The Travelers Indemnity Company

Carrier Corporation

Otis Elevator Company

Murat Yasar

Jeffrey Allen Leshuk

Teems E Lovett

Veronica Adetola

Marc Beasley

Mark E Cywilko

Jason R Vermes

Carolyn C Capshaw

Ryan J O'Connor

Nabeel A Syed

Kelly D Fisher

Brototi Paul

Jerrod K Bowman

Cathy J Miller

Sara M Nunez

Nikola Trcka

Soumalya Sarkar

Peter Liaskas

Kin Gwn Lore

Draguna Vrabie

Systems and methods for multivariate Artificial Intelligence (AI) smart cards are provided. An AI smart card may include, for example, pre-stored policy data that may be utilized as a portion of multivariate input by a suite of AI modules to formulate and analyze a claim of loss.

Systems and methods for multivariate artificial intelligence (AI) smart cards

Embodiments include techniques for developing a model framework for remote unit monitoring condition-based maintenance. The techniques include collecting data associated with unplanned service requests, and generating one or more models from the collected data. The techniques also include predicting unplanned service requests based at least in part on the one or more models, and transmitting an output of the prediction of the unplanned service request.

Model development framework for remote monitoring condition-based maintenance

A building detection model is applied to identify a footprint of a building based on a first dataset. The building characterization model is applied to identify one or more derived characteristics of the building based on the footprint. A building area is determined based on the footprint and at least one of the one or more derived characteristics of the building. A record is created including an indicator of a geographic area, the building area, and the one or more derived characteristics of the building. A processing request is generated based on the record. One or more derived characteristics of the building are compared with one or more corresponding values of property data from a third-party data source to identify a mismatch. A data accuracy verification request is output based on the mismatch.

Intelligent imagery

A system for managing transport refrigeration units () is provided. The system includes a storage device () to store transport parameters () associated with a transport refrigeration unit (). The storage device storing historical transport parameters () for other transport refrigeration units (). Also included is an equipment management system () coupled to the storage device, the equipment management system () including: a diagnostic module () to determine a condition of the transport refrigeration unit () in response to the transport parameters (); a predictive maintenance module () to determine a need for upcoming maintenance of the transport refrigeration unit () in response to the transport parameters (); and a remaining life module () to determine a remaining life of at least one component of the transport refrigeration unit () in response to the transport parameters ().

Automated diagnostics for transport refrigeration units

A system includes a processing system and memory system configured to apply a building detection model to identify a footprint of a building based on a first dataset. The building characterization model is applied to identify one or more derived characteristics of the building based on the footprint. A building area is determined based on the footprint and at least one of the one or more derived characteristics of the building. A record is created including an indicator of a geographic area, the building area, and the one or more derived characteristics of the building. A processing request is generated based on the record. One or more derived characteristics of the building are compared with one or more corresponding values of property data from a third-party data source to identify a mismatch. A data accuracy verification request is output based on the mismatch.

A cargo transport system includes a container for storing perishable products, and a control assembly for controlling an environment parameter. A sensor of the system is configured to measure the environment parameter. A detector of the system may be directly secured to the perishable products for measuring a product condition. A control module of the system is configured to receive signals from the sensor and the detector indicative of the measured environment parameter and product condition, process the signals, and send a command signal to the control assembly for adjusting the environment parameter.

Cargo transport system for perishable products

A condition monitoring system for performing a transformation of mixed elevator data is provided. The condition monitoring system includes a computer sub-system. The computer sub-system includes a memory storing transformation software and a processor coupled to the memory. The processor executes the transformation software to cause the condition monitoring system to acquire quantitative and qualitative information and transform the quantitative and qualitative information to produce transformed information. The processor executes the transformation software to further cause the condition monitoring system to execute analytics on the transformed information and generate predictions based on the analytics of the transformed information.

Elevator condition monitoring using heterogeneous sources

A system for monitoring goods within a distribution chain is provided. The system includes a storage device to store parameters associated with the goods of a distribution chain, at least one of the parameters being received from a transport refrigeration system. The storage device storing historical parameters for other goods. Also included is a parameter management system coupled to the storage device. The parameter management system including: a predictive module to determine predicted parameters; and a meshing module to determine output parameters by combining the predicted parameters and the parameters.

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West Hartford, CT, United States of America

Murat Yasar