Tyco Fire + Security Gmbh

Johnson Controls Technology Company

Dana S Petersen

Karl F Reichenberger

Miguel Galvez

Young M Lee

Rajiv Ramanasankaran

Trent Mark Swanson

Adam R Grabowski

Gary W Gavin

Julie J Brown

John F Kuchler

James Young

Nicole A Madison

Juliet A Pagliaro Herman

David S Elario

Josip Lazarevski

Scott Deering

Daniela M Natali

Deepak Budhiraja

Levent Tinaz

Michael Tenbrock

Prashanthi Sudhakar

Kaleb Luedtke

Pedriant Pena

Lauren C Dern

Samuel A Girard

Ghassan R Hamoudeh

Wenwen Zhao

Kristen Sheppard-Guzelaydin

Nevin L Forry

Ryan G Danielson

Sastry Km Malladi

Joseph R Ribbich

Ryan J Bykowski

Sastry K M Malladi

John S Jilek

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. The method includes automatically initiating, by the processors, one or more actions to address the problem based on the information provided via the user interface.

Building management system with generative AI-based interactive service tool

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.

Building management system with generative AI-based automated flexible customer report generation and standardization

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.

Building management system with generative AI-based predictive maintenance

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.

Building management system with generative AI-based root cause prediction

Systems and methods for using occupant location in a building management system are provided. A plurality of wireless emitters are provided at various locations in a building. Each of the wireless emitters broadcasts a different emitter identifier. Mobile devices in the building run an application which causes the mobile devices to detect and report, to the building management system, an emitter identifier associated with a nearby wireless emitter. The building management system uses the reported emitter identifier to determine a building zone in which the mobile device is located. The building management system provides information to the mobile device based on the location of the mobile device in the building. In some embodiments, the information includes a user interface for monitoring and/or controlling the building zone in which the mobile device is located.

Systems and methods for detecting and using occupant location in a building management system

Growing community of inventors

Milwaukee, WI, United States of America

Dana S Petersen