Sensors for Training Data Acquisition in an Intelligent Electronic Oven

A method for training a machine learning system for an electronic oven comprising:

• applying an application of energy to a heating chamber of the electronic oven from an energy source via an injection port in the heating chamber;
• adjusting a distribution of the application of energy in the heating chamber using a control system;
• sensing the distribution of the application of energy in the heating chamber using a set of radio frequency (RF) responsive sensors, wherein the set of RF responsive sensors are:
• (i) located in the heating chamber;
• creating a set of training data for the machine learning system using data from each RF responsive sensor in the set of RF responsive sensors;
• and
• training the machine learning system using the set of training data.

A non-transitory computer-readable medium storing instructions to enable an electronic oven to execute a method for training a machine learning system for the electronic oven, the method comprising:

• applying an application of energy to a heating chamber of the electronic oven from an energy source via an injection port in the heating chamber;
• adjusting a distribution of the application of energy in the heating chamber using a control system;
• sensing the distribution of the application of energy in the heating chamber using a set of radio frequency (RF) responsive sensors, wherein the set of RF responsive sensors are:
• (i) located in the heating chamber;
• and (ii) include at least two elements;
• creating a set of training data for the machine learning system using data from each RF responsive sensor in the set of RF responsive sensors;
• and
• training the machine learning system using the set of training data.

An electronic oven comprising:

• a heating chamber;
• an energy source coupled to an injection port in the heating chamber for introducing an application of energy into the heating chamber;
• a control system to adjust a distribution of the application of energy in the heating chamber;
• and
• a set of light emitting diodes;
• a set of antennas, wherein each antenna in the set of antennas is electrically coupled to at least one light emitting diode in the set of light emitting diodes;
• and
• a visible light camera with a view of the set of light emitting diodes
• wherein the control system includes a machine learning system;
• wherein the control system measures the distribution of the application of energy in the chamber using the visible light camera and the set of light emitting diodes;
• wherein the control system uses data from the set of light emitting diodes as captured by the visible light camera to create a set of training data;
• and
• wherein the machine learning system is trained using the set of training data.