System, methods, and apparatuses for distributed detection of luminaire anomalies

A computing device, comprising:

• one or more processors;
• and
• memory connected to the one or more processors, the memory comprising instructions that, when executed by the one or more processors, cause the one or more processors to perform operations that include:
• receiving, from a first luminaire, first sensor data in response to a stimulus affecting a network of luminaires that the one or more processors are in communications with;
• receiving, from a second luminaire, second sensor data in the network of luminaires, wherein the second sensor data is generated by the second luminaire in response to the stimulus;
• determining a correlation between the first sensor data and the second sensor data;
• modifying a luminaire spatial-temporal model based at least partially on the correlation between the first sensor data and the second sensor data, wherein the luminaire spatial-temporal model is based on gradient distribution data for multiple types of sensors integrated into the network of luminaires, and the multiple types of sensors include at least a passive infrared sensor;
• receiving subsequent sensor data from the first luminaire or the second luminaire;
• and
• providing a signal to the first luminaire or the second luminaire based on a comparison of the subsequent sensor data to the modified luminaire spatial-temporal model.

A system, comprising:

• one or more processors;
• and
• memory configured to store instructions that, when executed by the one or more processors, cause the one or more processors to perform operations that include:
• generating first sensor data at the one or more processors, wherein the one or more processors are in communication with a network of luminaires;
• receiving second sensor data from a luminaire in the network of luminaires, wherein the second sensor data is generated by the luminaire;
• comparing the first sensor data and the second sensor data to a luminaire spatial-temporal model to identify a variance between the first sensor data and the luminaire spatial-temporal model or the second sensor data and the luminaire spatial-temporal model, wherein the luminaire spatial-temporal model is based on historical sensor data collected from adjacent luminaires in the network of luminaires and wherein the variance corresponds to a probabilistic metric;
• determining that the probabilistic metric satisfies a probabilistic threshold;
• and
• when the variance is identified, causing the one or more processors, or the luminaire, to operate to compensate for the variance, wherein the variance corresponds to a probabilistic metric.