The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Mar. 17, 2026

Filed:

Jun. 01, 2025
Applicant:

Togal.ai Inc., Miami, FL (US);

Inventors:

Patrick E Murphy, Miami, FL (US);

Johnny Maghzal, Miami, FL (US);

Patrick Hughes, Miami, FL (US);

Thomas Patrick Murphy, Miami, FL (US);

Assignee:

Togal.AI, Inc., Miami, FL (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G05B 13/02 (2006.01);
U.S. Cl.
CPC ...
G05B 13/027 (2013.01);
Abstract

Methods, systems, and apparatus for automated building maintenance management using a digital representation of a physical building. A controller, operating an AI engine one or both of a GAN engine and a ViT, receives a design plan comprising dynamic components representing as-built building elements. Metadata, including historical maintenance logs, component specifications from a component database, sensor data from a Building Management System (BMS), and environmental conditions, is associated with the dynamic components. The controller detects maintenance requirements for the dynamic components based on sensor anomalies, historical failure patterns, metadata, and user inputs, determines interrelations between the dynamic components, and assigns priority levels to the maintenance tasks. A maintenance execution plan is generated, incorporating task prioritization, labor allocation, material requirements, and execution timelines. The system dynamically updates maintenance logs, the design plan, and metadata while optimizing resource utilization and predicting failures through AI-driven analysis.


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