Systems and methods for security camera control

Abstract

Disclosed are systems and methods that provide a novel framework for centralized security management of a location. The disclosed framework provides non-native functionality to a security system that enables the capture of event data (e.g., security camera footage, such as the images and / or video clips captured via an associated camera) via mechanisms that are tied to and / or enabled by the corresponding environment for which it is executing. The framework is configured to toggle between operational modes based on criteria (e.g., time, date, activity, weather, light exposure, and the like). This can enable the security camera to capture high-quality events, which can correlate to the detection of previously undetectable events as well as the capture of event imagery at a higher quality (e.g., 4K, for example) than current systems are capable of.

Description

SYSTEMS AND METHODS FOR SECURITY CAMERA CONTROLCROSS-REFERENCED APPLICATION

[0001] This application claims the benefit of, and priority to, U.S. Provisional Patent Application No. 63 / 609,609. filed December 13, 2023, its entirety’ of which is incorporated herein by reference.FIELD OF THE DISCLOSURE

[0002] The present disclosure is generally related to a location monitoring system, and more particularly, to a decision intelligence (Dl)-based computerized framework for automatically and dynamically managing mechanisms for which a security system captures events at and / or around a location.BACKGROUND

[0003] Conventional security systems are equipped to secure a location (e.g., home, office, building, yard, garage, patio, and the like) against unwanted activity. For example, such activities can involve break-ins, trespassing, and the like.SUMMARY OF THE DISCLOSURE

[0004] Current security systems, however, are limited in the manner in which they can detect and / or capture events. For example, at night, security’ systems can utilize color night vision; however, such night vision requires the use of a spotlight or other light emitting device. This, among other drawbacks, can lead to unwanted security activity, inclusive of the use of the spotlight, which can prevent such systems from properly, efficiently and accurately capturing events and / or preventing unwanted activity (e.g., triggering an alarm, for example).

[0005] Accordingly, as discussed herein, the disclosed framework provides non-native functionality to a security system that enables the capture of event data (e.g., security camera footage, such as the images and / or video clips captured via an associated camera) via mechanisms that are tied to and / or enabled by the corresponding environment for which it is executing. The disclosed framew ork is configured to toggle between operational modes based on criteria (e.g., time, date, activity, weather, light exposure, and the like). This can enable the security camera to capture high-quality events, which can correlate to the detection ofpreviously undetectable events as well as the capture of event imagery' at a higher quality (e.g.. 4K. for example) than current systems are capable of.

[0006] By way of a non-limiting example, a security camera may be configured so that when the sun sets or the environment is dark or dimly lit, the camera can toggle to, for example, infrared night mode. Therefore, upon detection of an event (e.g., motion detection, person detection, object detection, sound detection, and the like or some combination thereof), a security camera can automatically switch over from infrared night mode to color night mode. In some embodiments, the camera can toggle modes based on the environment for which it is operating and / or upon the detection of an event. Thus, in some embodiments, when the sun sets, in the above example, the camera can toggle to infrared night mode; and in some embodiments, the camera can toggle upon the detection of the event after the sun sets, as discussed in more detail below.

[0007] According to some embodiments, a method is disclosed for a Dl-based computerized framework for automatically and dynamically managing mechanisms for which a security system captures events at and / or around a location. In accordance with some embodiments, the present disclosure provides a non-transitory computer-readable storage medium for carrying out the above-mentioned technical steps of the framework’s functionality. The non-transitory' computer-readable storage medium has tangibly stored thereon, or tangibly encoded thereon, computer readable instructions that when executed by a device cause at least one processor to perform a method for automatically and dynamically managing mechanisms for which a security system captures events at and / or around a location.

[0008] In accordance with one or more embodiments, a system is provided that includes one or more processors and / or computing devices configured to provide functionality' in accordance with such embodiments. In accordance with one or more embodiments, functionality is embodied in steps of a method performed by at least one computing device. In accordance with one or more embodiments, program code (or program logic) executed by a processor(s) of a computing device to implement functionality in accordance with one or more such embodiments is embodied in, by and / or on a non-transitory computer-readable medium.DESCRIPTIONS OF THE DRAWINGS

[0009] The features, and advantages of the disclosure will be apparent from the following description of embodiments as illustrated in the accompanying drawings, in which reference characters refer to the same parts throughout the various views. The drawings are notnecessarily to scale, emphasis instead being placed upon illustrating principles of the disclosure:

[0010] FIG. 1 is a block diagram of an example configuration within which the systems and methods disclosed herein could be implemented according to some embodiments of the present disclosure;

[0011] FIG. 2 is a block diagram illustrating components of an exemplary’ system according to some embodiments of the present disclosure;

[0012] FIG. 3 illustrates an exemplary workflow according to some embodiments of the present disclosure;

[0013] FIG. 4 depicts an exemplary implementation of an architecture according to some embodiments of the present disclosure;

[0014] FIG. 5 depicts an exemplary implementation of an architecture according to some embodiments of the present disclosure; and

[0015] FIG. 6 is a block diagram illustrating a computing device showing an example of a client or server device used in various embodiments of the present disclosure.DETAILED DESCRIPTION

[0016] The present disclosure will now be described more fully hereinafter with reference to the accompanying drawings, which form a part hereof, and which show, by way of non-limiting illustration, certain example embodiments. Subject matter may. however, be embodied in a variety of different forms and, therefore, covered or claimed subject matter is intended to be construed as not being limited to any example embodiments set forth herein; example embodiments are provided merely to be illustrative. Likewise, a reasonably broad scope for claimed or covered subject matter is intended. Among other things, for example, subject matter may be embodied as methods, devices, components, or systems. Accordingly, embodiments may, for example, take the form of hardware, software, firmware or any combination thereof (other than software per se). The following detailed description is, therefore, not intended to be taken in a limiting sense.

[0017] Throughout the specification and claims, terms may have nuanced meanings suggested or implied in context beyond an explicitly stated meaning. Likewise, the phrase “in one embodiment'’ as used herein does not necessarily refer to the same embodiment and the phrase “in another embodiment'’ as used herein does not necessarily refer to a different embodiment.It is intended, for example, that claimed subject matter include combinations of example embodiments in whole or in part.

[0018] In general, terminology may be understood at least in part from usage in context. For example, terms, such as “and”, “or”, or “and / or,” as used herein may include a variety of meanings that may depend at least in part upon the context in which such terms are used. Typically, “or” if used to associate a list, such as A, B or C, is intended to mean A, B. and C, here used in the inclusive sense, as well as A, B or C, here used in the exclusive sense. In addition, the term “one or more” as used herein, depending at least in part upon context, may be used to describe any feature, structure, or characteristic in a singular sense or may be used to describe combinations of features, structures or characteristics in a plural sense. Similarly, terms, such as “a,” “an,” or “the,” again, may be understood to convey a singular usage or to convey a plural usage, depending at least in part upon context. In addition, the term “based on” may be understood as not necessarily intended to convey an exclusive set of factors and may, instead, allow for existence of additional factors not necessarily expressly described, again, depending at least in part on context.

[0019] The present disclosure is described below with reference to block diagrams and operational illustrations of methods and devices. It is understood that each block of the block diagrams or operational illustrations, and combinations of blocks in the block diagrams or operational illustrations, can be implemented by means of analog or digital hardware and computer program instructions. These computer program instructions can be provided to a processor of a general purpose computer to alter its function as detailed herein, a special purpose computer, ASIC, or other programmable data processing apparatus, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, implement the functions / acts specified in the block diagrams or operational block or blocks. In some alternate implementations, the functions / acts noted in the blocks can occur out of the order noted in the operational illustrations. For example, two blocks shown in succession can in fact be executed substantially concurrently or the blocks can sometimes be executed in the reverse order, depending upon the functionality / acts involved.

[0020] For the purposes of this disclosure a non-transitory computer readable medium (or computer-readable storage medium / media) stores computer data, which data can include computer program code (or computer-executable instructions) that is executable by a computer, in machine readable form. By way of example, and not limitation, a computer readable medium may include computer readable storage media, for tangible or fixed storage of data, orcommunication media for transient interpretation of code-containing signals. Computer readable storage media, as used herein, refers to physical or tangible storage (as opposed to signals) and includes without limitation volatile and non-volatile, removable and nonremovable media implemented in any method or technology for the tangible storage of information such as computer-readable instructions, data structures, program modules or other data. Computer readable storage media includes, but is not limited to, RAM. ROM, EPROM, EEPROM, flash memory or other solid state memory technology, optical storage, cloud storage, magnetic storage devices, or any other physical or material medium which can be used to tangibly store the desired information or data or instructions and which can be accessed by a computer or processor.

[0021] For the purposes of this disclosure the term ‘"server” should be understood to refer to a service point which provides processing, database, and communication facilities. By way of example, and not limitation, the term “server” can refer to a single, physical processor with associated communications and data storage and database facilities, or it can refer to a networked or clustered complex of processors and associated network and storage devices, as well as operating software and one or more database systems and application software that support the services provided by the server. Cloud servers are examples.

[0022] For the purposes of this disclosure a “network” should be understood to refer to a network that may couple devices so that communications may be exchanged, such as between a server and a client device or other types of devices, including between wireless devices coupled via a wireless network, for example. A network may also include mass storage, such as network attached storage (NAS), a storage area network (SAN), a content delivery network (CDN) or other forms of computer or machine-readable media, for example. A network may include the Internet, one or more local area networks (LANs), one or more wide area networks (WANs), wire-line type connections, wireless type connections, cellular or any combination thereof. Likewise, sub-networks, which may employ differing architectures or may be compliant or compatible with differing protocols, may interoperate within a larger network.

[0023] For purposes of this disclosure, a “wireless network” should be understood to couple client devices with a network. A wireless network may employ stand-alone ad-hoc networks, mesh networks, Wireless LAN (WLAN) networks, cellular networks, or the like. A wireless network may further employ a plurality of network access technologies, including Wi-Fi, Long Term Evolution (LTE), WLAN, Wireless Router mesh, or 2nd, 3rd, 4thor 5thgeneration (2G, 3G, 4G or 5G) cellular technology, mobile edge computing (MEC), Bluetooth, 802.1 Ib / g / n, orthe like. Network access technologies may enable wide area coverage for devices, such as client devices with varying degrees of mobility, for example.

[0024] In short, a wireless network may include virtually any type of wireless communication mechanism by which signals may be communicated between devices, such as a client device or a computing device, between or within a network, or the like.

[0025] A computing device may be capable of sending or receiving signals, such as via a wired or wireless network, or may be capable of processing or storing signals, such as in memory as physical memory states, and may, therefore, operate as a server. Thus, devices capable of operating as a server may include, as examples, dedicated rack-mounted servers, desktop computers, laptop computers, set top boxes, integrated devices combining various features, such as two or more features of the foregoing devices, or the like.

[0026] For purposes of this disclosure, a client (or user, entity, subscriber or customer) device may include a computing device capable of sending or receiving signals, such as via a wired or a wireless network. A client device may, for example, include a desktop computer or a portable device, such as a cellular telephone, a smart phone, a display pager, a radio frequency (RF) device, an infrared (IR) device a Near Field Communication (NFC) device, a Personal Digital Assistant (PDA), a handheld computer, a tablet computer, a phablet, a laptop computer, a set top box, a wearable computer, smart watch, an integrated or distributed device combining various features, such as features of the forgoing devices, or the like.

[0027] A client device may vary in terms of capabilities or features. Claimed subject matter is intended to cover a wide range of potential variations, such as a w eb-enabled client device or previously mentioned devices may include a high-resolution screen (HD or 4K for example), one or more physical or virtual keyboards, mass storage, one or more accelerometers, one or more gyroscopes, global positioning system (GPS) or other location-identifying type capability, or a display with a high degree of functionality, such as a touch-sensitive color 2D or 3D display, for example.

[0028] Certain embodiments and principles will be discussed in more detail with reference to the figures. With reference to FIG. 1, system 100 is depicted which includes user equipment (UE) 102 (e.g., a client device, as mentioned above and discussed below in relation to FIG. 7), network 104, cloud system 106, database 108, sensors 110 and camera engine 200. It should be understood that while system 100 is depicted as including such components, it should not be construed as limiting, as one of ordinary skill in the art w ould readily understand that varying numbers of UEs, peripheral devices, sensors, cloud systems, databases and networks can beutilized; however, for purposes of explanation, system 100 is discussed in relation to the example depiction in FIG. 1.

[0029] According to some embodiments, UE 102 can be any type of device, such as, but not limited to, a mobile phone, tablet, laptop, sensor, Internet of Things (loT) device, autonomous machine, camera, and any other device equipped with a cellular or wireless or wired transceiver.

[0030] For example, UE 102 can be a security camera operating as part of a security system for a location (e.g., a video doorbell camera, WiFi security camera, wireless indoor / outdoor camera, and the like), as discussed herein. In another example, UE 102 can be a security panel for the security system, which connects to and / or controls a security camera (e g., another UE and / or sensor 110, discussed infra).

[0031] In some embodiments, peripheral device (not shown) can be connected to UE 102, and can be any type of peripheral device, such as, but not limited to, a camera, printer, speaker, sensor, and the like. In some embodiments, peripheral device can be any type of device that is connectable to UE 102 via any type of known or to be known pairing mechanism, including, but not limited to, WiFi, Bluetooth™, Bluetooth Low' Energy (BLE), NFC, and the like. For example, the peripheral device can be a camera (e.g., sensor 110) that connectively pairs with UE 102, which is the security control panel and / or a user's smart phone.

[0032] According to some embodiments, sensors 110 (or sensor devices 110) can correspond to any type of device, component and / or sensor associated with a location of system 100 (referred to, collectively, as ‘’sensors”). In some embodiments, the sensors 110 can be any type of device that is capable of sensing and capturing data / metadata related to a user and / or activity of the location. For example, the sensors 110 can include, but not be limited to. cameras, motion detectors, door and window contacts, heat and smoke detectors, passive infrared (PIR) sensors, time-of-flight (ToF) sensors, and the like.

[0033] In some embodiments, the sensors 110 can be associated with devices associated with the location of system 100, such as, for example, lights, smart locks, garage doors, smart appliances (e.g., thermostat, refrigerator, television, personal assistants (e.g.. Alexa®, Nest®, for example)), smart phones, smart watches or other wearables, tablets, personal computers, and the like, and some combination thereof. For example, the sensors 110 can include the sensors on UE 102 (e.g., smart phone) and / or peripheral device (e.g., a paired smart watch). In another example, sensors 110 can correspond to the sensors on a user’s smart phone.

[0034] In some embodiments, network 104 can be any type of network, such as, but not limited to, a wireless network, cellular network, the Internet, and the like (as discussed above). Network 104 facilitates connectivity of the components of system 100, as illustrated in FIG. 1.

[0035] According to some embodiments, cloud system 106 may be any type of cloud operating platform and / or network based system upon which applications, operations, and / or other forms of network resources may be located. For example, system 106 may be a service provider and / or network provider from where services and / or applications may be accessed, sourced or executed from. For example, system 106 can represent the cloud-based architecture associated with location monitoring and / or control system provider (e.g., Resideo®), which has associated network resources hosted on the internet or private network (e.g., network 104), which enables (via engine 200) the location management discussed herein.

[0036] In some embodiments, cloud system 106 may include a server(s) and / or a database of information which is accessible over network 104. In some embodiments, a database 108 of cloud system 106 may store a dataset of data and metadata associated with local and / or network information related to a user(s) of the components of system 100 and / or each of the components of system 100 (e.g., UE 102, sensors 110, and the services and applications provided by cloud system 106 and / or camera engine 200).

[0037] In some embodiments, for example, cloud system 106 can provide a private / proprietary management platform, whereby engine 200, discussed infra, corresponds to the novel functionality system 106 enables, hosts and provides to a network 104 and other devices / platforms operating thereon.

[0038] Turning to FIG. 4 and FIG. 5, in some embodiments, the exemplary' computer-based systems / platforms, the exemplary computer-based devices, and / or the exemplary computer- based components of the present disclosure may be specifically configured to operate in a cloud computing / architecture 106 such as, but not limiting to: infrastructure as a sendee (laaS) 510, platform as a service (PaaS) 508, and / or software as a service (SaaS) 506 using a web browser, mobile app, thin client, terminal emulator or other endpoint 504. FIG. 4 and FIG. 5 illustrate schematics of non-limiting implementations of the cloud computing / architecture(s) in which the exemplary computer-based systems for administrative customizations and control of network-hosted application program interfaces (APIs) of the present disclosure may be specifically configured to operate.

[0039] Turning back to FIG. 1, according to some embodiments, database 108 may correspond to a data storage for a platform (e.g., a network hosted platform, such as cloud system 106, asdiscussed supra) or a plurality of platforms. Database 108 may receive storage instructions / requests from, for example, engine 200 (and associated microservices), which may be in any t pe of known or to be known format, such as, for example, standard query language (SQL). According to some embodiments, database 108 may correspond to any type of known or to be known storage, for example, a memory or memory stack of a device, a distributed ledger of a distributed network (e.g., blockchain, for example), a look-up table (LUT), and / or any other type of secure data repository

[0040] Camera engine 200, as discussed above and further below in more detail, can include components for the disclosed functionality. According to some embodiments, camera engine 200 may be a special purpose machine or processor, and can be hosted by a device on network 104, within cloud system 106 and / or on UE 102. In some embodiments, engine 200 may be hosted by a server and / or set of servers associated with cloud system 106.

[0041] According to some embodiments, as discussed in more detail below, camera engine 200 may be configured to implement and / or control a plurality of services and / or microsen ices, where each of the plurality of services / microservices are configured to execute a plurality of workflows associated with performing the disclosed location management. Non-limiting embodiments of such workflows are provided below in relation to at least FIG. 3.

[0042] According to some embodiments, as discussed above, camera engine 200 may function as an application provided by cloud system 106. In some embodiments, engine 200 may function as an application installed on a servetys), network location and / or other type of network resource associated with system 106. In some embodiments, engine 200 may function as an application installed and / or executing on UE 102 and / or sensors 110 (e.g., an application installed on a security panel, for example). In some embodiments, such application may be a web-based application accessed by UE 102 and / or devices associated with sensors 110 over network 104 from cloud system 106. In some embodiments, engine 200 may be configured and / or installed as an augmenting script, program or application (e.g., a plug-in or extension) to another application or program provided by cloud system 106 and / or UE 102 and / or sensors 110.

[0043] As illustrated in FIG. 2, according to some embodiments, camera engine 200 includes identification module 202, analysis module 204, determination module 206 and control module 208. It should be understood that the engine(s) and modules discussed herein are non- exhaustive. as additional or fewer engines and / or modules (or sub-modules) may be applicable to the embodiments of the systems and methods discussed. More detail of the operations.configurations and functionalities of engine 200 and each of its modules, and their role within embodiments of the present disclosure will be discussed below.

[0044] Turning to FIG. 3, Process 300 provides non-limiting example embodiments for the disclosed location management framework. According to some embodiments, Process 300 provides non-limiting embodiments for the disclosed framework (e.g., via camera engine 200) to control, manage and manipulate the operational status of security components at a location.

[0045] According to some embodiments, Steps 302, 306 and 308 Process 300 can be performed by identification module 202 of camera engine 200; Step 304 and 314-318 can be performed by control module 208; Steps 310 can be performed by analysis module 204; and Step 312 can be performed by determination module 206.

[0046] According to some embodiments, Process 300 begins with Step 302 where engine 200 can collect location data for a location for which a security system is configured to protect. For example, a security system is installed and / or executes to protect a home; therefore, in Step 302, engine 200 can collect environmental information as location data for the home. Such data can include, but is not limited to, sunrise, sunset, light exposure, cloud cover, precipitation, a weather forecast, and the like. In some embodiments, such location data can be collected via sensors 110, discussed in FIG. 1, supra and in some embodiments, such location data can be collected via third party applications (e.g., weather.com or other weather forecasting applications that provide weather and sunrise / sunset data); and in some embodiments, a combination of the two location data sources can be utilized.

[0047] In Step 304, engine 200 can trigger a first mode of the security system. By way of a non-limiting example, for purposes of the discussion of Process 300, the environmental conditions detected in Step 302 correspond to a nigh setting - for example, 10 PM (e.g., no sunlight, and even with the moonlight and / or other lights in / around the location, the available light at the location is at a level for which a spotlight may be required to capture color imagery / frames via a security camera). Thus, in some embodiments, for example, the first mode can be an infrared mode of the security camera (e.g., UE 102 and / or sensors 110, for example).

[0048] In Step 306, engine 200 can perform operations to monitor the location via the first mode. According to some embodiments, a camera in a security system can capture motion by continuously recording images or video frames at a certain rate, typically measured in frames per second (fps). When motion occurs within the camera’s field of view (FOV), several keysteps are involved.

[0049] According to some embodiments, for example, the camera's image sensor can capture still frames or video frames of the scene in its view. Each frame consists of a grid of pixels, with each pixel representing a tiny portion of the scene. The camera’s (e.g., via engine 200, for example) can compare consecutive frames to detect changes - for example, engine 200 can perform an analysis as to how the pixel values change from one frame to the next.

[0050] In some embodiments, engine 200 can apply a motion detection algorithm(s) (e.g.. frame difference algorithm, for example) to the frame comparison data. For example, such algorithms check for significant differences in pixel values between frames (e.g., at or above a threshold level). In some embodiments, if the differences exceed a predefined threshold, such frame(s) can be interpreted as corresponding to motion.

[0051] In Step 308, engine 200 can perform operations to detect an event at / around the location via the security system, which can be performed in line with and / or based on the monitoring from Step 306. In some embodiments, when motion is detected (as in Step 306, supra), engine 200 can trigger various actions, such as, for example, starting to record video. In some embodiments, such event detection can further involve, but is not limited to. sounding an alarm, sending notifications, and the like, which can depend on the security system’s configuration and / or user preferences.

[0052] In some embodiments, the event can be detected based on, but not limited to, image data, video data, audio data, and the like, or some combination thereof.

[0053] In Step 310. event data related to the detected event (e.g., motion detected) can be analyzed. In some embodiments, the event data can correspond to, but is not limited to, frame difference, digital content within each captured / recorded frame, time, date, people / objects detected in the frames, pixel data, and the like, or some combination thereof. Thus, the data / metadata recorded in Step 308 can be analyzed.

[0054] According to some embodiments, the event data can be analyzed via engine 200 implementing / executing any type of known or to be known computational analysis technique, algorithm, mechanism or technology. In some embodiments, the event data can be analyzed based on the location data (e.g., from Step 302). which can provide a reference for whether the mode of the camera’s operation should be toggled from the first mode to a different (e.g., “second”) mode, as discussed infra.

[0055] In some embodiments, engine 200 may execute and / or include a specific trained artificial intelligence / machine learning model (AI / ML), a particular machine learning model architecture, a particular machine learning model type (e.g., convolutional neural network(CNN), recurrent neural network (RNN), autoencoder, support vector machine (SVM), and the like), or any other suitable definition of a machine learning model or any suitable combination thereof.

[0056] In some embodiments, engine 200 may be configured to utilize one or more AI / ML techniques chosen from, but not limited to, computer vision, feature vector analysis, decision trees, boosting, support-vector machines, neural networks, nearest neighbor algorithms, Naive Bayes, bagging, random forests, logistic regression, and the like. By way of a non-limiting example, engine 200 can implement an XGBoost algorithm for regression and / or classification to analyze the event data, as discussed herein.

[0057] In some embodiments and, optionally, in combination of any embodiment described above or below, a neural network technique may be one of. without limitation, feedforward neural network, radial basis function network, recurrent neural network, convolutional network (e.g., U-net) or other suitable network. In some embodiments and, optionally, in combination of any embodiment described above or below, an implementation of Neural Network may be executed as follows: a. define a Neural Network architecture / model, b. transfer the input data to the neural network model, c. train the model incrementally, d. determine the accuracy for a specific number of timesteps, e. apply the trained model to process the newly-received input data. f. optionally and in parallel, continue to train the trained model with a predetermined periodicity.

[0058] In some embodiments and, optionally, in combination of any embodiment described above or below, the trained neural network model may specify a neural network by at least a neural network topology, a series of activation functions, and connection weights. For example, the topology7of a neural network may include a configuration of nodes of the neural network and connections between such nodes. In some embodiments and, optionally, in combination of any embodiment described above or below, the trained neural network model may also be specified to include other parameters, including but not limited to, bias values / functions and / or aggregation functions. For example, an activation function of a node may7be a step function, sine function, continuous or piecewise linear function, sigmoid function, hyperbolic tangent function, or other type of mathematical function that represents a threshold at which the node is activated. In some embodiments and, optionally, in combination of any embodimentdescribed above or below, the aggregation function may be a mathematical function that combines (e.g.. sum, product, and the like) input signals to the node. In some embodiments and. optionally, in combination of any embodiment described above or below, an output of the aggregation function may be used as input to the activation function. In some embodiments and, optionally, in combination of any embodiment described above or below, the bias may be a constant value or function that may be used by the aggregation function and / or the activation function to make the node more or less likely to be activated.

[0059] In Step 312, based on the analysis from Step 310, engine 200 can determine whether to switch to a second mode. For example, the first mode, as discussed above, is infrared night mode; and a second mode can be a color night mode, which can enable the capture of color imager / frames for the event captured in the camera’s FOV.

[0060] In some embodiments, when the determination results in engine 200 determining that infrared night mode (e.g., the first mode) is satisfactory for capturing the event, processing can proceed from Step 312 to Step 318. Accordingly, the event is captured via the first mode, as in Step 318, and monitoring of the location is recursively performed via the first mode. In some embodiments, the capture of the event can be for a time period for which the event (e.g. , motion) is detected.

[0061] By way of a non-limiting example, operation of the camera being maintained via first mode, as in Step 318, can be based on engine 200 determining, but not limited to, a false alarm, non-preferred object (e.g.. the security system is configured to ignore animals, and the motion was that of an animal), enough light at the time of capture (e.g., the street lights and / or other sources of light provided enough lighting to capture necessary' details for a particular type of event), the capture person was a known resident of the home (e.g., via facial recognition technology), infrared data capture is satisfactory for capturing the type of object (e.g., a car, for which the details of the license plate are readily viewable from the infrared image frames, and the like.

[0062] Accordingly, upon performing Step 318, the capture event data, metadata, imagery, frames, and / or clips can be stored in database 108 in association with an account of the location.

[0063] In some embodiments, when Step 312 results in a determination that the second mode is required (e.g., as per system settings upon detecting an event at night, an unrecognized person being captured, and the like, for example), processing can proceed to Step 314, where engine 200 can cause the camera to modily its operational modes from the first mode to the secondmode. For example, camera UE 102, can switch from infrared mode to color night mode, where a sensor 110 can be triggered to emit light to capture the event data.

[0064] And, in Step 316, engine 200 can enable and / or cause the camera to capture the event in the second mode, which can be stored in database 108 in a similar manner as discussed above. As in Step 318, the capture of the event in Step 316 can be for a time period for which the event (e.g., motion) is detected.

[0065] Accordingly, upon performing Step 316, the camera(s), via engine 200, can continue to capture frames and monitor for motion , which can be performed in a similar manner as discussed above. This, among other benefits, allows for real-time monitoring and recording of any ongoing motion events.

[0066] FIG. 6 is a schematic diagram illustrating a client device showing an example embodiment of a client device that may be used within the present disclosure. Client device 600 may include many more or less components than those shown in FIG. 6. However, the components shown are sufficient to disclose an illustrative embodiment for implementing the present disclosure. Client device 600 may represent, for example, UE 102 discussed above at least in relation to FIG. 1.

[0067] As shown in the figure, in some embodiments, Client device 600 includes a processing unit (CPU) 622 in communication with a mass memory' 630 via a bus 624. Client device 600 also includes a power supply 626, one or more network interfaces 650, an audio interface 652. adisplay 654, akeypad 656, an illuminator 658, an input / output interface 660. ahaptic interface 662, an optional global positioning systems (GPS) receiver 664 and a camera(s) or other optical, thermal or electromagnetic sensors 666. Device 600 can include one camera / sensor 666, or a plurality of cameras / sensors 666, as understood by those of skill in the art. Power supply 626 provides power to Client device 600.

[0068] Client device 600 may optionally communicate with a base station (not shown), or directly with another computing device. In some embodiments, network interface 650 is sometimes known as a transceiver, transceiving device, or network interface card (NIC).

[0069] Audio interface 652 is arranged to produce and receive audio signals such as the sound of a human voice in some embodiments. Display 654 may be a liquid crystal display (LCD), gas plasma, light emitting diode (LED), or any other type of display used with a computing device. Display 654 may also include a touch sensitive screen arranged to receive input from an object such as a stylus or a digit from a human hand.

[0070] Keypad 656 may include any input device arranged to receive input from a user. Illuminator 658 may provide a status indication and / or provide light.

[0071] Client device 600 also includes input / output interface 660 for communicating with external. Input / output interface 660 can utilize one or more communication technologies, such as USB, infrared, Bluetooth™, or the like in some embodiments. Haptic interface 662 is arranged to provide tactile feedback to a user of the client device.

[0072] Optional GPS transceiver 664 can determine the physical coordinates of Client device 600 on the surface of the Earth, which typically outputs a location as latitude and longitude values. GPS transceiver 664 can also employ other geo-positioning mechanisms, including, but not limited to, triangulation, assisted GPS (AGPS), E-OTD. CI. SAI, ETA, BSS or the like, to further determine the physical location of client device 600 on the surface of the Earth. In one embodiment, however. Client device 600 may through other components, provide other information that may be employed to determine a physical location of the device, including for example, a MAC address, Internet Protocol (IP) address, or the like.

[0073] Mass memory 630 includes a RAM 632, a ROM 634, and other storage means. Mass memory 630 illustrates another example of computer storage media for storage of information such as computer readable instructions, data structures, program modules or other data. Mass memory 630 stores a basic input / output system (“BIOS”) 640 for controlling low-level operation of Client device 600. The mass memory also stores an operating system 641 for controlling the operation of Client device 600.

[0074] Memory 630 further includes one or more data stores, which can be utilized by Client device 600 to store, among other things, applications 642 and / or other information or data. For example, data stores may be employed to store information that describes various capabilities of Client device 600. The information may’ then be provided to another device based on any of a variety of events, including being sent as part of a header (e.g., index file of the HLS stream) during a communication, sent upon request, or the like. At least a portion of the capability information may also be stored on a disk drive or other storage medium (not shown) within Client device 600.

[0075] Applications 642 may include computer executable instructions which, when executed by Client device 600, transmit, receive, and / or otherwise process audio, video, images, and enable telecommunication with a server and / or another user of another client device. Applications 642 may further include a client that is configured to send, to receive, and / or tootherwise process gaming, goods / services and / or other forms of data, messages and content hosted and provided by the platform associated with engine 200 and its affiliates.

[0076] As used herein, the terms “computer engine” and “engine” identify at least one software component and / or a combination of at least one software component and at least one hardware component which are designed / programmed / configured to manage / control other software and / or hardware components (such as the libraries, software development kits (SDKs), objects, and the like).

[0077] Examples of hardware elements may include processors, microprocessors, circuits, circuit elements (e.g., transistors, resistors, capacitors, inductors, and so forth), integrated circuits, application specific integrated circuits (ASIC), programmable logic devices (PLD), digital signal processors (DSP), field programmable gate array (FPGA), logic gates, registers, semiconductor device, chips, microchips, chip sets, and so forth. In some embodiments, the one or more processors may be implemented as a Complex Instruction Set Computer (CISC) or Reduced Instruction Set Computer (RISC) processors; x86 instruction set compatible processors, multi-core, or any other microprocessor or central processing unit (CPU). In various implementations, the one or more processors may be dual-core processor(s), dual-core mobile processor(s), and so forth.

[0078] Computer-related systems, computer systems, and systems, as used herein, include any combination of hardware and software. Examples of software may include software components, programs, applications, operating system software, middleware, firmware, software modules, routines, subroutines, functions, methods, procedures, software interfaces, application program interfaces (API), instruction sets, computer code, computer code segments, words, values, symbols, or any combination thereof. Determining whether an embodiment is implemented using hardware elements and / or software elements may vary in accordance with any number of factors, such as desired computational rate, power levels, heat tolerances, processing cycle budget, input data rates, output data rates, memory resources, data bus speeds and other design or performance constraints.

[0079] For the purposes of this disclosure a module is a software, hardware, or firmware (or combinations thereof) system, process or functionality, or component thereof, that performs or facilitates the processes, features, and / or functions described herein (with or without human interaction or augmentation). A module can include sub-modules. Software components of a module may be stored on a computer readable medium for execution by a processor. Modulesmay be integral to one or more servers, or be loaded and executed by one or more servers. One or more modules may be grouped into an engine or an application.

[0080] One or more aspects of at least one embodiment may be implemented by representative instructions stored on a machine-readable medium which represents various logic within the processor, which when read by a machine causes the machine to fabricate logic to perform the techniques described herein. Such representations, known as ‘IP cores,” may be stored on a tangible, machine readable medium and supplied to various customers or manufacturing facilities to load into the fabrication machines that make the logic or processor. Of note, various embodiments described herein may, of course, be implemented using any appropriate hardware and / or computing software languages (e.g., C++, Objective-C, Swift, Java, JavaScript, Python, Perl, QT. and the like).

[0081] For example, exemplary software specifically programmed in accordance with one or more principles of the present disclosure may be downloadable from a network, for example, a website, as a stand-alone product or as an add-in package for installation in an existing software application. For example, exemplary software specifically programmed in accordance with one or more principles of the present disclosure may also be available as a client-server software application, or as a web-enabled software application. For example, exemplary software specifically programmed in accordance with one or more principles of the present disclosure may also be embodied as a software package installed on a hardware device.

[0082] For the purposes of this disclosure the term “user”, “subscriber” “consumer” or “customer” should be understood to refer to a user of an application or applications as described herein and / or a consumer of data supplied by a data provider. By way of example, and not limitation, the term “user” or “subscriber” can refer to a person who receives data provided by the data or service provider over the Internet in a browser session, or can refer to an automated software application which receives the data and stores or processes the data. Those skilled in the art will recognize that the methods and systems of the present disclosure may be implemented in many manners and as such are not to be limited by the foregoing exemplary embodiments and examples. In other words, functional elements being performed by single or multiple components, in various combinations of hardware and software or firmware, and individual functions, may be distributed among software applications at either the client level or server level or both. In this regard, any number of the features of the different embodiments described herein may be combined into single or multiple embodiments, and alternate embodiments having fewer than, or more than, all of the features described herein are possible.

[0083] Functionality may also be, in whole or in part, distributed among multiple components, in manners now known or to become known. Thus, myriad software / hardware / firmware combinations are possible in achieving the functions, features, interfaces and preferences described herein. Moreover, the scope of the present disclosure covers conventionally known manners for carry ing out the described features and functions and interfaces, as well as those variations and modifications that may be made to the hardware or software or firmware components described herein as would be understood by those skilled in the art now and hereafter.

[0084] Furthermore, the embodiments of methods presented and described as flowcharts in this disclosure are provided by way of example in order to provide a more complete understanding of the technology. The disclosed methods are not limited to the operations and logical flow presented herein. Alternative embodiments are contemplated in which the order of the various operations is altered and in which sub-operations described as being part of a larger operation are performed independently.

[0085] While various embodiments have been described for purposes of this disclosure, such embodiments should not be deemed to limit the teaching of this disclosure to those embodiments. Various changes and modifications may be made to the elements and operations described above to obtain a result that remains within the scope of the systems and processes described in this disclosure.

Claims

CLAIMSWhat is claimed is:

1. A method comprising: monitoring, by a device associated with a security system, a location, the monitoring comprising capturing video footage according to a time period, the capturing comprising collecting video data via a first mode; analyzing, by the device, the collected video data; determining, based on the analysis, an event corresponding to motion occurring at the location; automatically switching, by the device, upon the event determination, to a second mode, the second mode comprising video capture functionality different than the first mode; and continuing capturing, by the device, the video footage via the second mode for a time period that corresponds to the detected motion.

2. The method of claim 1, wherein the first mode corresponds to an infrared night mode.

3. The method of claim 1, wherein the second mode corresponds to a color night mode.

4. The method of claim 1, wherein the determination of the event is based on the device executing a motion detection algorithm, wherein the motion detection algorithm is a frame difference algorithm.

5. The method of claim 1, further comprising: collecting location data related to the location, the location data comprising information related to an environment at the location; and setting, based on the location data, the device to the first mode.

6. The method of claim 5, wherein the analysis of the collected video data is based on the location data.

7. The method of claim I . wherein the event detection corresponds to at least one of image or audio data associated with the video data.

8. The method of claim 1, wherein the device comprises a camera.

9. A device comprising: a processor configured to: monitor a location, the monitoring comprising capturing video footage according to a time period, the capturing comprising collecting video data via a first mode; analyze the collected video data; determine, based on the analysis, an event corresponding to motion occurring at the location; automatically switch, upon the event determination, to a second mode, the second mode comprising video capture functionality different than the first mode; and continue to capture the video footage via the second mode for a time period that corresponds to the detected motion.

10. The device of claim 9, wherein the first mode corresponds to an infrared night mode.

11. The device of claim 9, wherein the second mode corresponds to a color night mode.

12. The device of claim 9, wherein the determination of the event is based on the device executing a motion detection algorithm, wherein the motion detection algorithm is a frame difference algorithm.

13. The device of claim 9, wherein the processor is further configured to: collect location data related to the location, the location data comprising information related to an environment at the location; andset, based on the location data, the device to the first mode, wherein the analysis of the collected video data is based on the location data.

14. The device of claim 9, wherein the device comprises a camera.

15. A non-transitory computer-readable storage medium tangibly encoded with computer-executable instructions that when executed by a device, perform a method comprising: monitoring, by the device, a location, the monitoring comprising capturing video footage according to a time period, the capturing comprising collecting video data via a first mode; analyzing, by the device, the collected video data; determining, based on the analysis, an event corresponding to motion occurring at the location; automatically switching, by the device, upon the event determination, to a second mode, the second mode comprising video capture functionality different than the first mode; and continuing capturing, by the device, the video footage via the second mode for a time period that corresponds to the detected motion.

16. The non-transitory computer-readable storage medium of claim 15, wherein the first mode corresponds to an infrared night mode.

17. The non-transitory computer-readable storage medium of claim 15, wherein the second mode corresponds to a color night mode.

18. The non-transitory computer-readable storage medium of claim 1 , wherein the determination of the event is based on the device executing a motion detection algorithm, wherein the motion detection algorithm is a frame difference algorithm.

19. The non-transitory computer-readable storage medium of claim 15, further comprising: collecting location data related to the location, the location data comprising information related to an environment at the location; andsetting, based on the location data, the device to the first mode, wherein the analysis of the collected video data is based on the location data.

20. The non-transitory computer-readable storage medium of claim 15, wherein the device comprises a camera.

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