A security device, such as a passive infra-red motion detector (1) is provided with a plurality of fasteners (15, 25). One fastener (25) removably fastens a lens (4) to a housing of the passive infra-red detector, such that the lens (4) can be removed from the outside of the housing, whilst the other fastener (15) fastens a front section (2) of the housing to the rear section (3). Both fasteners (15, 25) are transparent/translucent and act as light guides.

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.

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.

A system to search in a low visibility environment comprising: an infrared (IR) sensor and a radar unit to receive measurements in a first field of view; a microphone to receive audio measurements in a second field of view; processing circuitry to determine presence of an animal and/or human in the first field of view using a first machine learning engine trained based upon the IR image measurements and/or using a second machine learning engine trained based upon the radar image measurements; determine presence of an animal and/or human in the second field of view using a third machine learning engine trained based upon the audio measurements; providing a first digital transmission indicating whether a human and/or animal is detected within the first field of view; and providing a second digital signal indicating whether a human and/or animal is detected within the second field of view.

A system to search in a low visibility environment comprising: an infrared (IR) sensor and a radar unit to receive measurements in a first field of view; a microphone to receive audio measurements in a second field of view; processing circuitry to determine presence of an animal and/or human in the first field of view using a first machine learning engine trained based upon the IR image measurements and/or using a second machine learning engine trained based upon the radar image measurements; determine presence of an animal and/or human in the second field of view using a third machine learning engine trained based upon the audio measurements; providing a first digital transmission indicating whether a human and/or animal is detected within the first field of view; and providing a second digital signal indicating whether a human and/or animal is detected within the second field of view.

The fastening structure is fastening one member and another member via a fastening member, and includes: a fitting portion having a fitting hole; a to-be-fitted portion having a to-be-fitted hole; and the fastening member inserted into the fitting hole. The fastening member has: a trunk portion, between one end and another end of the fastening member; a tool groove at the one end; a come-off prevention portion at the other end, the come-off prevention portion having a greater radius than a radius; and a helical protrusion at a part of the trunk portion. The fitting portion has a helical groove configured to be screwed with the helical protrusion. A radius of the fitting hole is less than the radius of the come-off prevention portion, and a radius of the to-be-fitted hole is not less than the radius of the come-off prevention portion.

A system and method for use in environment with electrical equipment is provided. The system including a housing and at least one light source located on an exterior of the housing. The light source being activated when the system is in a switching mode of operation. At least one sensor is operably coupled to the housing and configured to measure at least one parameter associated with the electrical equipment. A computing device is disposed within the housing and coupled to communicate with the at least one light source and the at least one sensor.

A mailbox notification system includes a radio frequency transmitter attached to a mailbox configured to transmit a signal upon detection of motion by a motion sensor, the motion sensor in electronic communication with the transmitter and configured to detect motion of a mailbox door, and a radio frequency receiver in electronic communication with the transmitter via a radio frequency wherein the receiver is configured to alert a user upon receiving a transmission from the transmitter.

A mailbox notification system includes a radio frequency transmitter attached to a mailbox configured to transmit a signal upon detection of motion by a motion sensor, the motion sensor in electronic communication with the transmitter and configured to detect motion of a mailbox door, and a radio frequency receiver in electronic communication with the transmitter via a radio frequency wherein the receiver is configured to alert a user upon receiving a transmission from the transmitter.

A low-cost, low-power, stand-alone sensor platform having a visible-range camera sensor, a thermopile array, a microphone, a motion sensor, and a microprocessor that is configured to perform occupancy detection and counting while preserving the privacy of occupants. The platform is programmed to extract shape/texture from images in spatial domain; motion from video in time domain; and audio features in frequency domain. Embedded binarized neural networks are used for efficient object of interest detection. The platform is also programmed with advanced fusion algorithms for multiple sensor modalities addressing dependent sensor observations. The platform may be deployed for (i) residential use in detecting occupants for autonomously controlling building systems, such as HVAC and lighting systems, to provide energy savings, (ii) security and surveillance, such as to detect loitering and surveil places of interest, (iii) analyzing customer behavior and flows, (iv) identifying high performing stores by retailers.