Example implementations include a method, apparatus, and computer-readable medium comprising measuring a capacitance value between two measurement points in a capacitive sensing sensor of a door/window displacement detector, wherein the capacitance value between the two measurement points changes based on a proximity of the two measurement points to a door/window; and determining an open/close status of the door/window based on the capacitance value.

Example implementations include a method, apparatus, and computer-readable medium comprising capturing visual or audio data using at least one camera or microphone in a control panel; performing, by a processor of the control panel, at least one of a voice recognition or a facial recognition, based on the visual or audio data captured by the at least one camera or microphone in the control panel; recognizing an individual according to at least one of the voice recognition or the facial recognition; and presenting, on a display of the control panel, a graphical user interface that includes features associated with the individual.

Example implementations include a method, apparatus, and computer-readable medium comprising determining, by a processor of a control panel, that a security event has happened; and capturing still images or videos by a camera in the control panel subsequent to determining that the security event has happened. In some implementations, the camera is a forward-facing camera. In some implementations, determining that the security event has happened comprises detecting a motion using the camera in the control panel. In some implementations, determining that the security event has happened comprises receiving a signal indicative of activation of a door switch of a door located next to the control panel. In some implementations, the security event is associated with one or more Bluetooth devices being in range, and determining that the security event has happened comprises using a Bluetooth radio in the control panel to detect the Bluetooth devices.

Example implementations include a method, apparatus, and computer-readable medium comprising monitoring, by a control panel, an ambient noise via one or more microphones in the control panel. The implementations further include determining, by the control panel, whether the ambient noise is indicative of a security event. In some non-limiting implementations, the control panel may be configured to detect events based on various noise detection models, such as continued noise level above a threshold, noise associated with multiple short sharp impacts (e.g., an intruder trying to kick down a door), gunshot detection, voice recognition to identify a request for assistance (e.g., a person asking for help), glass break detection, or detection of a particular standardized pattern of beeps such as the temporal-three pattern of a smoke detector going off (according to ISO 8201 and ANSI/ASA S3.41 Temporal Pattern), the temporal-four pattern of a carbon monoxide detector going off, etc.

Example implementations include a method, apparatus, and computer-readable medium comprising executing a diagnostic tool locally at a control panel; and providing, by the diagnostic tool, via a display of the control panel, information related to a signal strength of a connection between the control panel and at least one device configured to communicate with the control panel over the connection.

Example implementations include a method, apparatus, and computer-readable medium comprising first broadcasting, by at least one primary speaker of a control panel, a first sound toward a front or a side of the control panel; and second broadcasting, concurrently with the first broadcasting, by a removable back speaker that is removably attachable to a back side of the control panel, a second sound toward the back side of the control panel. In some aspects, the removable back speaker is configured as a stand for placing the control panel on a flat surface.

It is provided a method for determining when a break-in attempt is in process. The method is performed in a break-in determiner and comprises the steps of: determining that a first vibration condition is tme when a vibration parameter associated with a barrier is greater than a first threshold, wherein the first vibration parameter is obtained from measurements from an accelerometer; determining whether an acceptable activity condition is tme or not, such that the acceptable activity condition is true only when there is an auxiliary signal indicating acceptable activity comprising determining that the acceptable activity condition is tme only when a time difference between determining that the first vibration condition is true and receiving the auxiliary signal is less than a threshold duration; and determining that a break-in attempt is in process when the first vibration condition is tme and the acceptable activity condition is false.

There is provided an abnormality detection device includes a detector configured to detect a shake of a vehicle, a threshold setting unit configured to set at least one threshold for determining whether the detected shake of the vehicle is abnormal, a vehicle peripheral information acquisition unit configured to acquire at least one of a video around the vehicle, illuminance information around the vehicle, and sound information around the vehicle, and a vehicle information acquisition unit configured to acquire information about a driving state of the vehicle, wherein the threshold setting unit is further configured to control the at least one threshold based on the information acquired by the vehicle peripheral information acquisition unit, when the vehicle is determined to be being parked based on the information acquired by the vehicle information acquisition unit.

Examples of systems and methods for locating movable objects such as carts (e.g., shopping carts) are disclosed. Such systems and methods can use dead reckoning techniques to estimate the current position of the movable object. Various techniques for improving accuracy of position estimates are disclosed, including compensation for various error sources involving the use of magnetometer and accelerometer, and using vibration analysis to derive wheel rotation rates. Various techniques utilize characteristics of the operating environment in conjunction with or in lieu of dead reckoning techniques, including characteristic of environment such as ground texture, availability of signals from radio frequency (RF) transmitters including precision fix sources. Navigation techniques can include navigation history and backtracking, motion direction detection for dual swivel casters, use of gyroscopes, determining cart weight, multi-level navigation, multi-level magnetic measurements, use of lighting signatures, use of multiple navigation systems, or hard/soft iron compensation for different cart configurations.

The present application provides a piezoelectric sensor, comprising: a base member, having an inverted conical structure at one end; a piezoelectric sensing element, disposed at the other end of the base member; a mass block, disposed on the piezoelectric sensing element; a charge amplifier, disposed above the mass block and electrically connected to the piezoelectric sensing element. The process of installing the piezoelectric sensor provided in the technical solution of the present application on the ground is simple and fast, and its low-frequency response sensitivity is high.