System and method for centralized collection of vehicle-detected event data

Abstract

To provide a method for collecting data associated with an event from a vehicle.SOLUTION: A method, a system, and a device are provided for collecting data associated with an event from a vehicle. The method may be implemented by one or more processors programmed in a server for collecting evidence to investigate an event, and may include: obtaining a time and a location for the event to be investigated; transmitting a signal including the time and the location for requesting sensor data corresponding to the event to a plurality of vehicles; receiving the sensor data corresponding to the event from at least one of the plurality of vehicles; and providing the received sensor data for investigating the event.SELECTED DRAWING: Figure 3

Description

[Technical Field]

[0001] Systems, methods, and devices consistent with exemplary embodiments of the present disclosure relate to vehicles, and more particularly to systems, methods, and devices that collect event data from vehicles and subsequently manage said event data. [Background technology]

[0002] Typically, events such as crimes, accidents, and other such cases requiring investigation are investigated using data collected from the scene as evidence. For example, a hit-and-run case may be investigated using data collected by security cameras or surveillance deployed near the case, a car accident may be investigated using data collected by on-board sensors, and the like.

[0003] However, sources of such evidence or data may be limited, especially in remote, rural, or other areas without operational surveillance or security cameras, or in cases involving vehicles without on-board sensors and / or permanent sensor data storage.

[0004] Furthermore, even for cases captured by one or more sensors, the captured data may often be from viewpoints, lines of sight, and the like that may not represent the complete situation. For example, an accident involving two vehicles may appear to be the fault of one particular vehicle based on public surveillance or traffic camera data, but in fact the other vehicle may have caused the accident by some illegal behavior (e.g., an illegal U-turn) outside the camera's capture area. In these cases, investigation of the case (such as a crime or accident) is hindered by a lack of evidence. Summary of the Invention

[0005] According to embodiments, methods, systems, and devices are provided for crowdsourcing data from multiple vehicles equipped with on-board sensors, so that greater amounts of more robust event data can be collected.

[0006] According to an embodiment, a method is provided that is implemented by one or more programmed processors in a server to collect evidence and investigate an event, the method may include obtaining a time and location for the event to be investigated, transmitting a signal including the time and location to request sensor data corresponding to the event from a plurality of vehicles, receiving sensor data corresponding to the event from at least one of the plurality of vehicles, and providing the received sensor data to investigate the event.

[0007] The time may include a time range corresponding to the event, and / or the location may include a location range corresponding to the event. The sensor data may include at least one of image data, LiDAR sensor data, accelerometer data, audio data, and infrared image data captured by an onboard sensor of the vehicle.

[0008] Receiving the sensor data may include receiving the sensor data from another server that anonymizes the sensor data.

[0009] The method may further include processing the received sensor data, where the received sensor data may include infrared image data, and where processing the received sensor data may include determining whether the infrared image data includes the shape of an object having a temperature above a predetermined threshold.

[0010] The method may further include processing the received sensor data, where the received sensor data may include LiDAR sensor data, and where processing the received sensor data may include determining whether an event is captured based on the LiDAR sensor data.

[0011] The method may further include performing one or more of pre-processing, transforming, matching, and filtering on the received sensor data.

[0012] According to an embodiment, a system for collecting evidence and investigating an event is provided, the system may include a memory that stores instructions and at least one programmed processor configured to execute the instructions to obtain a time and location for the event being investigated, transmit a signal including the time and location to request sensor data corresponding to the event from a plurality of vehicles, receive sensor data corresponding to the event from at least one of the plurality of vehicles, and provide the received sensor data for investigating the event.

[0013] The time may include a time range corresponding to the event, and / or the location may include a location range corresponding to the event. The sensor data may include at least one of image data, LiDAR sensor data, accelerometer data, audio data, and infrared image data captured by an onboard sensor of the vehicle.

[0014] Receiving the sensor data may include receiving the sensor data from another server that anonymizes the sensor data.

[0015] The at least one programmed processor may further be configured to execute instructions to process the received sensor data, where the received sensor data may include infrared image data, and where processing the received sensor data may include determining whether the infrared image data includes the shape of an object having a temperature above a predetermined threshold.

[0016] The at least one programmed processor may be further configured to execute instructions to process the received sensor data, where the received sensor data may include LiDAR sensor data, and where processing the received sensor data may include determining whether an event is captured based on the LiDAR sensor data.

[0017] The at least one programmed processor may be further configured to execute instructions to perform one or more of pre-processing, transforming, matching, and filtering on the received sensor data.

[0018] According to an embodiment, a non-transitory computer-readable recording medium is provided, the non-transitory computer-readable recording medium having instructions executable by at least one programmed processor recorded thereon to cause the at least one programmed processor to perform a method for gathering evidence and investigating an event, the method may include obtaining a time and location of the investigated event, transmitting a signal including the time and location to request sensor data corresponding to the event from a plurality of vehicles, receiving sensor data corresponding to the event from at least one of the plurality of vehicles, and providing the received sensor data to investigate the event.

[0019] The time may include a time range corresponding to the event, and / or the location may include a location range corresponding to the event. The sensor data may include at least one of image data, LiDAR sensor data, accelerometer data, audio data, and infrared image data captured by an onboard sensor of the vehicle.

[0020] Receiving the sensor data may include receiving the sensor data from another server that anonymizes the sensor data.

[0021] The non-transitory computer-readable recording medium may have stored thereon instructions executable by at least one programmed processor to cause the at least one programmed processor to perform a method that may further include processing received sensor data, where the received sensor data may include infrared image data, and where processing the received sensor data may include determining whether the infrared image data includes a predetermined object having a temperature above a predetermined threshold.

[0022] The non-transitory computer-readable storage medium may have stored thereon instructions executable by at least one programmed processor to cause the at least one programmed processor to perform a method that may further include processing received sensor data, where the received sensor data may include LiDAR sensor data, and where the processing of the received sensor data may include determining whether an event is captured based on the LiDAR sensor data.

[0023] Additional aspects will be set forth in part in the description that follows, and in part will be apparent from the description, or may be realized by practice of presented embodiments of the present disclosure. [Brief explanation of the drawings]

[0024] The features, advantages, and importance of preferred embodiments of the present disclosure will now be described with reference to the accompanying drawings, in which like reference numerals refer to like elements, and in which: [Figure 1] FIG. 1 illustrates a block diagram of an exemplary system for communicating with one or more vehicles, according to one or more embodiments. [Figure 2] FIG. 2 illustrates an exemplary components diagram of a server according to one or more embodiments. [Figure 3] FIG. 3 illustrates a flow diagram of an exemplary method for collecting data and investigating events according to one or more embodiments. [Figure 4] FIG. 4 illustrates a diagram of exemplary components of a vehicle, according to one or more embodiments. [Figure 5] FIG. 5 illustrates an example of a recording file according to one or more embodiments. [Figure 6] FIG. 6 illustrates a flow diagram of an exemplary method for providing data to investigate an event according to one or more embodiments. DETAILED DESCRIPTION OF THE INVENTION

[0025] The following detailed description of preferred embodiments refers to the accompanying drawings. The foregoing disclosure provides illustration and description, but is not intended to be exhaustive or to limit implementations to the precise form disclosed. Modifications and variations are possible in light of the above disclosure or may be acquired from practice of implementations. Furthermore, one or more features or components of one embodiment may be incorporated into or combined with another embodiment (or one or more features of another embodiment). Furthermore, in the flowcharts and descriptions of operations provided below, it is understood that one or more operations may be omitted, one or more operations may be added, one or more operations may occur (at least partially) concurrently, or the order of one or more operations may be switched.

[0026] It will be apparent that the systems and / or methods described herein may be implemented in various forms of hardware, firmware, or combinations of hardware and software. The actual dedicated control hardware or software code used to implement the systems and / or methods is not a limitation of the implementation. Thus, the operation and behavior of the systems and / or methods are described herein without reference to specific software code, and it will be understood that software and hardware can be designed to implement the systems and / or methods based on the description herein.

[0027] Although particular combinations of features are recited in the claims and / or disclosed herein, such combinations are not intended to limit the disclosure of possible implementations. Indeed, many of the features may be combined in ways not specifically recited in the claims and / or disclosed herein. Although each dependent claim listed below may depend directly on only one claim, the disclosure of possible implementations includes each dependent claim in combination with all other claims in the claim set.

[0028] No element, act, or instruction used herein should be construed as critical or required unless expressly stated otherwise. Also, as used herein, the articles "a" and "an" are intended to include one or more items and may be used interchangeably with "one or more." Where only one item is intended, the term "one" or similar terms are used. Also, as used herein, the terms "has," "have," "having," "include," "including," and the like are intended to be open-ended terms. Furthermore, the phrase "based on" is intended to mean "based at least in part on," unless expressly stated otherwise. Furthermore, phrases such as "at least one of [A] and [B]" or "at least one of [A] or [B]" should be understood to include A only, B only, or both A and B.

[0029] References throughout this specification to "one embodiment," "an embodiment," "a non-limiting preferred embodiment," or similar terms mean that the particular feature, structure, or characteristic described in connection with the illustrated embodiment is included in at least one embodiment of the solution. Thus, the phrases "in one embodiment," "in an embodiment," "a non-limiting preferred embodiment," and similar terms throughout this specification may, but do not necessarily, all refer to the same embodiment.

[0030] Furthermore, the described features, advantages, and characteristics of the present disclosure may be combined in any suitable manner in one or more embodiments. Those skilled in the art will recognize, in light of the description herein, that the present disclosure may be practiced without one or more of the specific features or advantages of a particular embodiment. In other instances, additional features and advantages may be recognized in certain embodiments that may not be present in all embodiments of the present disclosure.

[0031] In one implementation of the present disclosure described herein, a display page may include information residing in the memory of a computing device, and the information may be transmitted from the computing device to a data center over a network, or vice versa. The information may be stored in memory on each computing device, in data storage at the edge of the network, or on a server at the data center. A computing device or a mobile device may accept non-transitory computer-readable media, which may include instructions, logic, data, or code that may be stored in permanent or temporary memory of the mobile device or that may affect or initiate an action by the mobile device in some way. Similarly, one or more servers may communicate with one or more mobile devices in a network and transmit computer files residing in their memory. For example, the network may include the Internet, a wireless communication network, or any other network connecting one or more mobile devices to one or more servers.

[0032] Exemplary embodiments of the present disclosure provide methods, systems, and devices for crowdsourcing data from multiple vehicles equipped with onboard sensors. Thus, greater amounts of and more robust data can be collected. For example, greater amounts of, more reliable, or more unbiased evidence corresponding to an event or case can be obtained, and the event / case can be investigated and facilitated based thereon.

[0033] 1 shows a block diagram of an example system 100 for communicating with one or more vehicles, according to one or more embodiments. Referring to FIG. 1, system 100 may include a server 110, a network 120, and multiple vehicles (vehicles 130-1 and 130-2).

[0034] Server 110 may be communicatively coupled to a plurality of vehicles via network 120. Server 110 and the plurality of vehicles may be configured to send and receive one or more pieces of information from each other. Information may be exchanged between server 110 and the plurality of vehicles in the form of signals, network data, and any other suitable form.

[0035] Network 120 may include one or more data links that enable the transport of electronic data between server 110 and multiple vehicles (and components or systems contained therein). In this regard, network 120 may include one or more wired and / or wireless networks. For example, network 120 may include a cellular network (e.g., a fifth-generation (5G) network, a long-term evolution (LTE) network, a third-generation (3G) network, a code division multiple access (CDMA) network, etc.), a public land mobile network (PLMN), a local area network (LAN), a wide area network (WAN), a metropolitan area network (MAN), a telephone network (e.g., a public switched telephone network (PSTN)), a wireless fidelity (WiFi) network, a private network, a Bluetooth® network, an ad hoc network, an intranet, the Internet, an optical fiber-based network, or the like, and / or a combination of these or other types of networks. According to an embodiment, server 110 may be configured to broadcast or multicast queries or signals containing information about an event (e.g., a crime, an accident, etc.). The query / signal may be sent to multiple vehicles via over-the-air (OTA) transmission using network 120 .

[0036] Server 110 may include one or more devices capable of receiving, generating, storing, processing, computing, and / or providing information or data. According to an embodiment, server 110 may include a cloud server or a group of cloud servers (e.g., a server cluster, etc.). According to an embodiment, server 110 may be comprised of multiple servers, some of which may be deployed in different locations. For example, server 110 may include edge servers deployed near vehicles 130-1 and / or 130-2, central servers deployed remotely from vehicles 130-1 and / or 130-2, and the like.

[0037] 2 shows a diagram of example components of server 200, according to one or more embodiments. Server 200 may be similar to server 110 in FIG. 1, and therefore, descriptions corresponding to server 200 and server 110 may be applicable to one another unless expressly stated otherwise.

[0038] Referring to FIG. 2, server 200 may include a bus 210, a processor 220, a memory 230, a storage component 240, an input component 250, an output component 260, and a communication interface 270.

[0039] Bus 210 may include one or more components that allow communication between components of server 200. Processor 220 may be implemented in hardware, firmware, or a combination of hardware and software. Processor 220 may be a central processing unit (CPU), a graphics processing unit (GPU), an accelerated processing unit (APU), a microprocessor, a microcontroller, a digital signal processor (DSP), a field programmable gate array (FPGA), an application-specific integrated circuit (ASIC), or another type of processing or computational component. In some implementations, processor 220 may include one or more processors that are programmable to perform functions. Memory 230 may include random access memory (RAM), read-only memory (ROM), and / or another type of dynamic or static storage device (e.g., flash memory, magnetic memory, and / or optical memory) that stores information and / or instructions used by processor 220.

[0040] Storage component 240 may store information and / or software related to the operation and use of server 200. For example, storage component 240 may include a hard disk (e.g., a magnetic disk, optical disk, magneto-optical disk, and / or solid-state disk), a compact disk (CD), a digital versatile disk (DVD), a floppy disk, a cartridge, a magnetic tape, and / or another type of non-transitory computer-readable medium, along with a corresponding drive.

[0041] Input components 250 may include one or more components (e.g., a touchscreen display, a keyboard, a keypad, a mouse, buttons, switches, and / or a microphone, etc.) that allow server 200 to receive information, such as via user input. Additionally or alternatively, input components 250 may include sensors that detect information (e.g., a global positioning system (GPS) component, an accelerometer, a gyroscope, and / or an actuator). Output components 260 may include one or more components (e.g., a display, a speaker, and / or one or more light-emitting diodes (LEDs)) that provide output information from server 200.

[0042] Communication interface 270 may include transceiver-like components (e.g., a transceiver and / or a separate receiver and transmitter) that enable server 200 to communicate with other devices, such as via a wired connection, a wireless connection, or a combination of wired and wireless connections. Communication interface 270 may allow server 200 to receive information from and / or provide information to other devices (e.g., devices included in multiple vehicles, etc.). For example, communication interface 270 may include an Ethernet interface, an optical interface, a coaxial interface, an infrared interface, a radio frequency (RF) interface, a universal serial bus (USB) interface, a Wi-Fi interface, a cellular network interface, or the like.

[0043] Server 200 may perform one or more processes described herein in response to processor 220 executing software instructions stored by a non-transitory computer-readable storage medium, such as memory 230 and / or storage component 240. A computer-readable medium is defined herein as a non-transitory memory device. A memory device may include memory space within a single physical storage device or memory space spanning multiple physical storage devices.

[0044] Software instructions may be loaded into memory 230 and / or storage component 240 from another computer-readable medium or from another device via communications interface 270. When executed, the software instructions stored in memory 230 and / or storage component 240 may cause processor 220 to perform one or more processes described herein. Additionally or alternatively, hardwired circuitry may be used in place of or in combination with software instructions to perform one or more processes described herein. Thus, implementations described herein are not limited to any specific combination of hardware circuitry and software.

[0045] According to one or more embodiments, server 200 may be configured to perform a method of collecting data from one or more vehicles. The data may be used as evidence to investigate an event (e.g., a crime, an accident, etc.). Alternatively, the data may be used for other purposes, such as mapping, history logging, and the like.

[0046] 3 shows a flow diagram of an example method 300 for collecting data and investigating an event, according to one or more embodiments. One or more operations of method 300 may be performed by a server (e.g., server 110 in FIG. 1 , server 200 in FIG. 2 , etc.). For example, the server may be configured to receive or obtain information associated with the event, request associated vehicles to provide data associated with the event (which may be referred to herein as “event data”), receive the event data from associated vehicles, and provide the event for investigation of the event.

[0047] 3, at operation S310, information associated with the event is obtained or received. For example, one or more processors of the server (e.g., processor 220, etc.) may be configured to obtain or receive information (via a communication interface (e.g., communication interface 270, etc.) of the server) from one or more devices or systems (e.g., user equipment of an event investigator, an event investigation system, another server, etc.) that are communicatively connected to the server (e.g., directly connected to the server via a wired connection, indirectly connected to the server via a wireless connection, etc.). Alternatively or additionally, the one or more processors may be configured to obtain or receive a request directly from a user (e.g., an event investigator, a system operator, etc.) via an input component (e.g., input component 250, etc.) of the server.

[0048] According to embodiments, the information may include information associated with the event, such as a location of the event, a time of the event, a type of event, and the like. In this regard, the location of the event may include a particular latitude and longitude or a location range or the like corresponding to the event, the time of the event may include a particular point in time or time range corresponding to the event, and the type of event may include a category (e.g., crime, accident, etc.) and subcategory (e.g., car accident, hit-and-run case, etc.) corresponding to the event.

[0049] According to other embodiments, the server may be configured to determine or derive needed information from the request (e.g., location of the event, time of the event, etc.) For example, the request may include a report of the event (e.g., a written report, an audio recording, etc.), and one or more processors may perform keyword extraction (e.g., text recognition, speech processing, etc.) or other suitable operations to determine or extract the needed information from the report.

[0050] Thereafter, at operation S320, the server may be configured to communicate with one or more vehicles to request data associated with the event therefrom. According to an embodiment, the server may determine one or more vehicles associated with the event and may transmit a signal including information about the event (e.g., time of the event, location of the event, etc.) to request data corresponding to the event from the one or more vehicles. According to an embodiment, the request may be for sensor data collected via one or more sensors deployed in the one or more vehicles.

[0051] In this regard, the one or more processors may determine, based on the location and / or time of the event, one or more vehicles located within the area of ​​the event during the time of the event, and may send a request to the one or more vehicles via a network (e.g., network 120, etc.). As another example, the one or more processors may determine (e.g., based on information stored in one or more storage media, such as memory 230 and / or storage component 240) one or more vehicles that are registered in the system or whose owners have consented to participate in the data collection process, and may send a request to the one or more vehicles. As yet another example, the one or more processors may determine one or more vehicles within a particular range from one or more active networks, or one or more vehicles connected to one or more particular networks, and may send a request to the one or more vehicles.

[0052] Upon sending the request, at operation S330, the server may receive the requested event data from one or more vehicles. For example, the server may receive the requested event data (e.g., via a communication interface) from one or more vehicles and / or from one or more devices associated with the vehicles (e.g., one or more servers associated with the vehicles, one or more external storage media associated with the vehicles, etc.). According to an embodiment, the received event data may include sensor data. For example, the received event data may include image data, LiDAR sensor data, accelerometer data, audio data, infrared image data, and / or any other suitable sensor data captured by one or more on-board sensors of one or more vehicles.

[0053] The received event data may be stored in one or more storage media (e.g., memory 230, storage component 240, etc.). According to an embodiment, the server may be configured to process some or all of the received event data before and / or after storing the received event data in one or more storage media.

[0054] For example, the one or more processors may be configured to perform one or more of the following operations on some or all of the received event data: pre-processing (e.g., normalizing, encoding, decoding, enhancing, etc.), transformation (e.g., speech versus text and / or natural language understanding of the audio data), matching (e.g., cataloging, etc.), and filtering (e.g., filtering out portions of the data by specifically detecting or classifying objects or by comparing a threshold against a certain threshold (e.g., a threshold volume level for the captured audio data)).

[0055] Additionally, the one or more processors may be configured to anonymize some or all of the received event data. For example, the one or more processors may be configured to determine which received event data needs to be anonymized (e.g., sensitive information such as characteristics of the vehicle or user of the vehicle, vehicle driving history, etc.) and perform one or more suitable data anonymizations on that data (e.g., erasing, encrypting, etc.).

[0056] According to embodiments, the one or more processors may perform one or more of the aforementioned operations using one or more artificial intelligence (AI) or machine learning (ML) models (e.g., may input at least a portion of the received event data into one or more AI / ML models that are trained to perform the aforementioned operations, etc.). The one or more AI / ML models may be pre-trained and stored in one or more storage media and may be retrieved and used by the one or more processors when needed. According to embodiments, in addition to using one or more AI / ML models to perform the aforementioned operations, the one or more processors may also train the one or more AI / ML models using the received event data.

[0057] Additionally, the one or more processors may also utilize one or more AI / ML models and / or one or more rule-based algorithms to detect relevance of the received event data to a corresponding event. For example, if the received event data is audio data, the one or more processors may determine whether the audio data includes a predetermined keyword or is louder than a predetermined threshold. Furthermore, if the received event data is thermal image data and the event involves a fire of a specific object (e.g., another vehicle, a nearby building, etc.), the one or more processors may determine whether the thermal image data includes a shape of the specific object having a temperature higher than a predetermined threshold. Furthermore, if the received event data includes LiDAR sensor data, the one or more processors may determine based on the LiDAR sensor data whether the event is captured by a vehicle (e.g., whether there is a collision between a vehicle and a pedestrian if the event is a vehicular assault or homicide, etc.).

[0058] Thus, at operation S340, the server may provide the received event data for investigation of the event. For example, the one or more processors may provide the processed data to one or more devices or systems (e.g., an event investigator's user equipment, an event investigation system, another server, etc.) via a communications interface, may provide the processed data to a user (e.g., an event investigator, etc.) via an output component (e.g., output component 260, etc.), and / or the like. According to an embodiment, upon processing the data, the one or more processors may store the processed data in one or more storage media, so that the processed data can be retrieved or provided for investigation of the event when requested.

[0059] It may be understood that in operation S340, the server may also simply provide some or all of the received event data for investigation of the event without processing the received data. For example, the received event data may already have been processed by one or more vehicles and / or associated devices (e.g., a processing server associated with the vehicle, an external storage medium associated with the vehicle, etc.) and / or does not require further processing by server 200. By way of example, the event data may be provided by one or more servers associated with the vehicle that anonymize the event data, and the server may simply receive the event data from said one or more servers. In that case, upon receiving the event data in operation S330, the server may initiate operation S340 without processing the received event data.

[0060] 4 illustrates a diagram of exemplary components of a vehicle 400, according to one or more embodiments. Vehicle 400 may be similar to vehicle 130-1 and / or vehicle 130-2 in FIG. 1, and therefore, descriptions corresponding to vehicle 400 and vehicle 130-1 / vehicle 130-2 may be applicable to one another unless expressly stated otherwise.

[0061] Additionally, vehicle 400 may include any motorized and / or mechanical machine capable of carrying or transporting people and / or cargo, such as cars, trucks, motorcycles, buses, bicycles, mobility scooters, air vehicles, and the like.

[0062] 4, vehicle 400 may include bus 410, processor 420, memory 430, storage component 440, sensor 450, and communication interface 460. The general functions and roles of bus 410, processor 420, memory 430, storage component 440, and communication interface 460 may be similar to bus 210, processor 220, memory 230, storage component 240, and communication interface 270, respectively, described above with reference to FIG. 2. Therefore, redundant descriptions corresponding thereto may be omitted herein for the sake of brevity. Furthermore, it may be understood that vehicle 400 may also include input components and output components having similar functions and roles to input component 250 and output component 260 without departing from the scope of the present disclosure.

[0063] 4, vehicle 400 may include at least one sensor 450 configured to detect, measure, and capture respective data (which may be referred to herein as "sensor data"). For example, at least one sensor 450 may include an accelerometer that measures and captures data associated with vehicle acceleration / deceleration, vehicle speed, and / or vehicle distance traveled, an image sensor (e.g., a camera, etc.) that detects and captures image data around or near the vehicle, a Light Detection and Ranging (LiDAR) sensor that detects and captures data associated with light in one or more light spectrums, such as the visible spectrum, the infrared spectrum, the ultraviolet spectrum, and / or any other light spectrum, an audio sensor (e.g., a microphone, etc.) that may detect and capture audio data inside and / or outside the vehicle, and audio sensors (e.g., a microphone, etc.) that may detect and capture audio data inside and / or outside the vehicle. The sensors may include temperature sensors that measure and capture data associated with the temperature inside and / or outside the vehicle, location sensors (e.g., global positioning system (GPS), inertial measurement unit (IMU), etc.) that measure and capture data associated with the location, position, and / or orientation of the vehicle, contact sensors (e.g., pressure detectors, impact detectors, etc.) that detect and capture data between parts of the vehicle and objects, air sensors that measure and capture data associated with the air inside and / or outside the vehicle (e.g., oxygen levels, pollution levels, humidity levels, etc.), and any other sensors suitable for deployment in the vehicle.

[0064] It may be appreciated that some of the aforementioned sensors may operate together to perform certain operations, for example, an accelerometer and a location sensor may operate together to measure the current location of the vehicle and estimate the future location of the vehicle, an image sensor may operate together with an audio sensor to generate a video recording file, a location sensor may provide location and timing information to each of the aforementioned sensors so that data measured / captured by the sensors can be linked to the corresponding location and time measured / captured, and the like.

[0065] Additionally, at least one sensor 450 may be Internet of Things (IoT) based, allowing the vehicle to communicate with other devices over a network. For example, the vehicle may communicate with one or more external storage media on which measured sensor data is stored, may communicate with a server to provide some or all of the measured sensor data for anonymization, may communicate with a server (e.g., server 110, server 200, etc.) to receive requests and provide requested data, may communicate with other vehicles to exchange data for data verification, data enrichment, data correction, and the like.

[0066] Furthermore, the sensor data may be stored in the vehicle 400 (e.g., in the memory 430 and / or the storage component 440, etc.) permanently or semi-permanently for at least a predetermined period of time. In some embodiments, at least some of the sensor data may be transferred from the vehicle 400 to one or more storage media (e.g., a server or cloud storage, etc.) (e.g., via wireless transmission over a network). Metadata or logs of the transferred sensor data, or other information indicative of the transferred data, may be stored in the vehicle or may be implicitly recognized in the vehicle's control logic. The sensor data may be captured periodically, continuously, intermittently, or based on a trigger event (e.g., loud voice, horn activation, sudden deceleration or hard braking, sudden turn, etc.). Furthermore, some or all of the sensor data may be processed by the processor 420 before and / or after storage in the storage media. The sensor data may be processed (e.g., preprocessed, transformed, anonymized, etc.) in a manner similar to that described above with reference to FIG. 2 , and therefore, corresponding redundant descriptions may be omitted below for brevity.

[0067] 5 illustrates an example of a record file 500 according to one or more embodiments. Record file 500 may include sensor data captured by at least one sensor 450 in FIG. 4 and associated information such as the location where the data is measured and captured, the time the data is measured and captured, parameters specific to the sensor type (e.g., temperature type, image source, etc.), and the like.

[0068] The recording file 500 may be stored on the vehicle (e.g., in memory 430 and / or storage component 440, etc.) and / or on one or more devices external to the vehicle (e.g., a cloud server, external storage media, etc.). It may further be understood that multiple recording files may be generated and stored. For example, a first recording file may be generated that records sensor data provided by a temperature sensor, a second recording file may be generated that records sensor data provided by an image sensor, and the like.

[0069] It may further be understood that the recording file may include more / less information than that shown in Figure 5. For example, if the sensor data (e.g., metadata, etc.) is stored on an external storage medium, the recording file may include information of the external storage medium, such as an access link, storage time, and the like.

[0070] According to one or more embodiments, vehicle 400 may be configured to perform a method of providing data to one or more servers. The provided data may be used as evidence for investigating an event (e.g., a crime, an accident, etc.). Alternatively, the provided data may be used for other purposes, such as mapping, history logging, and the like.

[0071] 6 shows a flow diagram of an example method 600 for providing data to investigate an event, according to one or more embodiments. One or more operations of method 600 may be performed by one or more processors (e.g., processor 420) in a vehicle (e.g., vehicle 130-1 / vehicle 130-2 in FIG. 1 , vehicle 400 in FIG. 4 , etc.). For example, the vehicle may be configured to receive a request for event data from a server, determine the event data associated with the request, and provide the requested event data to the server.

[0072] 6, at operation S610, the vehicle may be configured to receive a request from a server. For example, one or more processors (e.g., processor 420, etc.) of the vehicle may be configured to obtain or receive a request via a communication interface (e.g., communication interface 460, etc.) from a server (e.g., server 110, server 200, etc.) communicatively connected to the vehicle via a network (e.g., network 120, etc.). According to an embodiment, the request may include information associated with the event, such as a location of the event, a time of the event, a type of event, and the like.

[0073] At operation S620, the vehicle may determine event data associated with the event. Specifically, one or more processors in the vehicle may determine from the request what sensor data is requested or most relevant to the event. For example, the one or more processors may retrieve a recording file (e.g., recording file 500) and determine therefrom the associated sensor data as the event data.

[0074] According to an embodiment, one or more processors of the vehicle may review the recording files to determine sensor data that corresponds to location information included in the request (e.g., a particular latitude, a particular longitude, etc.) and / or sensor data that corresponds to a predetermined range or area based on the location information.

[0075] Additionally, one or more processors of the vehicle may review the recording file to determine sensor data corresponding to timing information (e.g., a particular point in time, a particular date, etc.) and / or sensor data corresponding to a predetermined time range based on that particular point in time (before a first predetermined period of time and after a second predetermined period of time, where in various embodiments the first and second periods of time may be the same, the first period of time may be longer, or the second period of time may be longer).

[0076] Further, one or more processors of the vehicle may determine a type of event from the request (e.g., fire incident, car accident, etc.) and may determine a type of sensor data associated with the type of event from the recording file (e.g., temperature data, contact / impact data, etc.). Alternatively, the request may include information of one or more predetermined types of sensor data (e.g., image data, audio data, etc.), and the one or more processors may simply check the recording file for further details of the one or more predetermined types of sensor data. The predetermined types of sensor data may be encoded into one or more programming logic.

[0077] Upon determining the event data associated with the request, the vehicle may be configured to provide the requested event data to the server at operation S630. For example, one or more processors of the vehicle may retrieve the event data (e.g., sensor data associated with the event, etc.) from a storage medium (e.g., memory 430, storage component 440, etc.) and then provide the retrieved event data to the server via a communication interface.

[0078] According to embodiments, the vehicle may process (e.g., pre-process, transform, anonymize, etc.) the acquired event data and then transmit the processed event data to a server. According to other embodiments, the vehicle may transmit the acquired event data to one or more devices (e.g., servers, computers, etc.) configured to process the acquired event data before sending the event data to the server. Alternatively, the vehicle may only provide information of the event data (e.g., a uniform resource locator (URL) link of a device that stores / processes the event data, etc.) to the server, and the server may retrieve the event data based on the provided information.

[0079] In view of the above, exemplary embodiments of the present disclosure provide a method, system, device, or the like for crowdsourcing data from multiple vehicles equipped with on-board sensors. Thus, greater amounts of more robust data may be collected. For example, greater amounts of reliable or more unbiased evidence corresponding to an event or case may be obtained, and the event / case may be investigated and facilitated based thereon.

[0080] It is understood that the specific order or hierarchy of blocks in the processes / flowcharts disclosed herein is an example of an example approach. Based on design preferences, it is understood that the specific order or hierarchy of blocks in the processes / flowcharts may be rearranged. Furthermore, some blocks may be combined or omitted. The accompanying methods claim elements of the various blocks in a sample order and are not meant to be limited to the specific order or hierarchy presented.

[0081] Some embodiments may relate to systems, methods, and / or computer-readable media at any possible level of technical detail of integration. Furthermore, one or more of the above components described above may be implemented as instructions stored on a computer-readable medium and executable by at least one processor (and / or may include at least one processor). The computer-readable medium may include a computer-readable non-transitory storage medium(s) having computer-readable program instructions for causing a processor to perform operations.

[0082] A computer-readable storage medium may be a tangible device that can hold and store instructions for use by an instruction execution device. A computer-readable storage medium may be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination thereof. A non-exhaustive list of more specific examples of computer-readable storage media includes the following: portable computer diskettes, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disk read-only memory (CD-ROM), digital versatile disk (DVD), memory sticks, floppy disks, mechanically encoded devices such as punch cards or ridge-in-groove structures with instructions recorded thereon, and any suitable combination thereof. As used herein, computer-readable storage media should not be construed as being transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission medium (e.g., light pulses passing through a fiber optic cable), or electrical signals transmitted over wires.

[0083] The computer-readable program instructions described herein may be downloaded to each computing / processing device from a computer-readable storage medium, or may be downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network may include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in the respective computing / processing device.

[0084] The computer-readable program code / instructions for performing operations may be either source code or object code written in any combination of one or more programming languages, including assembler instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, configuration data for integrated circuits, or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, or the like, and procedural programming languages ​​such as the "C" programming language or similar programming languages. The computer-readable program instructions may be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection to the external computer may be made (e.g., through the Internet using an Internet Service Provider). In some embodiments, electronic circuitry including, for example, a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA) may execute computer-readable program instructions by utilizing state information of the computer-readable program instructions to personalize the electronic circuitry to perform an aspect or operation.

[0085] The computer-readable program instructions may be provided to a processor of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus to create a machine, such that the instructions, executed by the processor of the computer or other programmable data processing apparatus, create means for implementing the function(s) / act(s) specified in the block(s) of the flowcharts and / or block diagrams. The computer-readable program instructions may also be stored on a computer-readable storage medium that can direct a computer, programmable data processing apparatus, and / or other device to function in a particular manner, such that the computer-readable storage medium having instructions stored therein comprises an article of manufacture including instructions that implement aspects of the function(s) / act(s) specified in the block(s) of the flowcharts and / or block diagrams.

[0086] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or another device to cause the computer, other programmable apparatus, or other device to perform a series of operational steps to create a computer-implemented process, such that the instructions executing on the computer, other programmable apparatus, or other device implement the function(s) / act(s) specified in the flowchart and / or block diagram block or blocks.

[0087] The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer-readable media according to various embodiments. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of instructions comprising one or more executable instructions that implement a specified logical function. The methods, computer systems, and computer-readable media may include additional, fewer, different, or differently arranged blocks than those depicted in the figures. In some alternative implementations, the functions noted in the blocks may occur out of the order noted in the figures. For example, two blocks shown in succession may in fact be executed concurrently or substantially concurrently, or the blocks may even be executed in the reverse order, depending on the functionality involved. It should also be noted that each block of the block diagrams and / or flowchart illustrations, and combinations of blocks and / or flowchart illustrations, may be implemented by a dedicated hardware-based system that performs the specified functions or acts or executes a combination of dedicated hardware and computer instructions.

[0088] It will be apparent that the systems and / or methods described herein may be implemented in various forms of hardware, firmware, or combinations of hardware and software. The actual dedicated control hardware or software code used to implement the systems and / or methods is not a limitation of the implementation. Thus, the operation and behavior of the systems and / or methods are described herein without reference to specific software code, and it will be understood that software and hardware can be designed to implement the systems and / or methods based on the description herein.

Claims

1. 1. A method implemented by one or more programmed processors in a server for collecting evidence and investigating an event, the method comprising: obtaining a time and location for the event being investigated; determining one or more vehicles located at the event location during the event time based on the event time and location; transmitting a signal including the time and the location to request sensor data corresponding to the event from the determined one or more vehicles; receiving, from at least one of the one or more vehicles that received the signal, the sensor data corresponding to the event transmitted in response to the vehicle receiving the signal; providing the received sensor data to investigate the event; A method comprising:

2. The method of claim 1 , wherein the time comprises a time range corresponding to the event and / or the location comprises a location range corresponding to the event.

3. The method of claim 1 or 2, wherein the sensor data comprises at least one of image data, LiDAR sensor data, accelerometer data, audio data, and infrared image data captured by onboard sensors of the vehicle.

4. The method of claim 1 or 2, wherein the receiving of the sensor data comprises receiving the sensor data from another server that anonymizes the sensor data.

5. processing the received sensor data; the received sensor data comprises infrared image data; The method of claim 1 or 2, wherein the processing of the received sensor data includes determining whether the thermal image data includes the shape of an object having a temperature above a predetermined threshold.

6. processing the received sensor data; the received sensor data comprises LiDAR sensor data; The method of claim 1 or 2, wherein the processing of the received sensor data includes determining whether the event is captured based on the LiDAR sensor data.

7. The method of claim 1 or 2, further comprising performing one or more of pre-processing, transforming, matching, and filtering on the received sensor data.

8. 1. A system for gathering evidence and investigating an event, said system comprising: a memory for storing instructions; at least one programmed processor executing the instructions to: Obtaining the time and location of the event being investigated; determining one or more vehicles located at the event location during the event time based on the event time and location; transmitting a signal including the time and the location to request sensor data corresponding to the event from the determined one or more vehicles; receiving, from at least one of the one or more vehicles that received the signal, the sensor data corresponding to the event transmitted in response to the vehicle receiving the signal; providing the received sensor data to investigate the event; at least one programmed processor configured to: A system comprising:

9. The system of claim 8 , wherein the time comprises a time range corresponding to the event and / or the location comprises a location range corresponding to the event.

10. 10. The system of claim 8 or 9, wherein the sensor data comprises at least one of image data, LiDAR sensor data, accelerometer data, audio data, and infrared image data captured by onboard sensors of the vehicle.

11. The system of claim 8 or 9, wherein the receiving of the sensor data comprises receiving the sensor data from another server that anonymizes the sensor data.

12. The at least one programmed processor further executes the instructions to: configured to process the received sensor data; the received sensor data comprises infrared image data; 10. The system of claim 8 or 9, wherein the processing of the received sensor data includes determining whether the thermal image data includes the shape of an object having a temperature above a predetermined threshold.

13. The at least one programmed processor further executes the instructions to: configured to process the received sensor data; the received sensor data comprises LiDAR sensor data; 10. The system of claim 8 or 9, wherein the processing of the received sensor data includes determining whether the event is captured based on the LiDAR sensor data.

14. 10. The system of claim 8 or 9, wherein the at least one programmed processor is further configured to execute the instructions to perform one or more of pre-processing, transforming, collating, and filtering on the received sensor data.

15. 1. A non-transitory computer-readable storage medium having stored thereon instructions executable by at least one programmed processor to cause the at least one programmed processor to perform a method for gathering evidence and investigating an event, the method comprising: The method comprises: obtaining a time and location for the event being investigated; determining one or more vehicles located at the event location during the event time based on the event time and location; transmitting a signal including the time and the location to request sensor data corresponding to the event from the determined one or more vehicles; receiving, from at least one of the one or more vehicles that received the signal, the sensor data corresponding to the event transmitted in response to the vehicle receiving the signal; providing the received sensor data to investigate the event; A non-transitory computer-readable recording medium comprising:

16. The non-transitory computer-readable medium of claim 15 , wherein the time comprises a time range corresponding to the event and / or the location comprises a location range corresponding to the event.

17. 17. The non-transitory computer-readable storage medium of claim 15 or 16, wherein the sensor data comprises at least one of image data, LiDAR sensor data, accelerometer data, audio data, and infrared image data captured by onboard sensors of the vehicle.

18. The non-transitory computer-readable storage medium of claim 15 or 16, wherein the receiving of the sensor data comprises receiving the sensor data from another server that anonymizes the sensor data.

19. The method comprises: processing the received sensor data; the received sensor data comprises infrared image data; 17. The non-transitory computer-readable storage medium of claim 15 or 16, wherein the processing of the received sensor data includes determining whether the infrared image data includes the shape of an object having a temperature above a predetermined threshold.

20. The method comprises: processing the received sensor data; the received sensor data comprises LiDAR sensor data; 17. The non-transitory computer-readable storage medium of claim 15 or 16, wherein the processing of the received sensor data includes determining whether the event is captured based on the LiDAR sensor data.

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