Method, apparatus and system for passive infrared sensor framework

A method comprising:

• detecting, with a passive infrared sensor (PIR), levels of infrared radiation in a field of view (FOV) of the PIR;
• generating a signal based on the levels of infrared radiation detected with the PIR, the signal having values used to detect a change in the levels of infrared radiation as detected with the PIR;
• extracting a local feature from a sample of the signal by tracking an absolute deviation of the sample of the signal relative to a threshold predetermined to approximate a non-environmental radiation source, wherein the local feature indicates a first probability that a non-environmental radiation source in the FOV caused the change in the detected levels of infrared radiation;
• extracting a global feature from the sample of the signal by a product of a feature parameter determined through training on a dataset to achieve a slow total variation and a rolling average value updated after every frame of the PIR, wherein the global feature indicates a second probability that an environmental radiation source caused the change in the detected levels of infrared radiation;
• determining a score based on the local feature and the global feature;
• and
• determining that a non-environmental radiation source has been detected in the FOV based on the score.

A passive infrared (PIR) sensor device, comprising:

• a plurality of radiation sensitive elements that detect radiation levels in a field of view (FOV) and generate charges based on the radiation levels;
• a circuit that receives the generated charges and generates a single output signal based on the charges;
• and
• a processor that receives the signal and extracts a local feature from a sample of the signal by tracking an absolute deviation of the sample of the signal relative to a threshold predetermined to approximate a non-environmental radiation source and a global feature from the sample of the signal by a product of a feature parameter determined through training on a dataset to achieve a slow total variation and a rolling average value updated after every frame of the PIR, the local feature indicating a first probability that a non-environmental radiation source in the FOV caused a change in the detected radiation levels and the global feature indicating a second probability that an environmental radiation source in the FOV caused the change in the detected radiation levels,
• wherein the processor is configured
• to determine a score based on the global feature and the local feature, and
• to determine that a non-environmental radiation source has been detected in the FOV based on the score.

A system, comprising:

• a network;
• a controller configured to transmit and receive data through the network;
• and
• at least one passive infrared (PIR) sensor device configured to transmit data to the controller through the network, the PIR sensor device comprising:
• a plurality of radiation sensitive elements that detect radiation levels in a field of view (FOV) and generate charges based on the detected radiation levels;
• a circuit that receives the generated charges and generates a single output signal based on the charges;
• and
• a processor that receives the signal and extracts a local feature from a sample of the signal by tracking an absolute deviation of the sample of the signal relative to a threshold predetermined to approximate a non-environmental radiation source and a global feature from the sample of the signal by a product of a feature parameter determined through training on a dataset to achieve a slow total variation and a rolling average value updated after every frame of the PIR, the local feature indicating a first probability that a non-environmental radiation source in the FOV caused the change in the detected radiation levels and the global feature indicating a second probability that an environmental radiation source caused the change in the detected radiation levels, wherein the processor is configured
• to determine a score based on the global feature and the local feature and
• to determine that a non-environmental radiation source has been detected in the FOV based on the score.