Patent Publication Number: US-11392145-B1

Title: Unmanned vehicle security guard

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
     The present application claims priority to and is a continuation of U.S. patent application Ser. No. 15/596,898, filed May 16, 2017, which claims priority to, and the benefit of Provisional Patent Application No. 62/337,071 filed May 16, 2016, which is incorporated herein by reference in its entirety. 
    
    
     BACKGROUND OF THE INVENTION 
     Unmanned vehicles (e.g., unmanned aerial vehicles) are known for their use in combat zones. In combat zones, they are often used to surveille an area, damage a structures, or lethally wound a potential enemy combatant. The use of unmanned vehicles can go far beyond the aforementioned examples, especially outside of a combat zone and in a commercial setting. Businesses of all sorts are now developing innovative ways to use unmanned vehicles to benefit their business. 
     SUMMARY 
     Unmanned vehicles can be terrestrial, aerial, nautical, or multi-mode. Unmanned vehicles may be used to surveille a property in response to or in anticipation of a threat. For example, an unmanned vehicle may analyze information about the property and based on the information deter theft of items on the property. 
     This Summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This Summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter. Furthermore, the claimed subject matter is not constrained to limitations that solve any or all disadvantages noted in any part of this disclosure. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       A more detailed understanding may be had from the following description, given by way of example in conjunction with the accompanying drawings wherein: 
         FIG. 1  illustrates an exemplary system associated with a unmanned vehicle security guard; 
         FIG. 2  illustrates an overhead view of an exemplary neighborhood that may be surveilled by an unmanned vehicle; 
         FIG. 3  illustrates an exemplary method for providing security using an unmanned vehicle; 
         FIG. 4  is an exemplary block diagram representing a computer system in which aspects of the methods and systems disclosed herein or portions thereof may be incorporated. 
     
    
    
     DETAILED DESCRIPTION 
     Unmanned vehicles may be used to proactively or reactively secure one or more properties. For example, an unmanned vehicle may surveille a property in response to or in anticipation of a threat. For example, an unmanned vehicle may analyze information about the property and based on the information deter theft of items on the property. 
       FIG. 1  illustrates an exemplary system  90  associated with an unmanned vehicle security guard. Unmanned vehicle  100  includes sensor  145 , data analysis engine  120 , route determination engine  130 , and sensor management engine  140 . Unmanned vehicle  100  may be communicatively connected with network  50  and server  150 . A business (e.g., an insurance provider or law enforcement agency) may own or have control of unmanned vehicle  100 , network  50 , or server  150 . Person  131  (e.g., a homeowner or intruder) may be located in area  146  and vehicle  132  (e.g., an automobile, motorcycle, or boat—possibly unmanned) may be located in area  147 , as shown. 
     With continued reference to  FIG. 1 , data analysis engine  120 , route determination engine  130 , and sensor management engine  140  are logical entities that may be implemented in the form of software (e.g., computer-executable instructions) stored in a memory of, and executing on a processor of unmanned vehicle  100 , server  150 , or another computer system such as illustrated in  FIG. 4 . Data analysis engine  120  may analyze data retrieved by sensor  145 . Analysis by data analysis engine  120  may include comparing image data of person  131  or vehicle  132  to other information (e.g., information on server  150 ) to identify vehicle  132  or person  131 . Route determination engine  130  may be utilized to manage unmanned vehicle  100 , which may include confirming that unmanned vehicle  100  remains on a planned path based on a particular mission. Route determination engine  130  may also determine modifications to a route of unmanned vehicle  100  based on gathered information. For example, if additional images (e.g., picture or video) are needed of an alleged intruder (e.g., a certain location, which may include a different perspective or angle) route determination engine  130  may request unmanned vehicle  100  to vary the planned path accordingly, which may change the parameters of the mission. Another example may be for unmanned vehicle  100  to pursue person  131  (e.g., an alleged intruder) in order to identify the position of person  131  until law enforcement arrives. 
     Sensor management engine  140  controls sensor  145 . This control may include directing which sensor of a plurality of sensors gathers information, directing the operating characteristics of said information gathering (e.g., the level of zoom of a visible light camera), directing where sensor  145  is aimed, or any other sensor performance control variables. It is contemplated herein that sensor  145  may include a visible light camera, an infrared camera, a microphone, a particle inspection device (e.g., a device that can detect what compounds are in sampled air gathered by unmanned vehicle  100 ), radar emitting/detecting device(s), a spectrometer, a hyperspectral sensor, a temperature sensor, a humidity sensor, a gas sensor, or a navigation sensor, among other things. 
       FIG. 2  illustrates an overhead view of a neighborhood  160  that one or more unmanned vehicles may patrol. As shown, there may be a plurality of houses, such as house  162 , in neighborhood  160 . House  162  may have one or more sensors attached to it or the surrounding land within the property line associated with house  162 . Neighborhood  160  may have a plurality of unmanned vehicles, such as unmanned vehicle  100 , unmanned vehicle  166 , unmanned vehicle  167 , or unmanned vehicle  168 . There may be a vehicle  132  in neighborhood  160  and persons, such as person  131  or person  164 . Vehicle  132  may include sensors and may be a smart car that may have automated features with regard to self-driving or remote turn on/off. The houses, cars, and unmanned vehicles in neighborhood  160  may be communicatively connected with each other and share information captured by their respective sensors, indications of a threat level, or other information. 
       FIG. 3  illustrates an exemplary method to secure one or more properties with use of an unmanned vehicle. At step  171 , the environment (here neighborhood  160 ) is sensed by one more sensors. The sensed information may be from sensor  145  of unmanned vehicle  100  or other sensors or devices of house  162 , vehicle  132 , person  164 , person  131 , or sensors of unmanned vehicles  166 ,  167 , and  168 . In an example, house  162 , vehicle  162 , or unmanned vehicle  166  may have sensors that include a camera or motion detector, among other things. Person  164  or person  131  may have location sensors, cameras, wearable activity sensors, or manual indicators (e.g., alert button or text message), among other things. Activity sensors (also known as activity trackers) are wireless-enabled wearable devices that measure data such as the number of steps walked, heart rate, quality of sleep, steps climbed, and other personal metrics. Heart rate and other information from the activity sensor may be used to determine threat level. For example, higher the heart rate, then may be the more likely a threat. The heart rate may be compared to a baseline of that person. The heart rate may be indication that someone else proximate to the sensed person is a threat. 
     At step  172 , a threat level may be determined based on at least the sensed information of step  171 . The sensed information of step  171  may be combined in a variety ways with other information to determine the threat level of a general environment (e.g., neighborhood  160  overall), person (e.g., person  131 ), or thing (e.g., vehicle  132 —car bomb). The determination and display of the threat level may occur in real-time. The threat level may be constantly updated. In an example, house  162  and vehicle  132  may sense movement, which may trigger unmanned vehicle  100  to investigate an area proximate to house  162  and vehicle  132 . When unmanned vehicle  100  arrives proximate to house  162 , it may sense (e.g., via a camera) the activity or identity of a person, animal, or thing. In this example, the threat level may be determined by analyzing a combination of information including sensed movement from house  162  and vehicle  132  (e.g., movement or speed of movement), sensed identity (e.g., facial recognition) and activity patterns (e.g., sidewalk or bushes) of a person by unmanned vehicle  100 , heart rate of person  131  by activity sensor, time of day, or history of negative activity (e.g., break-ins) proximate to house  162 , among other things. 
     As discussed herein, identity may be sensed in different ways. For example, person  131  may have a mobile device or activity sensor that wirelessly transmits identity of person  131  when unmanned vehicle  100  is within a particularly close distance (e.g., 10 feet) of person  131 . In another example, person  131  may have an ID that may communicate via RFID or a driver&#39;s license type ID with a barcode that may be scanned by sensor  145  of unmanned vehicle  100 . In another example, an authorized person (e.g., a homeowner—person  164 ) of the security system of neighborhood  160  may program a temporary (e.g., 2 hours or a day) authorization code for person  131 , just in case person  131  is observed in neighborhood  160  by unmanned vehicle  100 . The authorization code may be associated with an RFID, driver&#39;s license, mobile phone, or activity tracker. In addition, the authorization code may be associated with a hand gesture, spoken code, texted code, or facial recognition, among other things. Threat level considerations that may tie into identity may include how many times and what issues occurred when person  131 , animal (e.g., wolf), or thing (e.g., car) entered into neighborhood  160  during a previous period, if at all. 
     With continued reference to  FIG. 3 , at step  173 , the area (e.g., neighborhood  160 , area  147 , area  146 , or area  169 ) may be secured based on the determined threat level. Securing an area may include sending alerts, triggering sirens, turning off devices in an area, or other actions which deter or neutralize a threat. In an example, the threat level of step  172  may be formerly classified based on the threat level reaching a certain threshold. For instance, the classification system may include four threshold levels which may be classified as low, elevated, high, or severe. The classifications may be displayed on a digitally displayed neighborhood map (e.g., a real-time updated heat map of threat levels of areas around houses in neighborhood  160 ) or sent to a subscriber mobile device via text message, among other things. The classifications may also provide for mandatory actions by unmanned vehicle  100  or other devices in neighborhood  160 . For example, at a classified high threat level, there may be mandatory video recording of all devices in neighborhood  160  or mandatory enablement of location services for all wireless devices in neighborhood  160 . 
     As discussed herein, when the threat level reaches a threshold level (e.g., high threat level or 90 rating), unmanned vehicle  100  may take certain actions to secure neighborhood  160 . In an example, when unmanned vehicle  100  determines a high threat level based on sensed information from sensor  145 , the entire neighborhood  160  may be lit or regions of neighborhood  160  may be lit based on lights being proximate (e.g., area  169 ) to the security threat, which may be person  131 . An example action by unmanned vehicle  100  may be to tag person  131  with an electronic beacon, with fluorescent paint, or the like. Based on the tag areas may be lit up, as well as alerts sent to different devices (e.g., mobile device). Fluorescent paint may be discovered or tracked by a camera, while an electronic beacon may send out wireless signals. Another example action may be for unmanned vehicle  100  to follow and video record person  100 . The video recording may be live streamed to televisions or mobile devices in neighborhood  160 . Another example action may be for unmanned vehicle  100  to split into multiple drones and follow person  131  and person  164 . 
     With continued reference to step  173  of  FIG. 3 , in a first example scenario, person  131  may have a high threat level. Cameras throughout neighborhood  160  may be directed to turn to the location of unmanned vehicle  100  or the location of person  131  based on other sensed information from unmanned vehicle  100 . Unmanned vehicle  100  may be used as beacon for other security related systems in neighborhood  160  to focus on or be directed by. In a second example scenario, unmanned vehicle  100  may indicate it is low on battery life. Because the integration of the security systems throughout neighborhood  160 , unmanned vehicle  168  may automatically communicate that it will take the place of unmanned vehicle  100 . In a third example scenario, person  131  may have a high threat level. A plurality of unmanned vehicles, such as unmanned vehicle  100 , unmanned vehicle  166 , and unmanned vehicle  167  may converge on area  169 . Unmanned vehicle  100 , unmanned vehicle  166 , and unmanned vehicle  167  may be strategically placed in locations around person  131  (e.g., a perimeter) based on the geography of neighborhood  160  (e.g., cliffs, dead-end roads, walls, etc. . . . ). The geography of neighborhood  160  may be used to determine not only location, but the number of unmanned vehicles used to surveille person  131 . Unmanned vehicle  100  may shutdown self-driving/automated vehicles (e.g., vehicle  132 ) in area  169 , lock down houses (e.g., doors and windows of house  162 ), send alerts via social media, alert law enforcement, or alert insurance service providers for a possible claim, among other things. The unmanned vehicles of neighborhood  160  may be positioned based on crime statistics (e.g., break-ins), which may or may not be based on threat level. 
     Unmanned vehicle  100  may be attached to house  162  and deployed periodically to proactively surveille house  162  or other property in neighborhood  160 . Deployment of unmanned vehicle  100  may be responsive to sensed information (e.g., motion) or historical information (crime statistics of neighborhood  160  or comparable neighborhoods). Unmanned vehicle  100  may be a shared resource for service providers (e.g., insurance providers). House  162  may be a smart home or the like. Generally, a smart home may be considered a home equipped with lighting, heating, and other electronic devices that may be controlled remotely by phone or computer and may be programmed to be automated. Multiple unmanned vehicles may be deployed based on the reason of deployment, specifications of an unmanned vehicle (e.g., range of unmanned vehicle), or consideration of information gathered after deployment. Unmanned vehicle  100  may release another unmanned vehicle (not shown) that may be smaller and be able go into restricted areas (e.g., inside a home). Unmanned vehicle  100  may have multiple sensors. 
     Sensed information may be encrypted, stored, or shared according to various criteria. In a fourth example scenario, unmanned vehicle  100  may indicate that it desires the identity of person  131 . As discussed herein, person  131  may have an RFID, driver&#39;s license, or mobile device that is able to provide the identity of person  131 . In an example, the mobile device may not send the identification to unmanned vehicle  100  directly, but may determine the most secure link (e.g., WiFi of house  162 ) to securely connect with server  150 . Server  150  may send only an indication of authorization (no identity information) to unmanned vehicle  100 . 
     The present disclosure is directed to an unmanned vehicle security guard. It is to be understood that any terms, phrases, structural and functional details, disclosed herein are merely examples for teaching various ways to employ the present disclosure. 
     Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Although any methods and materials similar or equivalent to those described herein can also be used in the practice or testing of the present disclosure, exemplary methods and materials are now described. 
     It must be noted that as used herein and in the appended claims, the singular forms “a”, “an,” and “the” include plural referents unless the context clearly dictates otherwise. Thus, for example, reference to “a stimulus” includes a plurality of such stimuli and reference to “the signal” includes reference to one or more signals and equivalents. 
     Although at least one series of steps are presented as an exemplary method of practicing one or more examples described herein, it is contemplated that the steps identified may be practiced in any order that is practicable, including without limitation the omission of one or more steps. 
     It is to be appreciated that network  50  depicted in  FIG. 1 , for example, may include a local area network (LAN), a wide area network (WAN), a personal area network (PAN), or combinations thereof. Such networking environments are commonplace in offices, enterprise-wide computer networks, intranets, and the Internet. For instance, when used in a LAN networking environment, system  90  is connected to the LAN through a network interface or adapter (not shown). When used in a WAN networking environment, the computing system environment typically includes a modem or other means for establishing communications over the WAN, such as the Internet. The modem, which may be internal or external, may be connected to a system bus via a user input interface, or via another appropriate mechanism. In a networked environment, program modules depicted relative to system  90 , or portions thereof, may be stored in a remote memory storage device such as storage medium. Computing devices may communicate over network  50  through one or more communications links formed between data interfaces. Communication links may comprise either wired or wireless links. It is to be appreciated that the illustrated network connections in the figures (e.g.,  FIG. 1  or  FIG. 4 ) are exemplary and other ways of establishing a communications link between multiple devices may be used. 
       FIG. 4  and the following discussion are intended to provide a brief general description of a suitable computing environment in which the methods and systems disclosed herein or portions thereof may be implemented. Although not required, the methods and systems disclosed herein is described in the general context of computer-executable instructions, such as program modules, being executed by a computer, such as a client workstation, server, personal computer, or mobile computing device such as a smartphone. Generally, program modules include routines, programs, objects, components, data structures and the like that perform particular tasks or implement particular abstract data types. Moreover, it should be appreciated the methods and systems disclosed herein and/or portions thereof may be practiced with other computer system configurations, including hand-held devices, multi-processor systems, microprocessor-based or programmable consumer electronics, network PCs, minicomputers, mainframe computers and the like. A processor may be implemented on a single-chip, multiple chips or multiple electrical components with different architectures. The methods and systems disclosed herein may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote memory storage devices. 
       FIG. 4  is a block diagram representing a general purpose computer system in which aspects of the methods and systems disclosed herein and/or portions thereof may be incorporated. As shown, the exemplary general purpose computing system includes a computer  920  or the like, including a processing unit  921 , a system memory  922 , and a system bus  923  that couples various system components including the system memory to the processing unit  921 . The system bus  923  may be any of several types of bus structures including a memory bus or memory controller, a peripheral bus, and a local bus using any of a variety of bus architectures. The system memory includes read-only memory (ROM)  924  and random access memory (RAM)  925 . A basic input/output system  926  (BIOS), containing the basic routines that help to transfer information between elements within the computer  920 , such as during start-up, is stored in ROM  924 . 
     The computer  920  may further include a hard disk drive  927  for reading from and writing to a hard disk (not shown), a magnetic disk drive  928  for reading from or writing to a removable magnetic disk  929 , and an optical disk drive  930  for reading from or writing to a removable optical disk  931  such as a CD-ROM or other optical media. The hard disk drive  927 , magnetic disk drive  928 , and optical disk drive  930  are connected to the system bus  923  by a hard disk drive interface  932 , a magnetic disk drive interface  933 , and an optical drive interface  934 , respectively. The drives and their associated computer-readable media provide non-volatile storage of computer readable instructions, data structures, program modules and other data for the computer  920 . As described herein, computer-readable media is a tangible, physical, and concrete article of manufacture and thus not a signal per se. 
     Although the exemplary environment described herein employs a hard disk, a removable magnetic disk  929 , and a removable optical disk  931 , it should be appreciated that other types of computer readable media which can store data that is accessible by a computer may also be used in the exemplary operating environment. Such other types of media include, but are not limited to, a magnetic cassette, a flash memory card, a digital video or versatile disk, a Bernoulli cartridge, a random access memory (RAM), a read-only memory (ROM), and the like. 
     A number of program modules may be stored on the hard disk, magnetic disk  929 , optical disk  931 , ROM  924  or RAM  925 , including an operating system  935 , one or more application programs  936 , other program modules  937  and program data  938 . A user may enter commands and information into the computer  920  through input devices such as a keyboard  940  and pointing device  942 . Other input devices (not shown) may include a microphone, joystick, game pad, satellite disk, scanner, or the like. These and other input devices are often connected to the processing unit  921  through a serial port interface  946  that is coupled to the system bus, but may be connected by other interfaces, such as a parallel port, game port, or universal serial bus (USB). A monitor  947  or other type of display device is also connected to the system bus  923  via an interface, such as a video adapter  948 . In addition to the monitor  947 , a computer may include other peripheral output devices (not shown), such as speakers and printers. The exemplary system of  FIG. 4  also includes a host adapter  955 , a Small Computer System Interface (SCSI) bus  956 , and an external storage device  962  connected to the SCSI bus  956 . 
     The computer  920  may operate in a networked environment using logical connections to one or more remote computers, such as a remote computer  949 . The remote computer  949  may be a personal computer, a server, a router, a network PC, a peer device or other common network node, and may include many or all of the elements described above relative to the computer  920 , although only a memory storage device  950  has been illustrated in  FIG. 4 . The logical connections depicted in  FIG. 4  include a local area network (LAN)  951  and a wide area network (WAN)  952 . Such networking environments are commonplace in offices, enterprise-wide computer networks, intranets, and the Internet. 
     When used in a LAN networking environment, the computer  920  is connected to the LAN  951  through a network interface or adapter  953 . When used in a WAN networking environment, the computer  920  may include a modem  954  or other means for establishing communications over the wide area network  952 , such as the Internet. The modem  954 , which may be internal or external, is connected to the system bus  923  via the serial port interface  946 . In a networked environment, program modules depicted relative to the computer  920 , or portions thereof, may be stored in the remote memory storage device. It will be appreciated that the network connections shown are exemplary and other means of establishing a communications link between the computers may be used. 
     Computer  920  may include a variety of computer readable storage media. Computer readable storage media can be any available media that can be accessed by computer  920  and includes both volatile and nonvolatile media, removable and non-removable media. By way of example, and not limitation, computer readable media may comprise computer storage media and communication media. Computer storage media include both volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by computer  920 . Combinations of any of the above should also be included within the scope of computer readable media that may be used to store source code for implementing the methods and systems described herein. Any combination of the features or elements disclosed herein may be used in one or more examples. 
     In describing preferred examples of the subject matter of the present disclosure, as illustrated in the Figures, specific terminology is employed for the sake of clarity. The claimed subject matter, however, is not intended to be limited to the specific terminology so selected, and it is to be understood that each specific element includes all technical equivalents that operate in a similar manner to accomplish a similar purpose. 
     This written description uses examples to disclose the invention, including the best mode, and also to enable any person skilled in the art to practice the invention, including making and using any devices or systems and performing any incorporated methods. The patentable scope of the invention is defined by the claims, and may include other examples. Such other examples are intended to be within the scope of the claims if they have structural elements that do not differ from the literal language of the claims, or if they include equivalent structural elements with insubstantial differences from the literal languages of the claims.