A computer-implemented event statistic generation method for intrusion detection comprises processing a plurality of return signals from a coherent optical time domain reflectometer into time domain signals for each of a plurality of sensor bins, the plurality of return signals corresponding to a plurality of stimulation pulses injected into an optical sensor fiber during a time period. For each sensor bin, the method comprises transforming the respective time-domain signal into a corresponding frequency-domain signal, calculating, from the respective frequency-domain signal, a first signal power area of a first frequency band expected to contain system noise, calculating, from the respective frequency-domain signal, a second signal power area of a second frequency band expected to contain any energy related to at least a first event; and generating an event statistic proportional to the ratio of the second signal power area to the first signal power area at least in part by dividing the second signal power area by the first signal power area.

A shock detector device (110) for premises security is described. The shock detector device (110) comprises a shock detector sensor (112) configured to sense physical motion and to output an electrical signal in response to the physical motion. Processing circuitry (114) is configured to process the electrical signal by: obtaining an indication that a shock event has occurred if a value for at least one parameter of the electrical signal is determined to exceed a threshold value; and processing instructions for adjusting at least one detection parameter of the shock detector device (110) in response to a determination that the shock event is a false alarm event, wherein the adjusting of the at least one detection parameter results in a decrease of a sensitivity of shock detection by the shock detector device (110).

Methods, systems, and apparatus for attempted entry detection are disclosed. A method for monitoring a property includes receiving, from a smart lock of a door located at a property monitored by a monitoring system, smart lock data that reflects a condition of the smart lock; receiving, from a sensor of the monitoring system, sensor data; analyzing the smart lock data and the sensor data; based on analyzing the smart lock data and the sensor data, determining that an attempted door entry is occurring; and in response to determining that an attempted door entry is occurring, performing a monitoring system action. Determining that an attempted door entry is occurring can include determining, based on the sensor data, that a person is located near the smart lock; and determining, based on analyzing the smart lock data, that the smart lock data satisfies criteria for an attempted door entry.

Methods are disclosed that, in some aspects, provide for the determination of alarm events or non-alarm events based on data received from various sensors monitoring one or more entry points of a premises. Non-alarm events may, for example, include a seismic event or a knock event. Determining whether the data received from the various sensors is an alarm or non-alarm event may be based on data received from two or more sensors monitoring two or more entry points of the premises. Further, data related to the non-alarm event that occurred at the premise may be compared to data related to non-alarm events that occurred at other premises and, based on the comparison, one or more authorities may be alerted to the non-alarm event.

The present disclosure relates to a monitoring system configured to monitor the activities of individuals without having to keep the surrounding area under the surveillance of a camera thereby maintaining the privacy of the individual. In particular, the monitoring system includes a network of sensitive sensor units that are installed onto indoor flooring to record human footstep induced vibrations. The data collected from the sensors can then be processed to identify individual occupants, determine the number of occupants, estimate the location of footsteps, and track the trajectory of each occupant. The extracted trajectory information can be used to assess an occupant's personal activity and social interaction, which can then be used to analyze the individual's physical and psychological health.

A computer-implemented event statistic generation method for intrusion detection comprises processing a plurality of return signals from a coherent optical time domain reflectometer into time domain signals for each of a plurality of sensor bins, the plurality of return signals corresponding to a plurality of stimulation pulses injected into an optical sensor fiber during a time period. For each sensor bin, the method comprises transforming the respective time-domain signal into a corresponding frequency-domain signal, calculating, from the respective frequency-domain signal, a first signal power area of a first frequency band expected to contain system noise, calculating, from the respective frequency-domain signal, a second signal power area of a second frequency band expected to contain any energy related to at least a first event; and generating an event statistic proportional to the ratio of the second signal power area to the first signal power area at least in part by dividing the second signal power area by the first signal power area.

Methods and a system for detecting physical intrusion are providing, including sampling a set of seismic signals from a vibration sensor of a buried sensor intrusion device, determining that the set of seismic signals matches a seismic threat pattern and responsively generating a seismic alert, recording a surveillance video of an area under which the sensor device has been buried, processing the surveillance video to determine whether a human figure is present and, responsively to determining that a human figure is present and to the generation of the seismic alert, issuing an threat detection alert.

A computer-implemented event statistic generation for intrusion detection comprises processing a plurality of return signals from a coherent optical time-domain reflectometer into time-domain signals for each of a plurality of sensor bins, the plurality of return signals corresponding to a plurality of stimulation pulses injected into an optical sensor fiber during a time period. For each sensor bin, transforming the respective time-domain signal into a corresponding frequency-domain signal, calculating, from the respective frequency-domain signal, a first signal power area of a first frequency band expected to contain system noise and a second signal power area of a second frequency band expected to contain any energy related to at least a first event; and generating an event statistic proportional to the ratio of the second signal power area to the first signal power area at least in part by dividing the second signal power area by the first signal power area.

Methods are disclosed that, in some aspects, provide for the determination of alarm events or non-alarm events based on data received from various sensors monitoring one or more entry points of a premises. Non-alarm events may, for example, include a seismic event or a knock event. Determining whether the data received from the various sensors is an alarm or non-alarm event may be based on data received from two or more sensors monitoring two or more entry points of the premises. Further, data related to the non-alarm event that occurred at the premise may be compared to data related to non-alarm events that occurred at other premises and, based on the comparison, one or more authorities may be alerted to the non-alarm event.

Methods are disclosed that, in some aspects, provide for the determination of alarm events or non-alarm events based on data received from various sensors monitoring one or more entry points of a premises. Non-alarm events may, for example, include a seismic event or a knock event. Determining whether the data received from the various sensors is an alarm or non-alarm event may be based on data received from two or more sensors monitoring two or more entry points of the premises. Further, data related to the non-alarm event that occurred at the premise may be compared to data related to non-alarm events that occurred at other premises and, based on the comparison, one or more authorities may be alerted to the non-alarm event.