A system and methods are provided for community outdoor fire protection comprising: receiving indicators of a current fire, and responsively determining a level of the current fire risk for each of multiple endpoints of a shared water supply; determining a relative duty cycle for operating each endpoint according to a fire risk; receiving a water pressure measurement of the shared water source and determining a maximum number of concurrent endpoints to operate; accordingly allocating operation of each endpoint to a set of time slots; and activating the multiple endpoints to turn on respective water flows according to the time slot allocation.

A photoelectric smoke detector (14) connected to a signal line (12-1) drawn into a warning area from a receiver (10) transmits a fire signal including identification information of smoke caused in detection zones Z1 and Z2. In the detection zones, a sensor (18) for sensing a change of physical phenomenon other than smoke involved in fire is provided, and the sensor (18) is connected to the signal line (12-1) via a relay device (16). The sensor (18) is at least one of a CO.sub.2 sensor, a CO sensor, a fire sensor, and a heat sensor. A fire alarm control unit (48) of the receiver (10) causes an alarm to be given, when determining the identification information of the smoke by the photoelectric smoke detector (14) and a sensing value by at least one of the CO.sub.2 sensor, the CO sensor, the fire sensor, and the heat sensor.

A vehicle theft-prevention apparatus can include at least one computing device couple to a plurality of sensors and a wireless transceiver. The plurality of sensors can be configured to sense measurements proximate to a vehicle. The at least one computing device can be configured to read a plurality of first measurements of a first sensor of the plurality of sensors. Based on the plurality of first measurements from the first sensor, the at least one computing device can determine that a key fob moved outside of a range of the first sensor. In response to the key fob moving outside of the range of the first sensor, the at least one computing device can transition to an armed state. The at least one computing device can read a plurality of second measurements from a subset of the plurality of sensors. Based on the plurality of second measurements, the at least one computing device can determine that a person has entered the vehicle.

Embodiments of this application provide a fire-fighting switch device and a fire-fighting system, which are applied to the field of fire-fighting. The fire-fighting switch device includes a plurality of fire detection switch units, where the fire detection switch unit includes one or more fire detection switches, the one or more fire detection switches form at least one switch path, the fire detection switch is configured to turn on when a fire is detected, and any one of the switch paths is configured to transmit a voltage signal to a fire-extinguishing device when all of the fire detection switches on the switch path are turned on. In this solution, when a fire is detected by one fire detection switch unit, the fire-extinguishing device can be controlled to extinguish the fire provided that all fire detection switches on one switch path in the fire detection switch unit are turned on.

The disclosure relates to a method for recognizing at least one naturally emitted sound produced by a real-life sound source in an environment comprising at least one artificial sound source. The method is implemented by an audio recognition device, and it includes simultaneously obtaining a first audio signal from a first microphone located in the environment and a second audio signal from an audio acquisition device associated with the at least one artificial sound source; analyzing the first audio signal, delivering a first list of sound classes corresponding to sounds recognized in the first audio signal; analyzing the second audio signal, delivering a second list of sound classes corresponding to sounds recognized in the second audio signal; and delivering a third list of sound classes, comprising only sound classes included in the first list of sound classes which are not included in the second list of sound classes.

One or more computing devices, systems, and/or methods are provided. One or more first signals received from one or more first devices may be monitored. One or more first threat indicators within a first signal of the one or more first signals may be detected. One or more second signals may be analyzed to determine a probability of a threat event. One or more second devices of a plurality of devices may be selected, based upon the probability, for transmission of one or more messages associated with the threat event.

A context driven alerting system and method is described in accordance with one or more embodiments of the present disclosure. The alerting system and method may consider a pilot's physiological, psychological, and behavioral state during a given mission context. The system may include biometric information which is fused with a context of the flight. The context may be based on one or more of a mission profile data or an aircraft state data. The fused data may be time synchronized and provided to an alerting algorithm. The alerting algorithm may then provide an alert to the pilot which includes a priority, intensity, frequency, or modality determined based on the fused information.

In accordance with a first aspect of the present disclosure, a system is provided for facilitating detecting an unauthorized access to an object, the system comprising: a plurality of ultra-wideband (UWB) communication nodes; a controller operatively coupled to said plurality of UWB communication nodes, wherein the controller is configured to: cause at least one of the UWB communication nodes to transmit one or more UWB messages to other UWB communication nodes of said plurality of UWB communication nodes; receive a channel impulse response (CIR) estimate and/or one or more parameters relating to said CIR output by the UWB communication nodes in response to receiving said UWB messages; analyze said CIR estimate and/or said parameters relating to the CIR to detect said unauthorized access to the object. In accordance with a second aspect of the present disclosure, a corresponding method is conceived for facilitating detecting an unauthorized access to an object. In accordance with a third aspect of the present disclosure, a computer program is provided for carrying out said method.

A machine-implemented method for automated detection of drowsiness, which includes receiving from an imaging device directed at the face of an operator a series of images of the face of the operator onto processing hardware, on the processor detecting facial landmarks of the operator from the series of images to determine the level of talking by the operator, the level of yawning of the operator, the PERCLOS of the operator, on the processor detecting the facial pose of the operator from the series of images to determine the level of gaze fixation by the operator, on the processor calculating the level of drowsiness of the operator by ensembling the level of talking by the operator, the level of yawning of the operator, the PERCLOS of the operator and the level of gaze fixation by the operator, and generating an alarm when the calculated level of drowsiness of the operator exceeds a predefined value.

The present disclosure discloses an object detection method used in an object detection apparatus that includes the steps outlined below. An image signal received from an image sensor is detected to generate an image detection signal when an image variation is detected. An infrared signal received from an infrared sensor is detected to generate an infrared detection signal when an infrared energy variation is detected. A time counting process is initialized when the image detection signal is generated. An object detection signal is generated when the infrared detection signal is generated within a predetermined time period after the time counting process is initialized. A detection distance of the image sensor is larger than a detection distance of the infrared sensor.