Honeywell International Inc.

Ademco Inc.

Zdenek Schindler

Jakub Malaník

Jiri Rojicek

Girija Parthasarathy

Petr Stluka

Marek Sikora

Wendy Foslien Graber

Eva Jerhotova

Tomás Tvrdon

Frank P DiMartino, Jr

Embodiments of the disclosure provide for determination and/or notifying of when an asset requires maintenance. Such embodiments enable outputting notifications in circumstances where tracked data for operations of an asset indicate or are predicted to violate particular thresholds. Some embodiments receive a feedback data set for an asset, identify a command data set for the asset, determine a delay value based at least in part on the feedback data set and the command data set, determine a command-feedback difference value based at least in part on the feedback data set and the command data set, and output a degradation indicator based at least in part on the delay value and the command-feedback difference value.

Apparatuses, computer-implemented methods, and computer program products for improved asset degradation monitoring and prediction

Methods, apparatuses, and computer program products are disclosed for performing air quality maintenance. An example method include receiving an air quality dataset and generating a quality tendency projection based upon the air quality dataset that includes a quality rate of change. In an instance in which the quality tendency projection exceeds a prediction threshold and the quality rate of change exceeds a pollutant rate increase threshold, the method performs performing air degradation analysis. In an instance in which the quality tendency projection exceeds a warning threshold and the quality rate of change exceeds a pollutant rate decrease threshold, the method performs ventilation analysis.

Apparatuses and methods for air quality maintenance by ventilation based on pollutant forecast

A hydronic heating system that may depend on pressure in the system for smooth operation. The pressure may be monitored. Pressure in the system may indicate health of the heating system. Certain pressures or variations of pressures may indicate one or more conditions in the system which may be good or adverse. An example of an adverse condition may be leakage of fluid from the system. Analyzes of pressures detected in the heating system may be performed by a computer programmed to indicate conditions of the system that are reflected by the detected pressures.

Evaluation of heating liquid pressure drops in a hydronic heating system

A computer implemented method optimizes a utility plant having multiple devices to convert input energy into output energy for a building. The method includes dividing a utility plant scheduling interval into several control intervals and for each control interval, obtaining a difference between a desired and a measured in-building condition controlled by output power from the utility plant, obtaining current values of multiple factors that influence operation of the utility plant, determining a new power demand of the building expected to decrease the difference, and finding set points for the multiple devices that satisfy the new power demand, take into account response times of the devices and their capacities, and optimize utility plant operation costs.

Allocation of energy production changes to meet demand changes

A computer implemented method includes providing information related to wind speed and direction prediction to a wind turbine energy prediction module, providing wind energy production prediction information to a resource allocation engine, and combining the wind energy production prediction information with information about non-renewable energy resources to provide an output identifying energy production resources to use for optimal load servicing.

Energy resource allocation including renewable energy sources

One embodiment of the application provides a method of forecasting utility demand of a utility consuming entity for a future time period. The method includes: selecting a utility demand matrix from a set of utility demand matrixes as a function of a future date, wherein the set of utility demand matrixes are classified by type-of-day, and representing a relation of past utility demand of the entity to time-in-day interval and outdoor temperature in the vicinity of the entity during the type-of-day; identifying a utility demand element from the utility demand matrix as a function of a future time-in-day and a known factor (e.g., future outdoor temperature) thereof; and generating a utility demand forecast of the entity for the future time period as a function of the identified utility demand element.

Utility demand forecasting using utility demand matrix

Utility demand is continuously monitored and monitoring data is aggregated and organized. The results are presented visually as a Utility Demand Footprint, referred to herein as a UDF. A UDF characterizes the utility demand in relation to selected influencing factors over a selected time period and over selected time intervals within the time period. In a preferred embodiment, the UDF is generated using a computer program and includes color mapping for simplifying analysis of the information displayed in the UDF. The footprint generation may be performed for a particular time period in which the demand essentially keeps its character (e.g., summer) or may be periodically updated (e.g., every day, every hour, etc.) to capture the latest changes.

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Prague, Czechia

Zdenek Schindler