaz, Samuel A. Girard, David S. Elario, Juliet A. Pagliaro Herman, Trent M. Swanson, Miguel Galvez, John F. Kuchler, Deepak Budhiraja, Daniela M. Natali, Josip Lazarevski, Scott Deering, Gary W. Gavin, Kristen Sheppard-Guzelaydin, James Young, Prashanthi Sudhakar, Kaleb Luedtke, Karl F. Reichenberger, Wenwen Zhao, Gregory A. Makowski
  • Publication number: 20240362544
    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.
    Type: Application
    Filed: June 28, 2024
    Publication date: October 31, 2024
    Inventors: Julie J. Brown, Young M. Lee, Rajiv Ramanasankaran, Sastry KM Malladi, Michael Tenbrock, Levent Tinaz, Samuel A. Girard, David S. Elario, Juliet A. Pagliaro Herman, Miguel Galvez, Trent M. Swanson, John F. Kuchler, Deepak Budhiraja, Daniela M. Natali, Josip Lazarevski, Scott Deering, Gary W. Gavin, Kristen Sheppard-Guzelaydin, James Young, Prashanthi Sudhakar, Kaleb Luedtke, Karl F. Reichenberger, Wenwen Zhao, Adam R. Grabowski, Lauren C. Dern, Nicole A. Madison, Dana S. Petersen, Nevin L. Forry, Pedriant Pena, Ghassan R. Hamoudeh, Ryan G. Danielson
  • Publication number: 20240346611
    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.
    Type: Application
    Filed: April 11, 2024
    Publication date: October 17, 2024
    Inventors: Julie J. Brown, Young M. Lee, Rajiv Ramanasankaran, Sastry KM Malladi, Michael Tenbrock, Levent Tinaz, Samuel A. Girard, David S. Elario, Juliet A. Pagliaro Herman, Miguel Galvez, Trent M. Swanson, John F. Kuchler, Deepak Budhiraja, Daniela M. Natali, Josip Lazarevski, Scott Deering, Gary W. Gavin, Kristen Sheppard-Guzelaydin, James Young, Prashanthi Sudhakar, Kaleb Luedtke, Karl F. Reichenberger, Wenwen Zhao, Adam R. Grabowski, Lauren C. Dern, Nicole A. Madison, Dana S. Petersen, Nevin L. Forry, Pedriant Pena, Ghassan R. Hamoudeh, Ryan G. Danielson
  • Publication number: 20240345560
    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.
    Type: Application
    Filed: April 11, 2024
    Publication date: October 17, 2024
    Inventors: Julie J. Brown, Young M. Lee, Rajiv Ramanasankaran, Sastry KM Malladi, Michael Tenbrock, Levent Tinaz, Samuel A. Girard, David S. Elario, Juliet A. Pagliaro Herman, Miguel Galvez, Trent M. Swanson, John F. Kuchler, Deepak Budhiraja, Daniela M. Natali, Josip Lazarevski, Scott Deering, Gary W. Gavin, Kristen Sheppard-Guzelaydin, James Young, Prashanthi Sudhakar, Kaleb Luedtke, Karl F. Reichenberger, Wenwen Zhao, Adam R. Grabowski, Lauren C. Dern, Nicole A. Madison, Dana S. Petersen, Nevin L. Forry, Pedriant Pena, Ghassan R. Hamoudeh, Ryan G. Danielson
  • Publication number: 20240346459
    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.
    Type: Application
    Filed: April 11, 2024
    Publication date: October 17, 2024
    Inventors: Julie J. Brown, Young M. Lee, Rajiv Ramanasankaran, Sastry KM Malladi, Michael Tenbrock, Levent Tinaz, Samuel A. Girard, David S. Elario, Juliet A. Pagliaro Herman, Miguel Galvez, Trent M. Swanson, John F. Kuchler, Deepak Budhiraja, Daniela M. Natali, Josip Lazarevski, Scott Deering, Gary W. Gavin, Kristen Sheppard-Guzelaydin, James Young, Prashanthi Sudhakar, Kaleb Luedtke, Karl F. Reichenberger, Wenwen Zhao, Adam R. Grabowski, Lauren C. Dern, Nicole A. Madison, Dana S. Petersen, Nevin L. Forry, Pedriant Pena, Ghassan R. Hamoudeh, Ryan G. Danielson
  • Publication number: 20240346458
    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.
    Type: Application
    Filed: April 11, 2024
    Publication date: October 17, 2024
    Inventors: Julie J. Brown, Young M. Lee, Rajiv Ramanasankaran, Sastry KM Malladi, Michael Tenbrock, Levent Tinaz, Samuel A. Girard, David S. Elario, Juliet A. Pagliaro Herman, Miguel Galvez, Trent M. Swanson, John F. Kuchler, Deepak Budhiraja, Daniela M. Natali, Josip Lazarevski, Scott Deering, Gary W. Gavin, Kristen Sheppard-Guzelaydin, James Young, Prashanthi Sudhakar, Kaleb Luedtke, Karl F. Reichenberger, Wenwen Zhao, Adam R. Grabowski, Lauren C. Dern, Nicole A. Madison, Dana S. Petersen, Nevin L. Forry, Pedriant Pena, Ghassan R. Hamoudeh, Ryan G. Danielson
  • Publication number: 20240345554
    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.
    Type: Application
    Filed: January 22, 2024
    Publication date: October 17, 2024
    Inventors: Julie J. Brown, Young M. Lee, Rajiv Ramanasankaran, Sastry KM Malladi, Michael Tenbrock, Levent Tinaz, Samuel A. Girard, David S. Elario, Juliet A. Pagliaro Herman, Miguel Galvez, Trent M. Swanson, John F. Kuchler, Deepak Budhiraja, Daniela M. Natali, Josip Lazarevski, Scott Deering, Gary W. Gavin, Kristen Sheppard-Guzelaydin, James Young, Prashanthi Sudhakar, Kaleb Luedtke, Karl F. Reichenberger, Wenwen Zhao, Adam R. Grabowski, Lauren C. Dern, Nicole A. Madison, Dana S. Petersen, Nevin L. Forry, Pedriant Pena, Ghassan R. Hamoudeh, Ryan G. Danielson
  • Publication number: 20240346060
    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.
    Type: Application
    Filed: April 11, 2024
    Publication date: October 17, 2024
    Inventors: Julie J. Brown, Young M. Lee, Rajiv Ramanasankaran, Sastry KM Malladi, Michael Tenbrock, Levent Tinaz, Samuel A. Girard, David S. Elario, Juliet A. Pagliaro Herman, Miguel Galvez, Trent M. Swanson, John F. Kuchler, Deepak Budhiraja, Daniela M. Natali, Josip Lazarevski, Scott Deering, Gary W. Gavin, Kristen Sheppard-Guzelaydin, James Young, Prashanthi Sudhakar, Kaleb Luedtke, Karl F. Reichenberger, Wenwen Zhao, Adam R. Grabowski, Lauren C. Dern, Nicole A. Madison, Dana S. Petersen, Nevin L. Forry, Pedriant Pena, Ghassan R. Hamoudeh, Ryan G. Danielson
  • Publication number: 20240346036
    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.
    Type: Application
    Filed: January 22, 2024
    Publication date: October 17, 2024
    Inventors: Julie J. Brown, Young M. Lee, Rajiv Ramanasankaran, Sastry KM Malladi, Michael Tenbrock, Levent Tinaz, Samuel A. Girard, David S. Elario, Juliet A. Pagliaro Herman, Miguel Galvez, Trent M. Swanson, John F. Kuchler, Deepak Budhiraja, Daniela M. Natali, Josip Lazarevski, Scott Deering, Gary W. Gavin, Kristen Sheppard-Guzelaydin, James Young, Prashanthi Sudhakar, Kaleb Luedtke, Karl F. Reichenberger, Wenwen Zhao, Adam R. Grabowski, Lauren C. Dern, Nicole A. Madison, Dana S. Petersen, Nevin L. Forry, Pedriant Pena, Ghassan R. Hamoudeh, Ryan G. Danielson
  • Publication number: 20240346311
    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.
    Type: Application
    Filed: April 11, 2024
    Publication date: October 17, 2024
    Inventors: Julie J. Brown, Young M. Lee, Rajiv Ramanasankaran, Sastry KM Malladi, Michael Tenbrock, Levent Tinaz, Samuel A. Girard, David S. Elario, Juliet A. Pagliaro Herman, Miguel Galvez, Trent M. Swanson, John F. Kuchler, Deepak Budhiraja, Daniela M. Natali, Josip Lazarevski, Scott Deering, Gary W. Gavin, Kristen Sheppard-Guzelaydin, James Young, Prashanthi Sudhakar, Kaleb Luedtke, Karl F. Reichenberger, Wenwen Zhao, Adam R. Grabowski, Lauren C. Dern, Nicole A. Madison, Dana S. Petersen, Nevin L. Forry, Pedriant Pena, Ghassan R. Hamoudeh, Ryan G. Danielson