Zoom video communications, inc. (20240329611). OPTIMIZING ENERGY EFFICIENCY ASSOCIATED WITH WORKSPACES IN A BUILDING simplified abstract

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OPTIMIZING ENERGY EFFICIENCY ASSOCIATED WITH WORKSPACES IN A BUILDING

Organization Name

zoom video communications, inc.

Inventor(s)

Jose Luis Espinosa, Jr. of Chattanoga TN (US)

Thanh Le Nguyen of Belle Chasse LA (US)

Andrew James Ruhland of Memphis TN (US)

OPTIMIZING ENERGY EFFICIENCY ASSOCIATED WITH WORKSPACES IN A BUILDING - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240329611 titled 'OPTIMIZING ENERGY EFFICIENCY ASSOCIATED WITH WORKSPACES IN A BUILDING

Simplified Explanation: The patent application discusses a system that uses machine learning to predict activity patterns in workspaces and adjust environmental conditions accordingly.

Key Features and Innovation:

  • Utilizes machine learning to forecast workspace activity patterns.
  • Generates control signals based on predicted activity patterns.
  • Adjusts environmental conditions in workspaces based on the generated control signals.

Potential Applications: This technology can be applied in office buildings, schools, hospitals, and other commercial spaces to optimize energy efficiency and create more comfortable environments for occupants.

Problems Solved:

  • Wastage of energy in unoccupied workspaces.
  • Inefficient control of environmental conditions in buildings.
  • Lack of predictive systems to adjust workspace settings based on activity patterns.

Benefits:

  • Reduced energy consumption.
  • Improved comfort for occupants.
  • Enhanced efficiency in managing workspace environments.

Commercial Applications: The technology can be used by building management companies, facility managers, and smart building solution providers to offer energy-efficient and comfortable workspaces to their clients.

Questions about the Technology: 1. How does the system learn and adapt to different workspace activity patterns? 2. What are the potential cost savings for building owners and occupants with the implementation of this technology?

Frequently Updated Research: Researchers are constantly exploring new algorithms and data sources to enhance the accuracy and efficiency of predicting workspace activity patterns and optimizing environmental conditions.


Original Abstract Submitted

some examples relate to optimizing energy efficiency associated with workspaces in a building. in one specific example, a system can execute a trained machine-learning model to generate a predicted activity pattern associated with a workspace in a building, the predicted activity pattern being a forecast of workspace activity associated with the workspace over a future time window. the system can, based on the predicted activity pattern, generate at least one control signal for at least one control system associated with the workspace. and the system can transmit the at least one control signal to the at least one control system, the at least one control system being configured to receive the at least one control signal and responsively adjust at least one environmental condition associated with the workspace from a first setting to a second setting.

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