The various implementations described herein include methods, devices, and systems for monitoring activity in a home environment. In one aspect, a method performed at a voice-assistant device includes: while operating in an assistant mode, receiving an occupant command to operate in a monitoring mode; in response to the command, transitioning to operating in the monitoring mode; while operating in the monitoring mode, detecting a sound; obtaining a determination as to whether the sound meets one or more monitoring criteria; and in accordance with a determination that the sound meets the one or more monitoring criteria, generating an alert or notification.

The various implementations described herein include methods, devices, and systems for monitoring activity in a home environment. In one aspect, a method performed at a voice-assistant device includes: while operating in an assistant mode, receiving an occupant command to operate in a monitoring mode; in response to the command, transitioning to operating in the monitoring mode; while operating in the monitoring mode, detecting a sound; obtaining a determination as to whether the sound meets one or more monitoring criteria; and in accordance with a determination that the sound meets the one or more monitoring criteria, generating an alert or notification.

The invention relates to a method (20) for functional classification of luminaires (101a-d), the luminaires (101a-d) being arranged as a grid (100) of a plurality of luminaires (101a-d), each of the luminaires (101a-d) comprising at least two different sensors (103, 105, 107), preferably at least two of a light sensor (103), an acoustic sensor (105) and/or a motion sensor (107); the method (20) comprising the steps of: supplying (21) output signals of said sensors (103, 105, 107) to a controller (109), preferably wirelessly forwarding (23) sensor information signals (130) including timestamps and luminaire IDs to a central database (403), correlating (25) the sensor information signals (130) over a defined period of time, and generating (27) functional classification information based on the correlations found, wherein the functional classification information indicates a likelihood function of a certain usage of each luminaire, out of a given set of usage functions.

The invention relates to a method (20) for functional classification of luminaires (101a-d), the luminaires (101a-d) being arranged as a grid (100) of a plurality of luminaires (101a-d), each of the luminaires (101a-d) comprising at least two different sensors (103, 105, 107), preferably at least two of a light sensor (103), an acoustic sensor (105) and/or a motion sensor (107); the method (20) comprising the steps of: supplying (21) output signals of said sensors (103, 105, 107) to a controller (109), preferably wirelessly forwarding (23) sensor information signals (130) including timestamps and luminaire IDs to a central database (403), correlating (25) the sensor information signals (130) over a defined period of time, and generating (27) functional classification information based on the correlations found, wherein the functional classification information indicates a likelihood function of a certain usage of each luminaire, out of a given set of usage functions.

Apparatus and methods for deployment of fixtures. The apparatus may include a system for controlling deployed fixtures. The system may receive user commands different devices in different formats. The fixtures may be independently addressable. The fixtures may be magnetically supported by a fixture support. A brace may join two or more fixture supports without reducing space available to support fixtures. The brace may join a fixture support to a fixture support accessory. An accessory may include a variable-angle junction. The fixture may include articulating joints for controlling the direction of a beam. The fixture may include a lens having an electrically controllable beam spread angle. The fixture may be stowable in the fixture support. The fixture may be slidable along a cord to adjust a height of the fixture. The fixture may include an extendable ring. The system may coordinate motions of the fixtures to follow a target. The fixture may include an elongated board. The elongated board may include a non-polar power socket.

Apparatus and methods for deployment of fixtures. The apparatus may include a system for controlling deployed fixtures. The system may receive user commands different devices in different formats. The fixtures may be independently addressable. The fixtures may be magnetically supported by a fixture support. A brace may join two or more fixture supports without reducing space available to support fixtures. The brace may join a fixture support to a fixture support accessory. An accessory may include a variable-angle junction. The fixture may include articulating joints for controlling the direction of a beam. The fixture may include a lens having an electrically controllable beam spread angle. The fixture may be stowable in the fixture support. The fixture may be slidable along a cord to adjust a height of the fixture. The fixture may include an extendable ring. The system may coordinate motions of the fixtures to follow a target. The fixture may include an elongated board. The elongated board may include a non-polar power socket.

Technology for use by a human user in a viewing environment that includes a plurality of Internet of Things (IoT) light sources. Responsive to a voice command from a human user, machine logic determines which Internet of Things (IoT) light sources (for example, fixed brightness lamps, adjustable brightness lamps, windows with adjustable covers or shades) are causing glare problem by simulating a voice command throughout the entirety of a viewing environment. Once the problem light source(s) are determined, then the lighting is automatically adjusted to fix the glare problem.

Technology for use by a human user in a viewing environment that includes a plurality of Internet of Things (IoT) light sources. Responsive to a voice command from a human user, machine logic determines which Internet of Things (IoT) light sources (for example, fixed brightness lamps, adjustable brightness lamps, windows with adjustable covers or shades) are causing glare problem by simulating a voice command throughout the entirety of a viewing environment. Once the problem light source(s) are determined, then the lighting is automatically adjusted to fix the glare problem.

The various implementations described herein include methods, devices, and systems for monitoring activity in a home environment. In one aspect, a method performed at a voice-assistant device includes: transitioning to operating in a second mode from a first mode; while operating in the second mode, detecting a sound; obtaining a determination as to whether the sound meets one or more monitoring criteria; and in accordance with a determination that the sound meets the one or more monitoring criteria, generating an alert or notification.

The various implementations described herein include methods, devices, and systems for monitoring activity in a home environment. In one aspect, a method performed at a voice-assistant device includes: transitioning to operating in a second mode from a first mode; while operating in the second mode, detecting a sound; obtaining a determination as to whether the sound meets one or more monitoring criteria; and in accordance with a determination that the sound meets the one or more monitoring criteria, generating an alert or notification.