Abstract: A method for detecting object paths in a workplace, at a sensor block, includes responsive to detecting absence of motion, capturing an initial sequence of frames at a baseline frame rate at a camera and for each frame in the initial sequence of frames: detecting an initial constellation of objects; and transmitting a container representing the initial constellation of objects to a computer system. The method further includes, responsive to detecting motion: capturing a frame at the baseline frame rate at the camera; detecting a first constellation of objects, including a set of humans, in the frame; calculating a quantity of humans; transitioning the camera to a first frame rate; capturing a second sequence of frames at the first frame rate; detecting a second constellation of objects in the second sequence of frames; deriving a set of object paths; and transmitting the set of object paths to the computer system.

Abstract: A method includes: accessing a floorplan representing the floorspace; and extracting from the floorplan a set of floorplan features representing areas of interest in the floorspace. The method also includes, calculating a set of target locations relative to the floorplan that, when occupied by the set of sensor blocks: locate the areas of interest in the floorspace within fields of view of the set sensor blocks; and yield a minimum overlap in fields of view of adjacent sensor blocks in the set of sensor blocks. The method further includes, for each sensor block in the sensor blocks installed over the floorspace: receiving, from the sensor block, an image of the floorspace; based on overlaps in the image with images from other sensor blocks in sensor blocks, estimating an installed location of the sensor block; and mapping the sensor block to a target location in the set of target locations.

Abstract: A method including, accessing an occupancy of the workspace. The method also includes, in response to the occupancy status indicating vacancy: at a first time, recording a first image and a second image of the workspace, the first image and the second image characterized by a first resolution; and executing an arrival detection model based on the first and second image. The method further includes, in response to detecting arrival at the workspace: at a third time, recording a third image of the workspace, the third image characterized by a second resolution greater than the first resolution; and executing an occupancy detection model based on the third image. The method additionally includes, in response to detecting occupancy of the workspace: updating the occupancy status to indicate occupancy; and transmitting the occupancy status to a remote scheduling system.

Abstract: A method for detecting object paths in a workplace, at a sensor block, includes responsive to detecting absence of motion, capturing an initial sequence of frames at a baseline frame rate at a camera and for each frame in the initial sequence of frames: detecting an initial constellation of objects; and transmitting a container representing the initial constellation of objects to a computer system. The method further includes, responsive to detecting motion: capturing a frame at the baseline frame rate at the camera; detecting a first constellation of objects, including a set of humans, in the frame; calculating a quantity of humans; transitioning the camera to a first frame rate; capturing a second sequence of frames at the first frame rate; detecting a second constellation of objects in the second sequence of frames; deriving a set of object paths; and transmitting the set of object paths to the computer system.

Abstract: A method including, accessing an occupancy of the workspace. The method also includes, in response to the occupancy status indicating vacancy: at a first time, recording a first image and a second image of the workspace, the first image and the second image characterized by a first resolution; and executing an arrival detection model based on the first and second image. The method further includes, in response to detecting arrival at the workspace: at a third time, recording a third image of the workspace, the third image characterized by a second resolution greater than the first resolution; and executing an occupancy detection model based on the third image. The method additionally includes, in response to detecting occupancy of the workspace: updating the occupancy status to indicate occupancy; and transmitting the occupancy status to a remote scheduling system.

Abstract: A method includes: accessing a floorplan representing the floorspace; and extracting from the floorplan a set of floorplan features representing areas of interest in the floorspace. The method also includes, calculating a set of target locations relative to the floorplan that, when occupied by the set of sensor blocks: locate the areas of interest in the floorspace within fields of view of the set sensor blocks; and yield a minimum overlap in fields of view of adjacent sensor blocks in the set of sensor blocks. The method further includes, for each sensor block in the sensor blocks installed over the floorspace: receiving, from the sensor block, an image of the floorspace; based on overlaps in the image with images from other sensor blocks in sensor blocks, estimating an installed location of the sensor block; and mapping the sensor block to a target location in the set of target locations.

Abstract: One variation of a method includes: detecting a set of radio signals transmitted between a set of computing devices and a set of access points in the space; for each radio signal in the set of radio signals, extracting a pair of unique identifiers representing an initial computing device and an initial access point from the radio signal; storing the pair of unique identifiers in a set of containers; accessing a known position of the wireless sensor; accessing a signal transmission range of an access point based on the set of containers; deriving a signal strength of a radio signal based on the known position and the signal transmission range; in response to the signal strength exceeding a threshold signal strength, deriving a location unit occupied by the access point; and aggregating the location unit into a localization map representing locations of the set of access points in the space.

Abstract: One variation of a method for monitoring occupancy in a work area includes, at a sensor block: transitioning from an inactive state into an active state when an output of a motion sensor indicates motion in a work area; during a scan cycle in the active state, recording an image through an optical sensor at a time, detecting a set of humans in the image, detecting a second set of human effects in the image, predicting a second set of humans occupying but absent the work area based on the second set of human effects, and estimating a total occupancy in the work area at the time based on the set of humans and the second set of humans; and transmitting the total occupancy to a remote computer system for update of a scheduler for the work area.

Abstract: One variation of a method includes, at a sensor block: detecting a set of objects within a region-of-interest in a frame; detecting an object type of each object; detecting a location of each object within the region-of-interest; and storing object types and object locations of the set of objects in a set of containers. The method further includes, at the computer system: accessing a database of commissioning images; extracting a commissioning image annotated with boundaries from the database; initializing a visualization layer of a set of pixels representing the region-of-interest; and calculating a frequency of presence of the object type intersecting each pixel based on the set of containers; calculating a color value for each pixel based on the frequency of presence; and assigning the color value to each pixel in the visualization layer; and generating a heatmap of the region-of-interest based on the visualization layer and the commissioning image.

Abstract: A method includes: recording an image at a sensor block, the sensor block; detecting a set of objects in the image based on an object classification model; generating a feature vector for the image based on the set of objects; accessing a workstation template for the work area, the workstation template defining a set of default objects for each workstation in the work area; identifying a subset of objects comprising an intersection of the set of default objects and the set of objects; removing the subset of objects from the feature vector; accessing an occupancy template for the work area, the occupancy template defining a set of significant objects; classifying the workstation as occupied based on the feature vector and the set of significant objects; and rendering a representation of the workstation at a work area interface, the representation indicating occupancy of the workstation.

Abstract: One variation of a method for monitoring occupancy in a work area includes, at a sensor block: transitioning from an inactive state into an active state when an output of a motion sensor indicates motion in a work area; during a scan cycle in the active state, recording an image through an optical sensor at a time, detecting a set of humans in the image, detecting a second set of human effects in the image, predicting a second set of humans occupying but absent the work area based on the second set of human effects, and estimating a total occupancy in the work area at the time based on the set of humans and the second set of humans; and transmitting the total occupancy to a remote computer system for update of a scheduler for the work area.

Abstract: One variation of a method for monitoring occupancy in a work area includes, at a sensor block: transitioning from an inactive state into an active state when an output of a motion sensor indicates motion in a work area; during a scan cycle in the active state, recording an image through an optical sensor at a time, detecting a set of humans in the image, detecting a second set of human effects in the image, predicting a second set of humans occupying but absent the work area based on the second set of human effects, and estimating a total occupancy in the work area at the time based on the set of humans and the second set of humans; and transmitting the total occupancy to a remote computer system for update of a scheduler for the work area.

Abstract: One variation of a method for detecting and visualizing objects within a space includes: retrieving a map of the space annotated with known locations of target anchor objects and regions in the space; accessing a set of images annotated with object types and locations of objects captured by a set of sensor blocks; projecting the set of images onto the map to form a visualization representing objects in the space based on known locations of the set of sensor blocks; isolating a target anchor object at a known location in a region of the visualization; detecting a mutable object at a location in the region; calculating an offset distance between the location and the known location; and, in response to the offset distance exceeding an offset distance threshold, highlighting the mutable object in the visualization as a deviation; and generating a notification to investigate the mutable object in the region.

Abstract: One variation of a method includes, at a sensor block: detecting a set of objects within a region-of-interest in a frame; detecting an object type of each object; detecting a location of each object within the region-of-interest; and storing object types and object locations of the set of objects in a set of containers. The method further includes, at the computer system: accessing a database of commissioning images; extracting a commissioning image annotated with boundaries from the database; initializing a visualization layer of a set of pixels representing the region-of-interest; and calculating a frequency of presence of the object type intersecting each pixel based on the set of containers; calculating a color value for each pixel based on the frequency of presence; and assigning the color value to each pixel in the visualization layer; and generating a heatmap of the region-of-interest based on the visualization layer and the commissioning image.

Abstract: One variation of a method includes, at a sensor block: detecting a set of objects within a region-of-interest in a frame; detecting an object type of each object; detecting a location of each object within the region-of-interest; and storing object types and object locations of the set of objects in a set of containers. The method further includes, at the computer system: accessing a database of commissioning images; extracting a commissioning image annotated with boundaries from the database; initializing a visualization layer of a set of pixels representing the region-of-interest; and calculating a frequency of presence of the object type intersecting each pixel based on the set of containers; calculating a color value for each pixel based on the frequency of presence; and assigning the color value to each pixel in the visualization layer; and generating a heatmap of the region-of-interest based on the visualization layer and the commissioning image.

Abstract: One variation of a method for monitoring occupancy in a work area includes, at a sensor block: transitioning from an inactive state into an active state when an output of a motion sensor indicates motion in a work area; during a scan cycle in the active state, recording an image through an optical sensor at a time, detecting a set of humans in the image, detecting a second set of human effects in the image, predicting a second set of humans occupying but absent the work area based on the second set of human effects, and estimating a total occupancy in the work area at the time based on the set of humans and the second set of humans; and transmitting the total occupancy to a remote computer system for update of a scheduler for the work area.

Abstract: A method includes: recording an image at a sensor block, the sensor block; detecting a set of objects in the image based on an object classification model; generating a feature vector for the image based on the set of objects; accessing a workstation template for the work area, the workstation template defining a set of default objects for each workstation in the work area; identifying a subset of objects comprising an intersection of the set of default objects and the set of objects; removing the subset of objects from the feature vector; accessing an occupancy template for the work area, the occupancy template defining a set of significant objects; classifying the workstation as occupied based on the feature vector and the set of significant objects; and rendering a representation of the workstation at a work area interface, the representation indicating occupancy of the workstation.

Abstract: A system for repeatably mounting an image sensor to a grid ceiling comprising: a mounting member defining an upper face; a set of magnets fixed to the upper face and characterized by a height greater than a protrusion distance of the outer surface of a ceiling tile of the grid ceiling below a grid segment of the grid ceiling; a detachable registration feature transiently coupled to the mounting member, configured to align with the grid ceiling while the set of magnetics are magnetically coupled to the grid ceiling, configured to adhere to the grid ceiling while the set of magnets are magnetically coupled to the grid ceiling, and configured to detach from the upper face and remain adhered to the grid ceiling in response to vertical displacement of the mounting member away from the grid ceiling.

Abstract: A method for detecting conditions within a space includes: accessing a corpus of object lists generated based on objects detected in images captured by a population of sensor blocks; compiling locations of a set of objects represented in the corpus of object lists into a map of the space based on known locations of the population of sensor blocks; accessing a nominal condition of the space defining a set of inclusion objects and a set of exclusion objects within a threshold distance of an anchor object type; and detecting the anchor object type in the map according to the nominal condition. The method further includes, in response to detecting an object within the threshold distance of the anchor object type in the map and deviating from the nominal condition: identifying the object as anomalous in the map; and generating a notification to investigate the object.

Abstract: A method includes: recording an image at a sensor block, the sensor block; detecting a set of objects in the image based on an object classification model; generating a feature vector for the image based on the set of objects; accessing a workstation template for the work area, the workstation template defining a set of default objects for each workstation in the work area; identifying a subset of objects comprising an intersection of the set of default objects and the set of objects; removing the subset of objects from the feature vector; accessing an occupancy template for the work area, the occupancy template defining a set of significant objects; classifying the workstation as occupied based on the feature vector and the set of significant objects; and rendering a representation of the workstation at a work area interface, the representation indicating occupancy of the workstation.