The present disclosure provides an early warning method and an early warning device based on WIFI signal strength disturbance, and a storage medium. The early warning method includes receiving and analyzing WIFI signals in a monitoring area in real time to obtain amplitude and phase of a current WIFI signal in the monitoring area; determining whether the amplitude and the phase of the current WIFI signal are disturbed according to a difference between the amplitude and the phase of the current WIFI signal and those of a previous WIFI signal; and sending out an early warning signal when it is determined that the amplitude and the phase of the current WIFI signal are disturbed.

Techniques are described for moving asset location tracking and monitoring system technology. A system monitors for events related to a monitoring system that monitors a fixed property and the system detects an event related to the monitoring system based on the monitoring. The system performs an operation that leverages geographic location tracking of at least one mobile asset associated with the fixed property based on the detected event.

There is provided a method of arranging a security alarm system on a window/door and framing. The system includes an object and a sensor which is capable of detecting the object within a predetermined range. The method includes positioning a first of the sensor and object on a first of the window/door and framing. The method includes opening the window/door to a threshold distance which facilitates ventilation and inhibits an intruder from passing through the window/door. The method includes positioning a second of the sensor and object along a second of the window/door and framing such that the sensor is able to detect the object as the window/door is opened up to but not past the threshold distance. There is also provided in combination, a window/door, framing extending about the window/door and a security alarm system coupled to the window/door and framing in the manner described above.

A method of detecting threats. A threat detection system is provided that includes a controller, a millimeter wave radar, a signature database and a camera. The signature database or machine learning includes time and frequency domain characteristic data for a threat. A signal is emitted by the millimeter wave radar. A return signal is received when the signal bounces off an object. Time and frequency domain characteristic data of the return signal is compared to the signature database or the machine learned characteristics to determine the threat, anomaly, foreign object and material characteristics.

Disclosed herein are system, method, and computer program product embodiments for the detection of human presence in front of a plurality of sensors such as those of speakers and a device with a processor, such as a television. Data gathered from the plurality of sensors may be analyzed by the processor to determine if one or more humans are present proximate to the device. Based on the determined presence or absence of one or more humans, further actions including, inter alia, activating a sleep mode for the one or more humans, shutting off the device in a green mode, or alerting an owner-user to the presence of an intruder can be taken.

This document describes techniques and devices to detect and classify human and animal presence and/or motion based on changes in the interaction of the human or animal with Wireless Local Area Network (WLAN) radio frequency (RF) signals within or about a building structure, such as a home or office. A first WLAN device transmits a sounding packet to a second WLAN device and receives an acknowledgement (ACK) of receiving the sounding packet by the second WLAN device. The first WLAN device uses the received ACK to determine Channel State Information (CSI) for an RF signal path between the first WLAN device and the second WLAN device, aggregates the determined CSI with additional CSI, and uses the aggregated CSI to determine a presence or a motion within the structure.

An electric or electronic device module comprises an electronic device, means for powering the electric or electronic device module, and at least one radar sensor having a detection range. The electric or electronic device module has a processor adapted for calibrating the at least one radar sensor by at least partly automatically defining and calculating parameters of boundaries of a predefined geometry, in which the at least one radar sensor has to measure, in order to prevent the at least one radar sensor from taking into account measurements outside that predefined geometry. The predefined geometry is located within the detection range of the at least one radar sensor and is equally sized to or smaller than that detection range of the at least one radar sensor.

Described is a security sensor comprising two or more sub-sensors for use in a variety of installations where different magnetic fields may be experienced by the security sensor as a result of the variety of installations. One of the sub-sensors may have a low magnetic sensitivity while the other sub-sensor may have a much higher sensitivity to magnetic fields. In operation, one or both sub-sensors are used to determine if a door or a window has been opened.

A networked system for managing a physical intrusion detection/alarm includes an upper tier of server devices, comprising: processor devices and memory in communication with the processor devices, a middle tier of gateway devices that are in communication with upper tier servers, and a lower level tier of devices that comprise fully functional nodes with at least some of the functional nodes including an application layer that execute routines to provide node functions, and a device to manage the lower tier of devices, the device instantiating a program manager that executes a state machine to control the application layer in each of the at least some of the functional nodes.

Methods of defining a virtual fence and for detecting a body inside or outside a region of interest defined by the virtual fence and/or of determining a height for a body on a surface in a region of interest use radar signals and a configuration mode and a monitoring mode are disclosed. In the configuration mode coordinates for defining a virtual fence are determined and/or a topology of a surface in the region of interest is determined. In the monitoring mode, a location of a second body on the surface is detected to determine if the second body is inside or outside the virtual fence and/or a height of for the second body relative to the determined topology is determined.