Abstract: Techniques are disclosed for detecting an uncovered portion of a body of a person in a frame of video content. In an example, a first machine learning model of a computing system may output a first score for the frame based on a map that identifies a region of the frame associated with an uncovered body part type. Depending on a value of the first score, a second machine learning model that includes a neural network architecture may further analyze the frame to output a second score. The first score and second score may be merged to produce a third score for the frame. A plurality of scores may be determined, respectively, for frames of the video content, and a maximum score may be selected. The video content may be selected for presentation on a display for further evaluation based on the maximum score.

Abstract: A safety automation system for an occupiable structure includes a computing management system, a first detection device, and a second detection device. The management system includes a computer processor, and a computer readable storage medium configured to run embedded software, The first detection device is adapted to detect a hazard condition and output an associated hazard condition detected signal to the computing management system. The second detection device is adapted to detect the presence of an occupant in the occupiable structure and the occupant's proximity to the first detection device, and output an occupied signal to the computing management system. The computing management system adjusts the sensitivity of the first detection device based on occupancy and proximity of the occupant to the first detection device.

Abstract: Techniques are described for automating virtual placements in video content.

Abstract: Techniques are disclosed for detecting a type of prurient activity shown by a portion of video content. In an example, a machine learning model of a computer system may receive a second portion of video content, the machine learning model including a neural network that is trained to analyze a temporal dimension of the second portion. The machine learning model determines a score indicating a likelihood that the video content shows the type of prurient activity based in part on applying a three-dimensional filter to the second portion of the video content. The computer system then generates a video clip that includes at least the portion of the video content showing the type of prurient activity based on the score, and provides the video clip for display.

Abstract: Techniques are described for automating virtual placements in video content.

Abstract: A gas detection device comprising a membrane filter disposed between an electrochemical sensor and an environment exterior to the gas detection device.

Abstract: A safety automation system for an occupiable structure includes a computing management system, a first detection device, and a second detection device. The management system includes a computer processor, and a computer readable storage medium configured to run embedded software, The first detection device is adapted to detect a hazard condition and output an associated hazard condition detected signal to the computing management system. The second detection device is adapted to detect the presence of an occupant in the occupiable structure and the occupant's proximity to the first detection device, and output an occupied signal to the computing management system. The computing management system adjusts the sensitivity of the first detection device based on occupancy and proximity of the occupant to the first detection device.

Abstract: A safety automation system for an occupiable structure includes a computing management system including a computer processor, and a computer readable storage medium configured to run embedded software and cloud server software. A fire detection device of the automation system is adapted to detect a fire condition and output an associated fire condition detected signal to the computing management system. A condition deterrence device is configured to accept a wireless command signal from the computing management system associated with the fire condition detected signal and for actuating an appliance to at least reduce risk presented by the condition.

Abstract: An illustrative example monitoring system includes a carbon monoxide sensor configured to detect carbon monoxide within an area, a heater situated near the carbon monoxide sensor to regulate a temperature of the carbon monoxide sensor, an ambient temperature sensor configured to provide an indication of an ambient temperature in the area, an occupancy sensor configured to provide an indication whether the area is occupied by at least one individual and a controller. The controller is configured to determine whether the ambient temperature in the area is below a threshold based on the indication from the ambient temperature sensor, determine whether the area is occupied by at least one individual based on the indication from the occupancy sensor, and activate the heater when the ambient temperature in the area is below the threshold and the area is occupied by at least one individual.

Abstract: An illustrative example monitoring system includes a carbon monoxide sensor configured to detect carbon monoxide within an area, a heater situated near the carbon monoxide sensor to regulate a temperature of the carbon monoxide sensor, an ambient temperature sensor configured to provide an indication of an ambient temperature in the area, an occupancy sensor configured to provide an indication whether the area is occupied by at least one individual and a controller. The controller is configured to determine whether the ambient temperature in the area is below a threshold based on the indication from the ambient temperature sensor, determine whether the area is occupied by at least one individual based on the indication from the occupancy sensor, and activate the heater when the ambient temperature in the area is below the threshold and the area is occupied by at least one individual.

Abstract: A safety automation system (20) for an occupiable structure and method of operation includes a plurality of detection devices (30) to facilitate the detection of a hazard condition and output a hazard detected signal to a computing management system (44) that may be a cloud computing system. The management system includes a computer processor (46), and a computer readable storage medium (48) capable of generating various notifications to a mobile user interface device (32).

Abstract: A safety automation system for an occupiable structure includes a computing management system including a computer processor, and a computer readable storage medium configured to run embedded software and cloud server software. A fire detection device of the automation system is adapted to detect a fire condition and output an associated fire condition detected signal to the computing management system. A condition deterrence device is configured to accept a wireless command signal from the computing management system associated with the fire condition detected signal and for actuating an appliance to at least reduce risk presented by the condition.

Abstract: A method for detecting smoke via a chamber-less smoke sensor includes applying one or more filters to eliminate a flooding of ambient light upon the smoke sensor and emitting, by a source, light. At least one detector detects at least a portion of the emitted light and a processor processes the detected light to signal an alarm condition when one or more threshold levels are reached. A chamber-less smoke sensor includes a light source configured to emit light and at least one detector configured to detect at least a portion of the emitted light. An electronic filter and/or a processor is configured to apply one or more filters to eliminate a flooding of ambient light upon the smoke sensor and process the detected light to signal an alarm condition when a threshold level is reached.

Abstract: A safety automation system (20) for an occupiable structure includes a computing management system (44) including a computer processor (46), and a computer readable storage medium (48) configured to run embedded software and cloud server software. A detection device (30) of the automation system is adapted to detect a condition and output an associated condition detected signal to the computing management system. A condition deterrence device (40) is configured to accept a wireless command signal from the computing management system associated with the condition detected signal and thereby actuate an appliance (51) to at least reduce risk of the condition.

Abstract: A safety automation system (20) for an occupiable structure includes a microphone (54) configured to receive an audible signature (50) and output an audible signature signal. A computing management system (40) of the automation system is configured to receive the audible signature signal and output a command signal. The command signal may be sent to appliances (36) within the structure that perform specific tasks in response to the command.

Abstract: A safety automation system (20) for an occupiable structure and method of operation includes a plurality of detection devices (30) to facilitate the detection of a hazard condition and output a hazard detected signal to a computing management system (44) that may be a cloud computing system. The management system includes a computer processor (46), and a computer readable storage medium (48) capable of generating various notifications to a mobile user interface device (32).

Abstract: A method for detecting smoke via a chamber-less smoke sensor includes applying one or more filters to eliminate a flooding of ambient light upon the smoke sensor and emitting, by a source, light. At least one detector detects at least a portion of the emitted light and a processor processes the detected light to signal an alarm condition when one or more threshold levels are reached. A chamber-less smoke sensor includes a light source configured to emit light and at least one detector configured to detect at least a portion of the emitted light. An electronic filter and/or a processor is configured to apply one or more filters to eliminate a flooding of ambient light upon the smoke sensor and process the detected light to signal an alarm condition when a threshold level is reached.

Abstract: A method for detecting smoke via a chamber-less smoke sensor includes applying one or more filters to eliminate a flooding of ambient light upon the smoke sensor and emitting, by a source, light. At least one detector detects at least a portion of the emitted light and a processor processes the detected light to signal an alarm condition when one or more threshold levels are reached. A chamber-less smoke sensor includes a light source configured to emit light and at least one detector configured to detect at least a portion of the emitted light. An electronic filter and/or a processor is configured to apply one or more filters to eliminate a flooding of ambient light upon the smoke sensor and process the detected light to signal an alarm condition when a threshold level is reached.

Abstract: There is provided an illuminated product including a foot element, a view mounting element, a housing containing a light source, and an interchangeable indicia carrier. There is also provided a method for coordinating a preferred occupant plan with a plurality of floor spot indicia carriers. The floor spot indicia carrier can be an illuminated product.

Abstract: A method for detecting smoke via a chamber-less smoke sensor includes applying one or more filters to eliminate a flooding of ambient light upon the smoke sensor and emitting, by a source, light. At least one detector detects at least a portion of the emitted light and a processor processes the detected light to signal an alarm condition when one or more threshold levels are reached. A chamber-less smoke sensor includes a light source configured to emit light and at least one detector configured to detect at least a portion of the emitted light. An electronic filter and/or a processor is configured to apply one or more filters to eliminate a flooding of ambient light upon the smoke sensor and process the detected light to signal an alarm condition when a threshold level is reached.