Abstract: Detection and identification of auditory events in distributed lighting networks is provided. Lighting fixtures or other devices in a distributed lighting network can incorporate an audio sensor (e.g., a microphone) through which auditory events (e.g., air leaks in compressed air systems, high noise events, shots fired, clapping, voice commands, etc.) are detected and measured. Through machine learning (e.g., a convolutional neural network), a type of auditory event can be identified, and action can be taken based on the type of the auditory event, such as to provide notification, alert nearby users, log events, provide sound cancelation, and so on. In some examples, the auditory event can be localized using multiple audio sensors. In some examples, a learning algorithm can fuse information from multiple sensor inputs, such as temperature sensors, cameras, occupancy sensors, light sensors, and so on.

Abstract: The present disclosure relates to determining one or more of a space occupancy score, space energy score, and space efficiency score for a collection of lighting endpoints in a lighting network. The space occupancy score is indicative of how effective the occupancy groups are configured for a given space or the utilization level for a space. The space energy score is indicative of how much energy the collection of lighting endpoints use or will likely use based on their configurations, actual use, or a combination thereof. The space efficiency score is indicative of the overall efficiency associated with the collection of lighting endpoints based on both occupancy and energy related metrics.

Abstract: The present disclosure relates to determining one or more of a space occupancy score, space energy score, and space efficiency score for a collection of lighting endpoints in a lighting network. The space occupancy score is indicative of how effective the occupancy groups are configured for a given space or the utilization level for a space. The space energy score is indicative of how much energy the collection of lighting endpoints use or will likely use based on their configurations, actual use, or a combination thereof. The space efficiency score is indicative of the overall efficiency associated with the collection of lighting endpoints based on both occupancy and energy related metrics.