Abstract: Techniques are described herein for workspace occupancy estimation using presence sensor data and a predictive model. In various embodiments, spatial distributions of workspaces (340) and presence sensors (342) may be identified (402) in an open environment and used to generate (406) a surrogate model. The surrogate model may indicate which workspaces in the open environment are within sensor range of each presence sensor in the open environment. A plurality of simulated occupancy patterns may be applied across the surrogate model to generate a corresponding plurality of triggered sensor patterns. Based on the applying, a predictive model may be generated (410) for estimating occupancy among the plurality of workspaces in the open environment based on triggered sensor patterns. A real life triggered sensor pattern may then be applied (414) across the predictive model to estimate occupancy among the plurality of workspaces in the environment.

Abstract: The described implementations provided herein relate to systems, methods, and apparatuses for using a network of luminaires to perform distributed computation of sensor data to identify hardware and network anomalies. In some implementations, a method is set forth as including operations such as receiving, from a first luminaire (114, 128, 216), first sensor data (122, 124) in response to a stimulus (204) affecting a network of luminaires (110), and receiving, from a second luminaire (208) in the network of luminaires, second sensor data. The method can also include determining a correlation between the first sensor data and the second sensor data, and modifying a luminaire spatial-temporal model (222) based at least partially on the correlation.

Abstract: A lighting plan generator configured to generate a lighting plan comprising a map of locations of a plurality of light units located in a space, the lighting plan generator being configured to generate the lighting plan from overlapping images captured by light units in a space. Orientation sensor information from each light unit is also received from each light unit to provide light unit orientation. The overlapping images are combined by aligning or rotating the images, using the orientation sensor information, to form a blended image and based on spatial information (e.g. distance between fixtures, camera field of view, and ceiling height). A lighting plan is then generated comprising a map of locations of a plurality of light units in the space.

Abstract: Disclosed are a system and method for developing computational models of the behavior of a building's occupants using data acquired from sensor-equipped connected luminaires. The models are then used to develop an optimized evacuation plan for safe and timely egress of the occupants without requiring mock evaluation drills.