A smoke detection device main body of a portable smoke detector can switch smoke detection sensitivity. At the start of operation, the smoke detection sensitivity of the portable smoke detector is equal to or higher than a smoke detection sensitivity of a fixed smoke detector that detects smoke in a monitoring area. At this time, switching of smoke detection sensitivity does not work. After the fixed smoke detector detects smoke generation, when the portable smoke detector is used to locate the smoke generation position while moving in the monitoring area, an operation is performed from an initial sensitivity. When a predetermined smoke detection signal is detected while using the portable smoke detector to identify the smoke generation position, the smoke detection sensitivity switching is activated, and the smoke detection sensitivity is changed accordingly. By lowering the smoke detection sensitivity, the smoke generation position is narrowed down and identified.

In various examples, systems and methods are disclosed that provide highly accurate gaze predictions that are specific to a particular user by generating and applying, in deployment, personalized calibration functions to outputs and/or layers of a machine learning model. The calibration functions corresponding to a specific user may operate on outputs (e.g., gaze predictions from a machine learning model) to provide updated values and gaze predictions. The calibration functions may also be applied one or more last layers of the machine learning model to operate on features identified by the model and provide values that are more accurate. The calibration functions may be generated using explicit calibration methods by instructing users to gaze at a number of identified ground truth locations within the interior of the vehicle. Once generated, the calibration functions may be modified or refined through implicit gaze calibration points and/or regions based on gaze saliency maps.

Methods, systems, and apparatuses for securing property are presented. Video content viewed by a user may be detected, and the user may be automatically prompted to change settings on a security system based on the detecting. A comparison of the current time with the duration of the video content may serve as the basis for such prompting. Additionally, a premise security system may be placed in a learning mode. Changes in position of a security sensor may be detected and used to set a permitted range of motion for the sensor. Further, a plurality of security sensor profiles may be stored, and each profile may identify a different predefined permitted range of motion of a sensor. The addition of a new sensor to a premise may be detected, and a user may be prompted, on a display, to identify a profile to be used for the new sensor.

Methods, systems, and apparatuses for securing property are presented. Video content viewed by a user may be detected, and the user may be automatically prompted to change settings on a security system based on the detecting. A comparison of the current time with the duration of the video content may serve as the basis for such prompting. Additionally, a premise security system may be placed in a learning mode. Changes in position of a security sensor may be detected and used to set a permitted range of motion for the sensor. Further, a plurality of security sensor profiles may be stored, and each profile may identify a different predefined permitted range of motion of a sensor. The addition of a new sensor to a premise may be detected, and a user may be prompted, on a display, to identify a profile to be used for the new sensor.

The present invention solves a very complex problem that is a major obstacles for electric utility industry's power lines vegetation encroachment management business. Vegetation contacts to the high voltage overhead power lines cause flash-over and/or blackout which results in hazardous situations and economic losses. Power line vegetation management is a very cost intensive business process which is essential to ensure safe, reliable and affordable electric energy supply by the electric utilities, transmission and generation owners. This routine electric utility vegetation management related work is mandated and overseen by applicable federal, state or local regulatory agencies. The state-of-the-art vegetation management process involves labor and cost intensive foot-patrol, vehicular patrol, air patrol and airborne LIDAR patrol of power lines. These methods are often inefficient, unreliable, risky and costly. The present invention provides a method and system for automated vegetation growth, condition and status monitoring near high voltage utility electric lines using stationary sensors, wireless or wired communications and computation technologies and proprietary algorithms. The method and system of the current invention monitors the power line infrastructures remotely and advises the vegetation maintenance crews on mitigating actions without requiring human interventions, thus saving cost and reducing risks to the humans and environment. A comprehensive vegetation encroachment condition report with vegetation proximity advisory (VPA) and vegetation resolution advisory (VRA) is automatically generated and transmitted to the operational staff by the system for each electric line span at certain time interval or continuously without boots-on-the-ground manual asset inspection and/or air patrol using aircraft. This current invention is an automated, safer and low-cost solution to an electric utility industry's essential reliability and compliance related business process.

The present invention solves a very complex problem that is a major obstacles for electric utility industry's power lines vegetation encroachment management business. Vegetation contacts to the high voltage overhead power lines cause flash-over and/or blackout which results in hazardous situations and economic losses. Power line vegetation management is a very cost intensive business process which is essential to ensure safe, reliable and affordable electric energy supply by the electric utilities, transmission and generation owners. This routine electric utility vegetation management related work is mandated and overseen by applicable federal, state or local regulatory agencies. The state-of-the-art vegetation management process involves labor and cost intensive foot-patrol, vehicular patrol, air patrol and airborne LIDAR patrol of power lines. These methods are often inefficient, unreliable, risky and costly. The present invention provides a method and system for automated vegetation growth, condition and status monitoring near high voltage utility electric lines using stationary sensors, wireless or wired communications and computation technologies and proprietary algorithms. The method and system of the current invention monitors the power line infrastructures remotely and advises the vegetation maintenance crews on mitigating actions without requiring human interventions, thus saving cost and reducing risks to the humans and environment. A comprehensive vegetation encroachment condition report with vegetation proximity advisory (VPA) and vegetation resolution advisory (VRA) is automatically generated and transmitted to the operational staff by the system for each electric line span at certain time interval or continuously without boots-on-the-ground manual asset inspection and/or air patrol using aircraft. This current invention is an automated, safer and low-cost solution to an electric utility industry's essential reliability and compliance related business process.

A method of calibrating a sensor (200) for a security system, the method comprising: switching the sensor (200) to a zone calibration mode for configuring the sensor (200) to operate with a detection zone; detecting a moveable object (202) moving along a border of the detection zone, wherein the sensor (200) detects the position of the moveable object (202) as the moveable object (202) moves along the border of the detection zone; calculating zone calibration data for the detection zone based on the detected positions of the moveable object (202); and configuring the sensor (200) to operate using the calculated zone calibration data.

A thermographic detector device for a fire alarm control system is described herein. In some examples, one or more embodiments include a thermography camera configured to capture a thermal image within a field of view of the thermographic detector device, a memory and a processor to execute instructions stored in the memory to detect a fault associated with the thermographic detector device, wherein the fault includes at least one of a field of view fault, an operating parameter fault, and an internal fault, generate a fault signal upon detecting the fault, and provide a notification of the fault using the fault signal.

A thermographic detector device for a fire alarm control system is described herein. In some examples, one or more embodiments include a thermography camera configured to capture a thermal image within a field of view of the thermographic detector device, a memory and a processor to execute instructions stored in the memory to detect a fault associated with the thermographic detector device, wherein the fault includes at least one of a field of view fault, an operating parameter fault, and an internal fault, generate a fault signal upon detecting the fault, and provide a notification of the fault using the fault signal.

A magnetometer sensor that detects tampering is described. The sensor samples magnetometer data and computes a set of vectors based on the magnetometer data. The sensor detects a tampering of the magnetic sensor based on determining that the set of vectors is outside the reference plane for the magnetometer sensor. The sensor generates a notification to a security system coupled to the magnetometer sensor. The notification indicating the tampering of the magnetometer sensor.