Self-Aware and Informative Home Automation Systems

  • Systems and methods that help homeowners to visualize, program, understand and monitor their many automation and robotics systems
  • Enables residents to use augmented reality (AR) to visualize otherwise invisible programmed electrical or logical connections between home automation devices
  • Detects errors, failures or anomalies that occur during programming or system use

Abstract
The University of Central Florida invention comprises four complementary advantageous features that can help homeowners program, comprehend, and monitor increasingly complex home automation and robotics systems. The features include:

Systems and methods for using the home automation and home robotics systems to detect errors, failures, or anomalies in the components or operations of the systems, that is, to be self-aware.
Mechanisms for storing, updating, and conveying device-specific information embedded in, updated, and transmitted from individual devices.
Systems and methods to allow residents of a home to visualize otherwise invisible home automation and home robotics information such as device connections, dependencies, plans, pathways, signals, events, and errors, failures, or anomalies.
In particular, the visualization of otherwise invisible information associated with the first advantageous feature can be used to inform homeowners about multiple aspects of the detected errors, failures, or anomalies associated with the first advantageous feature. These same systems and methods can also be applied in other contexts, for example, at a workplace, in a vehicle, in a building, or around a city, and beyond.

Partnering Opportunity

The research team is seeking partners for licensing and/or research collaboration.

Contact Information

Name: John Miner

Email: John.Miner@ucf.edu

Phone: 407.882.1136