On-camera tampering detection

Abstract

The present disclosure relates to methods and systems for detecting tampering of the camera or tampering with the camera performed at a camera. An exemplary camera used in a security system can include a housing for accommodating an image sensor, a lens for directing incident light toward the image sensor, a plurality of tamper detection sensors each providing a sensing value, a controller, and a memory operatively connected to the controller. The memory can store a set of normal sensor values ​​for the plurality of tamper detection sensors. The controller can be configured to repeatedly poll each of the plurality of tamper detection sensors to receive a set of current sensor values, and compare the set of current sensor values ​​with the set of stored normal sensor values. The controller can be configured to issue an alert when one or more identified differences meet one or more predetermined criteria.

Description

[0001] Priority claim

[0002] This application claims priority to and the benefit of U.S. patent application serial number 16 / 723,837, filed on December 20, 2019, which is incorporated herein by reference in its entirety. Technical Field

[0003] The present disclosure generally relates to cameras used in security systems. More specifically, the present disclosure relates to methods and systems for detecting tampering with cameras. Background Art

[0004] Camera tampering detection is considered an important requirement in video surveillance. Camera tampering can include, but is not limited to: the camera is physically moved or hit, power is interrupted, vandalism, covering the lens, blocking the field of view, blurring the image, focusing bright light on the lens, changing the field of view, etc. In some cases, camera tampering can be detected by processing the video stream captured by the camera. However, this can be a software-based solution, which may become complex due to repeated polling of the camera when centralized at a server. When software solutions are applied to the camera itself, the camera may require higher-end processing elements, which may be prohibitive for many applications due to high costs. A lower cost solution for detecting camera tampering is desired. Summary of the invention

[0005] The present disclosure generally relates to cameras used in security systems. More specifically, the present disclosure relates to methods and systems for tamper detection with respect to cameras.

[0006] In one example, a camera used in a security system can include a housing for accommodating a plurality of components, the plurality of components including an image sensor, a lens for directing incident light toward the image sensor, a plurality of tamper detection sensors each providing a sensed value, a controller operatively coupled to the image sensor and the plurality of tamper detection sensors, and a memory operatively coupled to the controller. The memory can store a set of normal sensor values ​​for the plurality of tamper detection sensors. At least one normal sensor value of the normal sensor values ​​of at least one of the tamper detection sensors can include a normal sensor pattern over time. For example, if the camera typically turns on the light in the field of view at 7:00 a.m. every weekday, the normal sensor value of the ambient light sensor of the camera can reflect a "normal" light pattern. The controller can be configured to repeatedly poll each of the plurality of tamper detection sensors to receive a set of current sensor values, and compare the set of current sensor values ​​with a set of stored normal sensor values ​​and identify one or more differences. The controller can be configured to issue an alert when the identified one or more differences meet one or more predetermined criteria.

[0007] In some cases, the one or more predetermined criteria can include one or more differences exceeding a threshold difference in response to each polling of at least "N" pollings of the plurality of tamper detection sensors within a predetermined amount of time, where "N" is an integer greater than 1.

[0008] In some cases, the normal sensor pattern over time can include expected changes in environmental conditions in or around the camera. In some cases, the normal sensor pattern over time can be established during a training phase. In some cases, the training phase can occur over one or more time periods representing one or more different operating conditions.

[0009] In another example, a camera used in a security system can include a housing for housing a plurality of components, the plurality of components including: an image sensor; a lens for directing incident light toward the image sensor; one or more structural tampering detection sensors for detecting structural tampering of the camera, each of the one or more structural tampering detection sensors providing a sensing value; one or more functional tampering detection sensors for detecting functional tampering of the camera, each of the one or more functional tampering detection sensors providing a sensing value; a controller operatively coupled to the image sensor, the one or more structural tampering detection sensors, and the one or more functional tampering detection sensors; and a memory operatively coupled to the controller. The memory can store a set of normal sensor values ​​of the one or more structural tampering detection sensors and the one or more functional tampering detection sensors, wherein at least one of the normal sensor values ​​of at least one of the functional tampering detection sensors includes a normal sensor pattern over time. The controller may be configured to repeatedly poll each of the one or more structural tamper detection sensors and each of the one or more functional tamper detection sensors to receive a set of current sensor values ​​and / or patterns, and compare the set of current sensor values ​​with the set of stored normal sensor values ​​and / or patterns and identify one or more differences. The controller may be configured to issue an alert when the identified one or more differences meet one or more predetermined criteria.

[0010] In some cases, a set of normal sensor values ​​for one or more structural tamper detection sensors and one or more functional tamper detection sensors can be represented by a normal vector, and wherein a set of current sensor values ​​for one or more structural tamper detection sensors and one or more functional tamper detection sensors is represented by a sensing vector, and wherein comparing the set of current sensor values ​​with the set of stored normal sensor values ​​includes comparing the normal vector with the sensing vector.

[0011] In some cases, one or more structural tamper detection sensors can include electrical contacts that complete a circuit monitored by the controller when the camera is assembled and become disengaged when the camera is removed due to tampering, thereby breaking the circuit detected by the controller.

[0012] In some cases, the one or more functional tamper detection sensors can include one or more of an ambient light sensor, a vibration sensor, an accelerometer, a digital compass, and a touch sensor.

[0013] In some cases, the one or more predetermined criteria can include one or more differences exceeding a threshold difference in response to each of at least "N" polling of one or more structural tamper detection sensors and one or more functional tamper detection sensors within a predetermined amount of time, where "N" is an integer greater than 1.

[0014] In another example, a camera used in a security system can include: a housing; an image sensor housed by the housing; a lens housed by the housing for directing incident light toward the image sensor; a controller housed by the housing, the controller operatively coupled to the image sensor; one or more connectors housed by the housing and operatively coupled to the controller, the one or more connectors being accessible from outside the housing and configured to selectively connect to one or more cables of the security system; and a sensor operatively coupled to the controller, the sensor configured to sense a force applied to one or more of the connectors. The controller can be configured to issue an alert when the sensor senses that the force applied to one or more of the connectors meets one or more predetermined criteria.

[0015] In some cases, the sensor can include a pressure sensor. In some cases, the sensor can include a force sensor. In some cases, the one or more predetermined criteria can include the sensed force exceeding a predetermined threshold. In some cases, the one or more predetermined criteria can include the sensed force changing beyond a predetermined threshold. In some cases, the one or more predetermined criteria can include the sensed force changing according to a predetermined force profile.

[0016] In some cases, the camera can further include one or more electrical contacts that form an electrical circuit monitored by the controller when the camera is assembled, wherein at least one of the one or more electrical contacts becomes disengaged when the camera is disassembled, thereby breaking the circuit, wherein the controller is configured to issue an alert when the circuit is broken. In some cases, one or more of the electrical contacts can include a screw that must be removed to disassemble the camera, wherein when the screw is removed, the corresponding electrical contact becomes disengaged, thereby breaking the circuit.

[0017] In some cases, the camera can further include one or more additional sensors configured to detect unauthorized tampering of the camera. In some cases, the one or more additional sensors can include an ambient light sensor, a vibration sensor, an accelerometer, a digital compass, a touch sensor, and / or a combination thereof.

[0018] The above summary is provided to facilitate understanding of some innovative features unique to the present disclosure, but is not intended to be a complete description. A comprehensive understanding of the present disclosure can be obtained by viewing the entire specification, claims, drawings and abstract as a whole. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The present disclosure may be more fully understood by considering the following description of various examples in conjunction with the accompanying drawings, in which:

[0020] Figure 1 is a schematic diagram of an exemplary camera for use in a security system;

[0021] Figure 2 For including a plurality of tamper detection sensors Figure 1 A schematic diagram of an exemplary camera;

[0022] Figure 3 A flow chart of an exemplary method for tamper detection;

[0023] Figure 4 is a flow chart of an exemplary method for establishing a normal mode;

[0024] Figure 5 A flowchart of an exemplary method for tamper detection; and

[0025] Figure 6 is an illustrative block diagram of a sensor mode.

[0026] Although the present disclosure is subject to various modifications and alternative forms, the details thereof have been shown by way of example in the accompanying drawings and will be described in detail. However, it should be understood that it is not intended to limit the present disclosure to the specific examples described. On the contrary, it is intended to cover all modifications, equivalents and alternatives that fall within the essence and scope of the present disclosure. DETAILED DESCRIPTION

[0027] The following description should be read with reference to the accompanying drawings, in which similar elements in different drawings are numbered in the same manner. The accompanying drawings are not necessarily drawn to scale, and they depict examples that are not intended to limit the scope of the present disclosure. Although examples of various elements are shown, those skilled in the art will recognize that many of the examples provided have suitable alternatives that can be utilized.

[0028] It is assumed herein that all numbers are modified by the term "about" unless the content clearly dictates otherwise. The recitation of numerical ranges by endpoints includes all numbers subsumed within that range (eg, 1 to 5 includes 1, 1.5, 2, 2.75, 3, 3.80, 4, and 5).

[0029] As used in this specification and the appended claims, the singular forms "a," "an," and "the" include plural referents unless the content clearly dictates otherwise. As used in this specification and the appended claims, the term "or" is generally employed in its sense including "and / or" unless the content clearly dictates otherwise.

[0030] It should be noted that references to "one embodiment", "some embodiments", "other embodiments", etc. in the specification indicate that the described embodiments may include a particular feature, structure, or characteristic, but every embodiment may not necessarily include the particular feature, structure, or characteristic. Moreover, these phrases do not necessarily refer to the same embodiment. In addition, when a particular feature, structure, or characteristic is described in conjunction with one embodiment, it is contemplated that the feature, structure, or characteristic is described in conjunction with one embodiment, and it is contemplated that the feature, structure, or characteristic may be applied to other embodiments regardless of whether explicitly described, unless otherwise clearly stated.

[0031] The present disclosure as a whole relates to cameras used in security systems or video surveillance systems. As described above, there is a need for a solution with lower cost, which may not require high-end processing of video streams at the edge or have the challenge of processing video streams on a central server. Generally speaking, with this system, sensors and hardware provide an onboard solution for camera tampering. It is conceivable that both the structural and functional integrity of the camera can be monitored using specific analytical sensors. Some exemplary sensors that can be used for camera tampering detection include, for example, ambient light sensors, accelerometers, gyroscopes, vibration sensors, force sensors, pressure sensors, digital compasses, etc. These sensors can be mounted on the camera, mounted in the camera housing, or mounted on other components of the camera. It is conceivable that the alignment mechanism of the camera can also be used to detect impact or breakage. In some cases, a simple analysis of sensor values ​​can be used to detect tampering while avoiding false alarms. In some cases, a portion of the same sensor, such as an accelerometer, a gyroscope, and / or a vibration sensor, can be used to determine parameters related to wear and tear on the camera.

[0032] Camera tampering may affect both the structure of the camera and the functionality of the camera. The camera tampering detection system can specify different sensors and mechanisms for detecting both of these conditions. Figure 1 A schematic diagram of an exemplary camera 10 for use in an alarm and / or surveillance system is shown. Figure 1 The camera 10 does not include all structural elements and / or functional elements of the camera, but for the sake of clarity, only some of these elements are shown. The exemplary camera 10 can include a housing 12 for enclosing the components of the camera 10. In some cases, the camera 10 can be a dome camera including a transparent protective dome 14. However, this is not required. In some cases, the camera 10 can be a bullet-type camera. As needed, the camera 10 can have a fixed field of view or can be a pan-tilt-zoom (PTZ) camera. It is conceivable that the camera 10 can be used indoors and / or outdoors and for daytime and / or nighttime use as needed. In some cases, the housing 12 can be weatherproof for use outdoors, or one or more night vision light emitting diodes (LEDs) can be set near the dome 14 for nighttime use.

[0033] Within the housing 12, the exemplary camera 10 can include or house a lens 16. The lens 16 can be configured to direct incident light toward an image sensor 22. The image sensor 22 can process the light captured by the lens 16 into a digital signal. The digital signal (e.g., a video recording) can be stored in a memory 26 of the camera 10. In some cases, the image sensor 22 can be provided as part of the control printed circuit board 18, although this is not required. The control printed circuit board 18 can include a processor or controller 20. Although some components are described as part of the control printed circuit board 18, these components can be provided separately from the control printed circuit board 18. In some cases, the controller 20 can be configured to poll various sensors for data, analyze sensor data, and determine when the camera 10 has been tampered with. The controller 20 can also be in communication with or operatively coupled to the memory 26. The memory 26 can be used to store any desired information, such as, but not limited to, machine instructions for how to process data from sensors and / or digital signals from image sensors. The memory 26 can be any suitable type of storage device, including, but not limited to, RAM, ROM, EPROM, flash memory, hard drive, etc. In some cases, controller 20 and / or image sensor 22 may be able to store information within memory 26 and may later be able to retrieve the stored information from memory 26 .

[0034] In some embodiments, the camera 10 can be equipped with a communication module 24. The communication module 24 can allow the camera to communicate with other components of the security system, such as, but not limited to, a network video recorder (NVR) and / or a remote monitoring station. The communication module 24 can provide wired and / or wireless communication. In one example, the communication module 24 can use any desired wireless communication protocol, such as, but not limited to, cellular communication, ZigBee, REDLINK, or the like, as desired. TM , Bluetooth, WiFi, IrDA, Dedicated Short Range Communication (DSRC), EnOcean, and / or any other suitable public or proprietary wireless protocol. In another example, the communication module 24 can communicate via a network cable 28. In some cases, the network cable 28 can be a Power over Ethernet (POE) cable. The exemplary camera 10 can receive power as desired via a POE cable, a separate power cable 32, a battery, or any other suitable power source.

[0035] The exemplary camera 10 can also include a rear frame 30. The rear frame 30 can be mounted to the housing 12 to mount the camera 10 to a wall or ceiling. In some cases, the rear frame 30 can be coupled to the outside of the housing 12, while in other cases, the rear frame 30 can be within or internal to the housing 12. In some cases, the rear frame 30 can accommodate cable connections. For example, the rear frame 30 can accommodate connections such as between the network cable 28 and the control printed circuit board 18, between the power cable 32 and the control printed circuit board 18, and / or between the audio cable 34 and the control printed circuit board 18. It is contemplated that the camera 10 can include other cables and / or connections as desired. In some cases, the connection between the camera 10 and the network can be tested using the internal circuitry of the connection port within the rear frame 30. The port can include LEDS that illuminate in a certain color to indicate connectivity.

[0036] In some embodiments, the camera 10 can include an alignment mechanism 38, which can be a structural tampering sensor configured to detect structural tampering with the camera 10. The alignment mechanism 38 can include a plurality of interconnected wires or tubes 40 and screws 42 (or other fixing mechanisms) configured to maintain the desired orientation between the dome 14, the lens 16, the control printed circuit board 18 and / or the rear frame 30. The alignment mechanism 38 can extend from the dome 14 (or the first end of the housing 12) to the rear frame 30 (or the second end of the housing 12), and can form a circuit. The alignment mechanism 38 can be connected to the control printed circuit board 18, and a micro switch (not explicitly shown) can indicate the breakage or damage of any part of the alignment mechanism 38 circuit. If the circuit is disconnected due to any mechanical impact or disassembly of the camera 10, the switch can indicate the disconnection of the circuit and can send an alarm signal. The alarm can be captured by the controller 20 and sent to the user. More generally, the alignment mechanism 38 can form a circuit monitored by the controller 20, and when the camera is tampered with and disassembled or structurally damaged, the circuit detected by the controller 20 can be disconnected. In some cases, at least a portion of the circuit can include mounting elements that must be removed to disassemble the camera 10. Thus, removing the mounting screws may cause the circuit to become open and activate an alarm.

[0037] Although the camera 10 is described as providing a video stream, in some cases, the camera 10 can be a still camera that captures static images, possibly on a specific schedule or in response to detected motion. In either case, the image or video stream captured by the camera 10 can be transmitted to a server. In some cases, the server can provide a real-time video stream to a workstation or other remote device, and can store or archive part or all of the video stream for later viewing. The server can be a cloud server, but this is not necessary in all cases. The server can represent a single computer, or the server can represent a large number of computers networked together. The camera 10 can be hardwired to a device such as a computer, a router, a modem, or a gateway that communicates with the server itself. Alternatively or in addition, the camera 10 can communicate wirelessly with the server.

[0038] The workstation or remote device can communicate with the server so that the images or video streams captured by the camera 10 can be accessed and viewed on the workstation and / or remote device. In some cases, the workstation and / or remote device can be used to control the camera 10, or adjust the camera 10. In some cases, the workstation and / or remote device can provide a method for individuals such as security personnel to view the footage captured by the camera 10, either alone or in combination. In some cases, the camera 10 can communicate with a remote monitoring station, which can be a server or any other suitable device.

[0039] Figure 2 for Figure 1 1 is a schematic diagram of an exemplary camera 10 in which a plurality of functional tamper detection sensors 44a-e (collectively referred to as 44) are configured to detect interference with the function of the camera 10. Each of the sensors 44 can be communicatively coupled to the controller 20 (e.g., wired or wireless communication). As will be described in more detail herein, the tamper detection sensors 44 can each provide a sensed value to the controller 20. Figure 2 Many different types of tamper detection sensors are contemplated and described. It is contemplated that the camera 10 can be provided with any combination of tamper detection sensors (e.g., less than all) or all of the tamper detection sensors, as desired. The tamper detection sensor 44 can be small, low-cost, and require less processing power to identify tampering than video analytics. Although the sensor 44 is described as a tamper detection sensor, the sensor 44 can also be used to detect a measure of wear and tear on the camera 10 in order to proactively predict necessary maintenance and / or replacement before the camera 10 loses functionality.

[0040] The first tamper detection sensor can include an ambient light sensor 44a positioned outside of or adjacent to the housing 12. In some cases, the ambient light sensor 44a can be positioned on or adjacent to the dome 14 (or other lens cover). The ambient light sensor 44a can detect the amount of ambient light in the room in which the camera 10 is located or entering the camera 10. It is contemplated that data or sensor values ​​from the ambient light sensor 44a can be used to determine whether there is a light source in the room, whether the view of the camera 10 is blocked (e.g., by placed objects or paint), whether bright light is shining into the lens 16, and the like.

[0041] Another tamper detection sensor can include a vibration sensor 44b. The vibration sensor 44b can be configured to detect when an object contacts the camera 10. For example, if an object is thrown at the camera 10 (or otherwise contacts it) and contacts an area adjacent to the camera 10 or the camera 10 itself, the camera 10 can shake or vibrate. This movement can be detected by the vibration sensor 44b. It is also contemplated that the vibration sensor 44b can alert a user to possible structural damage to the camera 10. In some cases, the vibration sensor 44b can cooperate with the alignment mechanism 38 to determine structural damage. It is also contemplated that the vibration sensor 44b can provide data for detecting small and / or continuous vibrations caused by the environment, which can affect the function of the camera 10 through wear and tear.

[0042] Another tamper detection sensor can include an accelerometer (e.g., a one-dimensional accelerometer or other accelerometer, as desired) 44c. The accelerometer 48 can be attached to or adjacent to the lens 16. It is contemplated that during daily use, the lens 16 can be moved or adjusted to change the focus of the image. However, in some cases, the lens 16 can be moved to intentionally blur the captured image. It is contemplated that accidental movement of the lens 16 can be detected by the accelerometer 44c. It is also contemplated that the accelerometer 44c can provide data for detecting the frequency and / or total amount of movement of the lens 16, which can affect the function of the camera 10 through wear and tear.

[0043] Another tamper detection sensor may be a digital compass 44d. The digital compass 44d may be configured to detect camera movement and / or changes in the camera field of view. For example, the digital compass 44d may be configured to distinguish between the current position of the camera 10 and the position where the camera 10 should be based on the control signal.

[0044] Another tamper detection sensor can be a force sensor, a touch sensor, or a pressure sensor 44e. The force sensor 44e can be coupled to or adjacent to the rear frame 30. The force sensor 44e can be configured to detect an attempt to remove the camera 10 from its mounting location. In some cases, the force sensor 44e can detect an attempt to access the cables 28, 32, 34. For example, if a person attempts to access the network cable 28 by, for example, stripping the insulation coating of the network cable and biting or clamping the device onto the exposed wires (e.g., "vampiring") when attempting to enter the building network, the force sensor 44e can detect an attempt to do so. Similarly, if a person wants to detect that the network can be removed from the cable connector on the rear frame 30, the force sensor 44e can detect an attempt to do so. In some cases, the camera 10 can include a battery that is activated only when the power cable 32 is tampered with or disconnected. It is also contemplated that in some cases, the communication module 24 can communicate wirelessly only when the network cable 28 is tampered with or disconnected (e.g., as identified by the force sensor 44e).

[0045] In some cases, the controller 20 may be configured to issue an alert when the sensor 44e senses that the force applied to the rear frame 30 and / or one or more of the cables 28, 32, 34 exceeds a predetermined standard. For example, the controller 20 can issue an alert when the change in the force measured at the sensor 44e exceeds a predetermined threshold or the force exceeds a predetermined threshold. It is contemplated that a baseline or normal force profile can be determined during a training phase.

[0046] Although not explicitly shown, other tamper detection sensors 44 can be used as desired. For example, in some cases, microphones, temperature sensors, occupancy sensors, motion sensors, etc. can be used as tamper detection sensors 44. This list is not intended to include every sensor that can be used as tamper detection sensor 44, but rather to illustrate some suitable sensors.

[0047] Figure 3Flowchart of an exemplary method 100 for tamper detection. As described above, the camera 10 can be installed with the included tamper detection sensor 44 and / or alignment mechanism 38. During installation or for a period of time thereafter, data from the sensor 44 can be collected to establish normal sensor values ​​and patterns thereof representing one or more different operating conditions of the environment in which the camera 10 is positioned, as shown in block 102. It is contemplated that the sensor 44 can be placed in a training mode for a period of time sufficient to establish normal values ​​and / or patterns for a variety of different expected conditions. The training mode can be entered repeatedly before and / or after a test or operating cycle. It is contemplated that the controller 20 can be programmed to automatically initiate a training cycle at predefined intervals (e.g., every few hours, every few days, every few weeks, etc.). For example, if the camera 10 is installed in a bank, it can be expected that the ambient light sensor 44 senses a certain level of light during normal business hours, and senses less light or even no light after business hours, on weekends and / or holidays. In another example, if a piece of equipment in the environment, such as a fan, machine, or other device, causes the camera 10 to vibrate with a specific frequency spectrum, and in some cases for a specific duration, the vibration sensor 44b can sense the vibration in the training mode and establish the specific vibration as a normal value and / or normal pattern. These are just examples.

[0048] It is contemplated that the camera 10 can be placed into a training mode as desired via a command issued through a remote device or via a training mode button or switch or other mechanism directly on the camera 10. It is contemplated that establishing a normal sensor value pattern can help the controller 20 determine, for example, whether a reduction in ambient light is due to a light source being turned off or dimmed (e.g., expected or normal behavior) or due to an object blocking the lens 16 (e.g., accidental or tampering).

[0049] See also Figure 4, which shows a flow chart of an exemplary method 200 for establishing a normal mode. The training mode can begin with a user configuring the time interval between data points (e.g., the sample acquisition rate), as shown in block 202. It is contemplated that the user can configure the sampling rate using a remote device (e.g., a PC, laptop, tablet, smart phone, etc.) that communicates with the controller 20 of the camera 10 (e.g., via the communication module 24). The various sensors 44 can have the same data sampling rate or different data sampling rates as desired. For example, data can be collected every millisecond, every second, every 5 seconds, every 15 seconds, every 30 seconds, every 1 minute, every 5 minutes, or any other suitable sampling period. Once the sampling rate is configured, the controller 20 can begin capturing data from the sensors 44 by repeatedly polling the sensors 44 at the specified sampling rate, as shown in block 204. When the controller 20 captures the sensor data, the sensor data can be classified as normal or regular data or as special date / time (e.g., night, weekend, holiday, etc.) data, as shown in block 206. The classification can be stored in the memory 26 along with the sensor data, as shown in block 208. The sensor data can also be stored as a pattern with other related information, such as, but not limited to, the time when the sensor data was collected, the day of the year (which can be correlated with local sunrise and sunset data), etc. In some cases, the normal sensor data pattern can be captured over a period of time so as to include expected changes in environmental conditions in or around the camera 10. It is also contemplated that the camera 10 can be placed in a training mode at predefined intervals in response to frequent occurrences of false alarms, in response to repositioning of the camera 10, reshaping of the environment in which the camera 10 is placed, or other factors that may modify or change the normal sensor pattern.

[0050] In some cases, the data pattern may be sensor readings associated with a predetermined time period or window, such as 5 seconds, 15 seconds, one minute, 5 minutes, 10 minutes, etc. Figure 6Described in more detail, data patterns can overlap. For example, the beginning of a data pattern can occur at half of the previous data pattern, but this is not necessary. In some cases, data from two or more sensors 44 can be combined into a vector, which represents the state of the camera 10 at a given time. For example, the controller 20 can be configured to obtain data readings from a time point and form a vector representing the camera 10 at the given time point. In some cases, continuous vectors can be grouped into time windows (or time periods) to form a pattern for comparison. Therefore, the data pattern can represent a single sensor (for example, a plurality of sensor values ​​form a pattern) or a combination of sensors (for example, a plurality of vectors form a pattern). For example, a group of normal sensor values ​​of a structural tampering detection sensor 38 and / or one or more functional tampering detection sensors can be represented as a normal vector. It can be imagined that, as required, the camera 10 can be placed in a training mode to capture data of a special date or as regular data of normal daily changes.

[0051] return Figure 3 Once the normal mode and vectors have been established (e.g., for normal days and / or special days), the camera 10 can be placed in an operational mode, as shown in block 104. The camera 10 can be placed in an operational mode via a command issued through a remote device or via an operational mode button or switch directly on the camera 10 or any other suitable mechanism, as desired.

[0052] Once in the operating mode, the sensor 44 can begin collecting data at predetermined intervals by repeatedly polling each of the sensors 44, as shown in block 106. The controller 20 can also verify that the circuit of the alignment mechanism is still intact to verify the structural integrity of the camera 10. It is contemplated that the predetermined time intervals for the operating mode can be the same as the predetermined time intervals (e.g., data sampling rates) for the training mode. After the data is collected, it is transmitted to the controller 20, as shown in block 108. The controller 20 can be configured to compare the current sensor values ​​with the normal sensor values ​​collected during the training mode using a mode change algorithm, as shown in block 110. In some cases, the controller 20 can be configured to group the current sensor values ​​into patterns in a manner similar to the training mode. For example, a data pattern can be a sensor reading associated with a predetermined length of time, such as more than 5 seconds, 15 seconds, one minute, 5 minutes, 10 minutes, etc. The controller 20 can also be configured to associate a time of day, a day of the week, data classification as regular or special data, etc. with the currently collected data. In some cases, current data collected from two or more sensors 44 can be combined into a vector that represents the state of the camera 10 at a given time. For example, the controller 20 can be configured to take data readings from a point in time and form a vector representing the camera 10 at that given point in time. A set of current sensor values ​​of the structural tamper detection sensor 38 and / or one or more functional tamper detection sensors can be represented as a sensing vector. In some cases, consecutive vectors can be grouped into time windows (or time periods) to form a pattern for comparison.

[0053] The controller 20 can then identify whether there is a difference or change between the current or operational sensor data and the normal sensor data, as also shown at block 110. In some cases, the controller 20 can compare the sensed vector to a previously acquired normal vector. The controller 20 can use any vector comparison method, such as, but not limited to, a distance metric that can include Mahalanobis distance, Euclidean distance, etc. The controller 20 can then compare the current sensor data to normal sensor data of the same classification, the same day of the week, the same time of the day, etc., to identify or determine whether there is a change in sensor values, patterns, and / or vectors, as shown in block 112. The controller 20 can determine whether the difference in the distance metric (e.g., Mahalanobis distance, Euclidean distance, etc.) between the normal and operational sensor vectors is greater than a predetermined value or range of values. If the controller 20 determines that there is no difference (e.g., less than a predetermined threshold difference), the controller 20 determines that the camera 10 has not been tampered with, as shown in block 114. The process continues, and the controller 20 continues to poll the data of the sensor 44, as shown in block 106.

[0054] Returning to block 112, if the controller 20 determines that a difference exists (e.g., greater than a predetermined threshold difference), the controller 20 can determine whether the difference satisfies one or more predetermined criteria. The one or more predetermined criteria can be that the current sensor value exceeds a predetermined threshold difference in each of at least "N" polls of the plurality of tamper detection sensors within a predetermined amount of time, where "N" is an integer greater than 1. For example, if the controller 20 determines that a difference exists (e.g., greater than a predetermined threshold difference), the controller 20 increments a counter of the number of times the difference occurred, as shown in block 116. For example, when no difference has been identified (e.g., less than a predetermined threshold difference), the counter will be at N=0. When a difference has been identified (e.g., greater than a predetermined threshold difference), the counter is incremented by 1 so that N is now equal to 1 (e.g., 0+1). The counter can track the number of differences or changes that have been identified within a predetermined period of time. The controller 20 can then compare the number of changes within a predetermined time period (e.g., N) to a threshold number of changes (Th) (e.g., a predetermined minimum number of changes within a predetermined time period), as shown in block 118. The threshold number of changes can be determined by the user and any desired number, such as, but not limited to, one, two, three, four, or more. Similarly, the predetermined length of time over which changes can occur can also be determined by the user.

[0055] If N is less than the change count threshold, the controller 20 determines that the camera 10 has not been tampered with, and the process continues with the controller 20 continuing to poll the sensor 44 for data, as shown in block 106. If N is greater than the change count threshold, the controller 20 can determine that the camera 10 has been tampered with and can generate an alert, as shown in block 120. Although the method 100 refers to the sensor 44, it should be understood that the controller 20 can simultaneously determine whether a break has occurred in the circuit of the alignment mechanism 38. Anomalies in the alignment mechanism can be added to the change counter or counted separately.

[0056] In some embodiments, generating an alert can send a notification to a remote device (e.g., a security monitoring station, a central server, a network video recorder, a mobile phone, etc.). Alternatively or in addition, the alert can be sent directly to a law enforcement agency. In some cases, the alert can be an audible (e.g., a siren or buzzer) or a visual alert (e.g., a flashing light) from the camera 10 itself. It is contemplated that only issuing an alert when a threshold number of differences or changes occur within a predetermined period of time can help prevent false alarms that do not provide an alert when experiencing minor sensor changes (e.g., anomalies) and random changes that affect sensor patterns.

[0057] Figure 5Flowchart of an exemplary method 300 for tamper detection with respect to a particular sensor. The method 300 is described with respect to a particular light sensor 44a, but it should be understood that any sensor 44 or combination of sensors can be used. To this end, the controller 20 can collect operational sensor data or values ​​from, for example, the light sensor 44a, as shown in block 302. The sensor values ​​can be collected at predefined intervals. When the sensor values ​​are collected, the controller 20 can extract a pattern of one or more values ​​or vectors at one or more time points corresponding to a time window (e.g., a predetermined duration), as shown in block 304.

[0058] Figure 6 Block diagram 400 of illustrative sensor mode and analysis is shown. Single sampled sensor value is represented at 402, wherein each square represents the sensor value at the corresponding sampling time. These sensor values ​​402 can be single values ​​or converted to vectors. In the example shown, sensor value 402 is grouped into time windows 404a, 404b (collectively referred to as 404). In an exemplary embodiment, the first four sensor values ​​402a are grouped into first window 404a. Second window 404b can also include 4 values ​​and overlap with the first window so that the third value and the fourth value are in both first window 404a and second window 404b. Window 404 can include any desired number of sensor data points. Using four data points is only an example. It can be imagined that overlapping window 404 can improve the stability of tampering detection system by providing more accurate output and reducing the unintentional omission of data points. However, in some cases, window 404 may not overlap. As described herein, pattern changes in each window 404 of consecutive windows or a specified number of windows 404 within a specific time interval can be identified or marked as tampering. More than one such marking can confirm tampering and an alert has been generated.

[0059] return Figure 5 , the controller 20 can then compare the operating mode to the normal pattern for the same type of date or similar time determined during the training phase, as shown at block 306. In some cases, the comparison can be performed using a vector distance calculation. Figure 6 , a comparison operation can be performed between the operational window lengths 404a, 404b and the normal mode time windows 406a, 406b. The normal mode time windows 406a, 406b can have the same length, the same number of data points, be collected on the same day of the week, at the same (or similar) time of day, and / or include the same type of date classification as the operational data 404a, 404b. Operational data collected during the day on a weekday may be significantly different from normal operational data collected at midnight, so comparing these data will likely result in false alarms.

[0060] It is also contemplated that the length of window 404 can determine the speed at which an alert can be generated. For example, if the time window corresponds to hours, an hour or more may elapse between a tampering event and an alert (particularly if two or more significant changes are required to issue an alert). Thus, time window 404 can be configured by an end user for the particular environment in which the camera is placed (e.g., via a remote device).

[0061] Return again Figure 5 , the controller 20 can be configured to determine whether there is a significant change in the operating data relative to the normal mode, as shown in box 308. The controller 20 can determine whether a significant change in the distance metric (e.g., Mahalanobis distance, Euclidean distance, etc.) between the normal and operating sensor vectors is greater than a predetermined value or range of values. If there is no significant change, the controller 20 can return to box 302 and repeat the process. If there is a significant change, the controller 20 can determine whether there is a threshold number of consecutive significant changes (e.g., a significant change in each window of a predetermined number of consecutive windows). If the number of consecutive significant changes exceeds the threshold, an alert can be sent, such as Figure 5 Box 310 and Figure 6 As shown by arrow 408 in FIG.

[0062] Although several illustrative embodiments of the present disclosure have been described in this manner, it will be readily understood by those skilled in the art that other embodiments may be made and used within the scope of the claims appended hereto. However, it should be understood that the present disclosure is in many respects merely illustrative. Details (especially details related to shape, size, arrangement of parts, and exclusion and order of steps) may be changed without exceeding the scope of the present disclosure. Of course, the scope of the present disclosure is defined in the language in which the appended claims are expressed.

Claims

1. A camera for use in a security system, the camera comprising: A housing, the housing being used to accommodate a plurality of components, the plurality of components comprising: Image sensor; a lens for directing incident light toward the image sensor; a plurality of tamper detection sensors, each of the plurality of tamper detection sensors providing a sensed value; a controller operatively coupled to the image sensor and the plurality of tamper detection sensors; a memory operatively coupled to the controller, the controller configured to enter a training mode (training period) and establish a set of normal sensor values ​​for the plurality of tamper detection sensors during the training period, at least one of the normal sensor values ​​for at least one of the tamper detection sensors comprising a normal sensor pattern over time; The controller is configured to store normal sensor values ​​of the plurality of tamper detection sensors established during the training in a memory, The controller is configured to enter an operational mode, and once in the operational mode, repeatedly poll each of the plurality of tamper detection sensors to receive a set of current sensor values, and compare the set of current sensor values ​​to the set of normal sensor values ​​established during stored training and identify one or more differences; and The controller is configured to issue an alert when the identified one or more differences meet one or more predetermined criteria.

2. The camera of claim 1, wherein the training period occurs during one or more time periods representing one or more different operating conditions.

3. The camera of claim 1 , wherein the one or more predetermined criteria include the one or more differences exceeding a threshold difference in response to each of the plurality of tamper detection sensors being polled at least “N” times within a predetermined amount of time, wherein “N” is an integer greater than 1.

4. The camera of claim 1, wherein the normal sensor pattern over time includes expected changes in environmental conditions in or around the camera.

5. The camera of claim 1 , wherein the plurality of tamper detection sensors comprises: One or more structural tampering detection sensors for detecting structural tampering of the camera, each of the one or more structural tampering detection sensors providing a sensing value; and One or more function tampering detection sensors are used to detect function tampering of the camera, and each of the one or more function tampering detection sensors provides a sensing value.

6. The camera according to claim 5, wherein the controller being operatively coupled to the one or more structural tamper detection sensors and the one or more functional tamper detection sensors; the memory storing a set of normal sensor values ​​for the one or more structural tamper detection sensors and the one or more functional tamper detection sensors, wherein at least one of the normal sensor values ​​for at least one of the functional tamper detection sensors comprises a normal sensor pattern over time; the controller being configured to repeatedly poll each of the one or more structural tamper detection sensors and each of the one or more functional tamper detection sensors to receive a set of current sensor values ​​and compare the set of current sensor values ​​to the set of stored normal sensor values ​​and identify one or more differences; and The controller is configured to issue an alert when the identified one or more differences meet one or more predetermined criteria.

7. The camera of claim 6 , wherein the one or more structural tamper detection sensors include electrical contacts that form a circuit monitored by the controller when the camera is assembled, and that become disengaged when the camera is disassembled due to tampering, thereby breaking the circuit detected by the controller.

8. The camera of claim 6, wherein the one or more functional tamper detection sensors include one or more of an ambient light sensor, a vibration sensor, an accelerometer, a digital compass, and a touch sensor.

9. The camera according to claim 1, comprising: one or more connectors housed by the housing and operatively coupled to the controller, the one or more connectors being accessible from outside the housing and configured to selectively connect to one or more cables of a security system; a force sensor operatively connected to the controller, the force sensor configured to sense a force applied to one or more of the connectors; and The controller is configured to issue an alert when the sensor senses that a force applied to one or more of the connectors meets one or more predetermined criteria.

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