An intelligent entrance detection system is provided where, primarily, any authorized or unauthorized entry to an area of a residential (or small industrial) unit covered by a wireless network is automatically detected from active off-the-shelf devices in that area. After the detection, an identification algorithm is employed to verify if this entry is a legal or illegal action. Based on this verification, either the routine smart home system is activated or a hazardous monitoring period begins to further investigate the suspicious event. If the illegal entrance is confirmed during the hazardous monitoring period, the owner of the property is informed through an intruder alarm protocol. In this invention, all of the analytic and processing steps, including entrance detection, owner identification, and device-free authority verification are designed based on monitoring and quantification of changes in surrounding wireless signals originated by human or object movements within the sensing area.

In a general aspect, a method is presented for detecting a location of motion using wireless signals that propagate along two or more paths of a wireless communication channel. The method includes storing a set of eigenvectors derived from first motion-sensing data associated with a first time frame. The first motion-sensing data is associated with a first motion-sensing topology of a wireless mesh network. The method also includes obtaining a motion vector based on wireless signals transmitted between access point nodes in the wireless mesh network during a second, subsequent time frame. The wireless mesh network operates in a second, distinct motion-sensing topology during the second time frame. The motion vector is compared with the respective eigen vectors, and a probability vector is generated based on the comparison. A location of the motion of the object during the second time frame is determined based on the probability vector.

A presence sensor device 8 for a building. The presence sensor device 8 is for detecting persons and includes a first radar sensor 14 and a second radar sensor 20. The first radar sensor 14 is arranged to operate with a first frequency band, a first power consumption, and a first range, with the second radar sensor 20 being arranged to operate with a second frequency band, a second power consumption, and a second range. The first frequency band is lower than the second frequency band and the first range is longer than the second range.

In a general aspect, a method is presented for detecting a location of motion using wireless signals that propagate along two or more paths of a wireless communication channel. The method includes storing a set of eigenvectors derived from first motion-sensing data associated with a first time frame. The first motion-sensing data is associated with a first motion-sensing topology of a wireless mesh network. The method also includes obtaining a motion vector based on wireless signals transmitted between access point nodes in the wireless mesh network during a second, subsequent time frame. The wireless mesh network operates in a second, distinct motion-sensing topology during the second time frame. The motion vector is compared with the respective eigen vectors, and a probability vector is generated based on the comparison. A location of the motion of the object during the second time frame is determined based on the probability vector.

Presented herein are systems and methods for detecting a boundary line crossing based on Round Trip Time (RTT) measured for wireless signals transmitted between and initiator wireless transceiver and a responder wireless transceiver deployed to form a straight boundary line. The initiator wireless transceiver transmits wireless probe signal(s) to the responder wireless transceiver, receives a wireless response signal transmitted by the responder wireless transceiver in response to the wireless probe signal(s), calculates an RTT combining a travel time of the wireless probe signal(s) and the travel time of the wireless response signal(s), compares the RTT to a reference RTT computed for a wireless probe signal and a corresponding wireless response signal transmitted in a clear straight transmission path while the boundary line is clear of obstacles and determines whether an object is blocking the straight transmission path based on a deviation of the RTT from the reference RTT.

The systems and method proposed herein aim to identify a mobile device or devices worn by an individual or a subject that has entered an area monitored by a passive motion detection system that uses wireless signals to sense motion in the space. The system will collect as much signals as possible from both the devices worn by the individual and from the system performing the passive (device-free) motion detection for identifying the individual or person of interest. The individual or person of interest may be a user of a product or an intruder.

A process of identifying suspicious object movements in an incident location. An electronic computing device obtains incident information identifying a time of occurrence and a location of an incident. The electronic computing device identifies internet-of-things (IoT) devices deployed in the incident location and accesses received signal strength indication (RSSI) information associated with a selected IoT device. The RSSI information includes historical RSSI values that were captured at the IoT device during the time of occurrence of the incident. The electronic computing device generates a suspicious object movement pattern corresponding to the at least one IoT device based on variations within the historical RSSI values that were captured at the at least one IoT device during the first time period. A display or audio output device provides a corresponding visual or audio output indicating the suspicious object movement pattern corresponding to the IoT device.

A process of identifying suspicious object movements in an incident location. An electronic computing device obtains incident information identifying a time of occurrence and a location of an incident. The electronic computing device identifies internet-of-things (IoT) devices deployed in the incident location and accesses received signal strength indication (RSSI) information associated with a selected IoT device. The RSSI information includes historical RSSI values that were captured at the IoT device during the time of occurrence of the incident. The electronic computing device generates a suspicious object movement pattern corresponding to the at least one IoT device based on variations within the historical RSSI values that were captured at the at least one IoT device during the first time period. A display or audio output device provides a corresponding visual or audio output indicating the suspicious object movement pattern corresponding to the IoT device.

A multi sensor detection and disabling lock system includes detector cases for holding interchangeable detectors that sample for chemical, biological and radiological compounds, agents and elements, with each detector case disposed in or upon the monitored product. The detector case transmits detection information to a monitoring computer terminal and transmits a signal to a lock disabler engaged to the product to lock or disable the product's lock thereby preventing untrained, unauthorized and unequipped individuals from gaining access and entry to the product, and also preventing further contamination of the area. The detection system can be interconnected to surveillance towers scanning detector cases disposed at seaport docks, freight depots and rail terminals for monitoring containers being prepared for shipment or sitting on docks for long periods of time.

A device for measuring disruptions in a controlled magnetic field and generated by the device itself surrounding a sole conductive element, antenna or electrode and comprising, at least: a controlled magnetic field sensor comprising, in turn, an oscillator circuit connected to at least one electrode, a digital module; and a processor connected to the digital module. The applications of the device that is the object of the invention are all those requiring the detection of an object prior to it resulting in the violation of the restricted space. Amongst these applications we can highlight the following: the localisation of people, industrial security applications, robotics, domestic security applications, military applications and vehicle security applications.