KR102385492B1 - System for providing video storage service using accelerometer - Google Patents

Abstract

Provided is a system for providing a video storage service by using an accelerometer. The system comprises: a camera for photographing the front of a vehicle and recording an accident as metadata when the accident is detected; and a video storage service providing server including an accident detection unit for detecting an accident through at least one sensor attached to the vehicle and vehicle data; a crash accident analysis unit for analyzing a driver reaction and a vehicle operation status by using the at least one sensor and the vehicle data after the detecting of the accident detection unit; a storage unit for storing the at least one sensor and the vehicle data so that the same is synchronized with the metadata; and an image management unit for storing, in the storage unit, video data captured by the camera so that the same is synchronized with the at least one sensor and the vehicle data. Therefore, the system can identify the driving habits of the driver and correct poor driving habits.

Description

Image storage service providing system using acceleration sensor {SYSTEM FOR PROVIDING VIDEO STORAGE SERVICE USING ACCELEROMETER}

The present invention relates to a system for providing an image storage service using an acceleration sensor, and provides a platform for storing images through accident and collision analysis using the acceleration sensor.

The importance of scientific interpretation of accident situations in the frequent car crashes has been strongly recognized recently with the rapid increase in car accidents. Recently, in advanced countries such as North America, Europe and Japan, reliable scientific collision accident analysis, effective traffic accident rescue prevention measures, vehicle design that enhances safety, and intelligent transportation system (ITS: For the purpose of implementing Intelligent Transport Systems), it is possible to record various data of the vehicle at the time of the accident and based on this, the cause of the accident and the event data recorder (EDR) that can analyze the vehicle movement and the driver's reaction at the time of the accident. Development and testing have been actively conducted. One of them is to configure a vehicle black box that acts like a black box of an airplane for prompt and accurate accident notification, and uses the acceleration value measured from the vehicle sensor to determine the accident, store accident data, and notify the accident. make judgment

At this time, a method of detecting an accident using acceleration and recording an image was researched and developed. In this regard, the prior art Korean Utility Model No. 20-0434041 (published on December 15, 2006) and In No. 10-1428008 (announced on August 07, 2014), rapid deceleration, rapid acceleration, and shock from the outside of the vehicle are recorded by a memory means for storing image digital information input from the camera control unit, and an acceleration sensor and an impact sensor. It detects and inputs from a sensor to record, and detects an accident situation based on the amount and pattern of the acceleration sensor to improve the identification of the accident situation, and sets a threshold value for each driving mode of the vehicle set according to the driving acceleration of the vehicle. By setting it, the sensitivity of the acceleration sensor is variably adjusted individually according to the threshold to improve the discriminating power of accident situation judgment, and by filtering non-accident situations through step-by-step pattern matching, the accident situation is detected and the speed of accident situation detection is increased. A configuration capable of detecting an accident situation using a sound reflecting the frequency change value by setting a frequency change value for each driving mode and reducing the resource used for accident situation detection is disclosed, respectively.

However, research on black boxes for post-accident handling and analysis of car accidents worldwide has been actively carried out and commercialized, and automakers are also obliged to install and release their vehicles based on their own technology. However, most of the products that have been released, are commercialized, or are scheduled to be released have a function to determine whether or not there is negligence after a traffic accident. Accordingly, in order to prevent the lack of initial first aid measures due to the driver's unconsciousness, which occurs frequently in car crashes, or the situation of being left unattended after a hit and run accident, a system that detects and notifies or analyzes the traffic accident situation together with a vehicle black box Therefore, research and development of a black box and platform having the above-described functions are required.

An embodiment of the present invention is based on a technology that detects an accident when sudden deceleration, rapid acceleration, and external shock of a vehicle are detected and input by the sensor by an acceleration sensor and an impact sensor, and furthermore, the movement of the vehicle and A vehicle accident situation detection system that detects and analyzes the driver's operation state and detects, stores, and analyzes the vehicle's movement, driver's various operational states, collision pulses, and collision-related signals when a vehicle collision accident occurs in real road conditions By adding , information on the driver's reaction and vehicle operation status just before the collision, information on the physical movement of the vehicle, that is, longitudinal and lateral acceleration and vehicle speed data related to the physical movement of the vehicle, steering angle and direction related to the driver's operation status, etc. , it is possible to provide a method of providing an image storage service using an acceleration sensor, which can provide information such as whether to brake or accelerate. However, the technical task to be achieved by the present embodiment is not limited to the technical task as described above, and other technical tasks may exist.

As a technical means for achieving the above-mentioned technical problem, an embodiment of the present invention is at least attached to the camera and the vehicle to record the accident as metadata (MetaData) when photographing the front of the vehicle and detecting the accident An accident detection unit that detects an accident through one sensor and vehicle data, a collision accident analysis unit that analyzes the driver reaction and vehicle operation status using at least one sensor and vehicle data after detection by the accident detection unit, metadata and It includes an image storage service providing server including a storage unit for storing at least one sensor and vehicle data to be synchronized, and an image management unit for storing image data captured by the camera to be synchronized with at least one sensor and vehicle data in the storage unit .

According to any one of the above-described problem solving means of the present invention, the collected and analyzed information can be used to identify the cause of an accident when a crash occurs and to handle the accident fairly, and to identify the driver's driving habit and correct the wrong driving habit. Effects such as calibration and fuel cost reduction can be obtained.

1 is a diagram for explaining a system for providing an image storage service using an acceleration sensor according to an embodiment of the present invention.
FIG. 2 is a block diagram illustrating a storage service providing server included in the system of FIG. 1 .
3 and 4 are diagrams for explaining an embodiment in which an image storage service using an acceleration sensor according to an embodiment of the present invention is implemented.
5 is an operation flowchart illustrating a method of providing an image storage service using an acceleration sensor according to an embodiment of the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those of ordinary skill in the art can easily implement them. However, the present invention may be embodied in several different forms and is not limited to the embodiments described herein. And in order to clearly explain the present invention in the drawings, parts irrelevant to the description are omitted, and similar reference numerals are attached to similar parts throughout the specification.

Throughout the specification, when a part is "connected" with another part, this includes not only the case of being "directly connected" but also the case of being "electrically connected" with another element interposed therebetween. . In addition, when a part "includes" a certain component, it means that other components may be further included, rather than excluding other components, unless otherwise stated, and one or more other features However, it is to be understood that the existence or addition of numbers, steps, operations, components, parts, or combinations thereof is not precluded in advance.

The terms "about", "substantially", etc. to the extent used throughout the specification are used in or close to the numerical value when manufacturing and material tolerances inherent in the stated meaning are presented, and are intended to enhance the understanding of the present invention. To help, precise or absolute figures are used to prevent unfair use by unconscionable infringers of the stated disclosure. As used throughout the specification of the present invention, the term "step of (to)" or "step of" does not mean "step for".

In this specification, a "part" includes a unit realized by hardware, a unit realized by software, and a unit realized using both. In addition, one unit may be implemented using two or more hardware, and two or more units may be implemented by one hardware. Meanwhile, '~ unit' is not limited to software or hardware, and '~ unit' may be configured to be in an addressable storage medium or to reproduce one or more processors. Thus, as an example, '~' denotes components such as software components, object-oriented software components, class components, and task components, and processes, functions, properties, and procedures. , subroutines, segments of program code, drivers, firmware, microcode, circuitry, data, databases, data structures, tables, arrays and variables. The functions provided in the components and '~ units' may be combined into a smaller number of components and '~ units' or further separated into additional components and '~ units'. In addition, components and '~ units' may be implemented to play one or more CPUs in a device or secure multimedia card.

Some of the operations or functions described as being performed by the terminal, apparatus, or device in the present specification may be performed instead of by a server connected to the terminal, apparatus, or device. Similarly, some of the operations or functions described as being performed by the server may also be performed in a terminal, apparatus, or device connected to the server.

In this specification, some of the operations or functions described as mapping or matching with the terminal means mapping or matching the terminal's unique number or personal identification information, which is the identification data of the terminal. can be interpreted as

Hereinafter, the present invention will be described in detail with reference to the accompanying drawings.

1 is a diagram for explaining a system for providing an image storage service using an acceleration sensor according to an embodiment of the present invention. Referring to FIG. 1 , an image storage service providing system 1 using an acceleration sensor may include at least one camera 100 and a storage service providing server 300 . However, since the image storage service providing system 1 using the acceleration sensor of FIG. 1 is only an embodiment of the present invention, the present invention is not limitedly interpreted through FIG. 1 .

At this time, each component of FIG. 1 is generally connected through a network (Network, 200). For example, as shown in FIG. 1 , at least one camera 100 may be connected to the storage service providing server 300 through the network 200 . In addition, the storage service providing server 300 may be connected to at least one camera 100 and at least one incident processing agency server 400 through the network 200 . In addition, the at least one incident processing agency server 400 may be connected to the storage service providing server 300 through the network 200 .

Here, the network refers to a connection structure in which information exchange is possible between each node, such as a plurality of terminals and servers, and an example of such a network includes a local area network (LAN), a wide area network (WAN: Wide Area Network), the Internet (WWW: World Wide Web), wired and wireless data communication networks, telephone networks, wired and wireless television networks, and the like. Examples of wireless data communication networks include 3G, 4G, 5G, 3rd Generation Partnership Project (3GPP), 5th Generation Partnership Project (5GPP), Long Term Evolution (LTE), World Interoperability for Microwave Access (WIMAX), Wi-Fi (Wi-Fi) , Internet, LAN (Local Area Network), Wireless LAN (Wireless Local Area Network), WAN (Wide Area Network), PAN (Personal Area Network), RF (Radio Frequency), Bluetooth (Bluetooth) network, NFC ( Near-Field Communication) networks, satellite broadcast networks, analog broadcast networks, Digital Multimedia Broadcasting (DMB) networks, and the like are included, but are not limited thereto.

In the following, the term at least one is defined as a term including the singular and the plural, and even if the at least one term does not exist, each element may exist in the singular or plural, and may mean the singular or plural. it will be self-evident In addition, that each component is provided in singular or plural may be changed according to embodiments.

At least one camera 100 takes a picture using a web page, an app page, a program or an application related to an image storage service using an acceleration sensor, but when the storage service providing server 300 detects an accident, the sensor It may be a device controlled by the storage service providing server 300 to store data and vehicle data or an accident detection analysis result.

Here, the at least one camera 100 may be implemented as a computer that can connect to a remote server or terminal through a network. Here, the computer may include, for example, navigation, a laptop equipped with a web browser, a desktop, and a laptop. In this case, the at least one camera 100 may be implemented as a terminal capable of accessing a remote server or terminal through a network. The at least one camera 100 is, for example, a wireless communication device that ensures portability and mobility, such as navigation, Personal Communication System (PCS), Global System for Mobile communications (GSM), Personal Digital Cellular (PDC), and PHS. (Personal Handyphone System), PDA (Personal Digital Assistant), IMT (International Mobile Telecommunication)-2000, CDMA (Code Division Multiple Access)-2000, W-CDMA (W-Code Division Multiple Access), Wibro (Wireless Broadband Internet) It may include all types of handheld-based wireless communication devices such as terminals, smartphones, smartpads, and tablet PCs.

The storage service providing server 300 may be a server that provides an image storage service web page, an app page, a program, or an application using an acceleration sensor. In addition, the storage service providing server 300 is a server that controls the camera 100 so that the camera 100 takes a picture, and collects sensor data and vehicle data when an accident is detected and inserts it as metadata. can In this case, although expressed as a server, it may be a terminal provided in a vehicle, or it may be a terminal that may serve as an AP for transmitting accident data and driver data to at least one accident processing agency server 400 . If the storage service providing server 300 is implemented as a vehicle terminal and only control is performed by a separate server, it may be a server that can be connected to the control server.

Here, the storage service providing server 300 may be implemented as a computer capable of accessing a remote server or terminal through a network. Here, the computer may include, for example, navigation, a laptop equipped with a web browser, a desktop, and a laptop.

The at least one accident handling agency server 400 may be a server such as a police, insurance company, fire department, etc. using a web page, an app page, a program or an application related to an image storage service using an acceleration sensor. In this case, the incident handling agency server 400 may be a server that receives the incident data transmitted from the storage service providing server 300 and displays the incident data on the screen so that the incident handling persons can understand the situation.

Here, the at least one incident processing agency server 400 may be implemented as a computer capable of accessing a remote server or terminal through a network. Here, the computer may include, for example, navigation, a laptop equipped with a web browser, a desktop, and a laptop. In this case, the at least one incident processing agency server 400 may be implemented as a terminal capable of accessing a remote server or terminal through a network. At least one incident processing agency server 400, for example, as a wireless communication device that guarantees portability and mobility, navigation, PCS (Personal Communication System), GSM (Global System for Mobile communications), PDC (Personal Digital Cellular) ), PHS (Personal Handyphone System), PDA (Personal Digital Assistant), IMT (International Mobile Telecommunication)-2000, CDMA (Code Division Multiple Access)-2000, W-CDMA (W-Code Division Multiple Access), Wibro (Wireless) Broadband Internet) terminals, smartphones, smart pads, tablet PCs, and the like may include all kinds of handheld-based wireless communication devices.

FIG. 2 is a block diagram illustrating a storage service providing server included in the system of FIG. 1 , and FIG. 3 is an embodiment in which an image storage service using an acceleration sensor according to an embodiment of the present invention is implemented. is a drawing for

Referring to FIG. 2 , the storage service providing server 300 may include an accident detection unit 310 , a crash accident analysis unit 320 , a storage unit 330 , and an image management unit 340 .

The storage service providing server 300 according to an embodiment of the present invention or another server (not shown) operating in conjunction with at least one camera 100 and at least one incident processing agency server 400 uses an acceleration sensor. When transmitting an image storage service application, program, app page, web page, etc., the at least one camera 100 and the at least one incident processing agency server 400 use an acceleration sensor to provide an image storage service application, program, app You can install or open pages, web pages, etc. In addition, the service program may be driven in the at least one camera 100 and the at least one incident processing agency server 400 by using a script executed in a web browser. Here, the web browser is a program that enables the use of a web (WWW: World Wide Web) service, and refers to a program that receives and displays hypertext written in HTML (Hyper Text Mark-up Language), for example, Netscape. , Explorer, Chrome, and the like. In addition, the application means an application on the terminal, for example, includes an app (App) executed in a mobile terminal (smartphone).

Referring to FIG. 2 , the accident detection unit 310 may detect an accident through at least one sensor attached to the vehicle and vehicle data. The at least one sensor may include a longitudinal and lateral acceleration sensor for detecting a collision of a vehicle and analyzing a dynamic motion, and a gyro sensor for analyzing a driver's reaction and a vehicle operation state. The vehicle data for analyzing the driver's response and the vehicle operation state may be at least one type of data capable of determining a steering angle, a direction lamp, whether braking, acceleration, gear selection, and engine RPM.

The core of the vehicle black box is to detect a traffic accident, store and analyze accident information, identify the cause of the accident, or analyze and improve the driver's driving habits to operate the analyzed information. Currently, there are various methods to detect a traffic accident situation, but most detect the accident using a front collision sensor for an airbag in the driver's or front passenger's seat, and a side collision sensor in a vehicle equipped with a side airbag. In summary, when a traffic accident occurs, the accident is detected by calculating the amount of impact measured by the acceleration sensors on the front and side. to use it

Accordingly, an embodiment of the present invention provides a longitudinal and lateral acceleration sensor for detecting a collision of a vehicle and analyzing a dynamic motion, a gyro sensor for analyzing the driver's reaction and vehicle operation state, and various switch operation information. There are devices for input, and it may be composed of an electronic control device composed of a memory to store these data, a microprocessor to control the system, etc., and an accident detection module and information analysis module for recording and analyzing accident information. The stored information includes longitudinal and lateral acceleration and vehicle speed data related to the dynamic movement of the vehicle, and steering angle, direction lights, braking status, acceleration status, etc. are related to driver manipulation.

<Accident detection hardware>

As a method of detecting a collision accident, a collision may be detected by using an acceleration sensor or an airbag explosion signal, or by manually operating the driver. When the system detects a vehicle crash, data related to the vehicle's movement and driver's actions are stored for a certain period of time before and after the accident, and these data are used in the accident information analysis program for analyzing the cause of the crash. Through this process, the trajectory of the vehicle can be checked at the accident site, and the speed change and main direction of the crashed vehicle can be checked during the crash accident cause analysis process. The main functions of the accident detection module are automatic detection of collision, calculation of speed change and main direction of the collision vehicle, and measurement of vehicle behavior. For collision determination and calculation of the speed change and main direction of the collision vehicle, for example, a Dual-Axis Capacitance type accelerometer (Analog Devices ADXL250) with a ±50G measurement range can be used.

On the other hand, for measurement of acceleration in normal vehicle driving, for example, two Single-Axis Capacitance type accelerometers (Analog Devices ADXL105) with a range of ±5G and one Yaw-Rate sensor with a range of ±100/sec (Silicon Sensing) Systems CRS-03) can be used. Because the characteristics of acceleration during impact are very different from those during normal driving, we use accelerometers with different measurement ranges and different sampling frequencies. In addition, FeRAM can be used to protect the recorded material even if the input power is turned off while the recorded material is being saved.

For example, among the acceleration sensors, a range of ±50G can be used for collision detection, a range of ±5G can be used for trajectory tracking, the detection directions are horizontal and vertical, and a frequency of 200 Hz can be used for collision detection. The range of the angular velocity sensor is ±100 degrees/sec and a frequency of 20 Hz can be used, and driver manipulation data can use driver manipulation steering angle, direction lights, braking status, acceleration status, gear selection, engine RPM, etc.

In general, the acceleration pulse is present between 0.08 and 0.17 seconds after the collision, regardless of the speed. When frequency analysis of the acceleration signal component is performed, it can be seen that the frequency distribution in which the first peak is located has weak correlation information with respect to the collision speed and exists between 50 and 70 Hz. Therefore, it can be assumed that a collision accident can be determined through this specific frequency.

The crash accident analysis unit 320 may analyze a driver reaction and a vehicle operation state using at least one sensor and vehicle data after being detected by the accident detection unit. The collision accident analysis unit 320 detects a collision of the vehicle and analyzes the dynamic movement of the vehicle by using a sensor and various switch manipulations to collect longitudinal and lateral acceleration, vehicle speed data, steering angle, direction lights, braking and acceleration. Analyzes the driver's reaction and vehicle operation status. Data used for information analysis is collected using accident detection hardware and then stored in memory, and used to analyze information related to the dynamic movement of the vehicle.

The accident detection unit 310 includes an event information and an accident analysis function for inputting basic information of a vehicle accident to manage vehicle information and accident information, and perform a function for analyzing the movement of the vehicle, vehicle information and The accident information may include an accident list, an incident number, vehicle information, an accident information file, and accident information. When the accident detection unit 310 collects vehicle movement information among vehicle information and analyzes accident driving information, it may analyze the vehicle movement information and display it as a three-dimensional driving trajectory and analysis of sensing information to visually express the vehicle movement information. The accident detection unit 310 performs noise filtering on raw data including at least one sensor data and vehicle data to analyze the sensing information, and the noise filtering is performed using a K-mean algorithm (K -means algorithm) and Kalman filter algorithm can be applied to process.

The crash accident analysis unit 320 is divided into accident analysis and real-time sensing data processing. The accident analysis is a function for analyzing vehicle movement information, and inputs vehicle information and accident information and analyzes vehicle movement. And the sensing data processing performs a function to analyze the information of the vehicle motion recorder in real time.

<Accident Analysis>

Accident analysis is a function for analyzing vehicle movement information, and performs a function to manage vehicle information and accident information, and to analyze vehicle movement. That is, it includes event information and an accident analysis function for inputting basic information of an automobile accident. In vehicle information and accident information management, information such as accident list, case number, vehicle information, accident information file, and accident information is managed. The accident vehicle information is input, the vehicle movement information stored in the storage device is imported, and the accident driving information is analyzed. Accident driving information analysis is a function for visually expressing vehicle movement information by analyzing it. Sensing data stores 10 pieces of information per second from the accelerometer and gyro sensor, and K-means algorithm and Kalman filter algorithm are applied to perform noise filtering of raw data. can be processed by

<Sensing data processing>

The accident detection data calibrates and initializes the sensor of the vehicle's motion storage device to display the accident situation data in a graph in real time. It communicates with the sensor using serial communication of 115,200bps, and the default output speed of the sensor is 100ms. The sensing information is displayed in a graph in real time, and the value can be checked through the sensing data.

The storage unit 330 may store at least one sensor and vehicle data to be synchronized with metadata. Since research in the black box video domain is relatively inactive, when the existing video summary algorithm, library, and metadata authoring tool are applied to the black box video domain, the reliability is lowered, making it difficult to use. For this reason, generating metadata for a long black box video is inefficient in terms of time and cost. Existing metadata authoring tools do not allow users to modify the generated metadata if it does not match the actual metadata, and since it creates metadata for all frames or specific frames of a video, reliability is lowered. In addition, the method of directly generating metadata by humans to ensure reliability is inefficient in terms of time efficiency and cost.

Accordingly, the storage unit 330 stores the frames of the section summarized using the video summary method in order to increase the reliability, time, and cost efficiency of metadata generation for the black box video domain, and allows the user to manually meta data. By creating data or automatically generating metadata through a module, users can modify metadata when it is inconsistent with actual metadata, thereby increasing efficiency and reliability in terms of time and cost. In addition, a metadata authoring tool with increased intuitiveness by displaying the metadata generated by the user on the time axis for easy viewing can be used.

In creating metadata of black box CCTV video, the intuitive UI can increase user convenience, time, and cost effectiveness. At this time, the video summary detector uses MOG (Mixture of Gaussian) algorithm to remove the background and apply a threshold to change pixel values over time and accumulate them to show a heat map image as a result, and the user can can be checked The user can generate metadata through the module in the video metadata auto-generation viewer using the frame extracted through the video summary detector. If the generated metadata does not match the actual metadata, the user can edit the metadata through the metadata editing viewer. The automatically generated metadata is tagged by reflecting the metadata modified by the user, and you can check the top 5 labels that appear the most.

When the metadata is created, how much and when the metadata of the object/situation of interest was created in the video can be displayed through the time axis to increase intuition. The generated metadata information has the corresponding detection object ID, class, frame number, ROI area X, Y, Width, and Height, and can be saved as a file so that it can be used as data in case of an accident later.

The image management unit 340 may store the image data captured by the camera 100 to be synchronized with at least one sensor and vehicle data in the storage unit 330 . The camera 100 may photograph the front of the vehicle and record the accident as metadata (MetaData) when an accident is detected.

In addition, it is also possible to facilitate the collection of data for reporting traffic law violations through real-time screen recognition in the image frame in the image data captured by the camera 100 . The storage service providing server 300 analyzes the road environment, including structures and obstacles, lanes, vehicle license plates, lighting devices, etc. on the road while driving, and connects with various databases, that is, in connection with various databases such as the National Police Agency or the cleaning department. It enables real-time inquiry of traffic laws and vehicle numbers, and can be used for the arrest of illegally parked and stopped vehicles, criminal and stolen vehicles, delinquent vehicles, and wanted vehicles. In addition, it can be linked with a mechanical black box via Bluetooth. The recently emerging 'connected black box', that is, a voice recognition function through interworking with a mechanical black box that can be linked with Bluetooth, is added to record immediately when the driver detects a violation. can make it happen In addition, it is linked with the smartphone's photo gallery to make it easy to upload data. In order to automatically create and classify public interest reporting data, it detects traffic violations through real-time screen recognition and links and contrasts with various databases learned through machine learning to automatically create and classify reporting data by violation. It can also be implemented to organize the data.

Currently, it is very cumbersome to file a traffic-related public interest report. Since Corona (COVID-19), news of drunk driving and traffic accidents has not ceased every day. Even so, there are not many reports of violations of traffic laws in the public interest, and it is expected that a very large number of violations of traffic laws are occurring. Also, if you have had an accident, you have to edit the video or check it from the time you were in the accident, which is also very cumbersome. Therefore, by making this cumbersome task very simple, the convenience of the reporting process can be greatly increased. In addition, drivers' compliance with traffic laws can lead to safe driving, improve the traffic environment, and foster a sense of order.

Hereinafter, an operation process according to the configuration of the storage service providing server of FIG. 2 will be described in detail with reference to FIG. 3 as an example. However, it will be apparent that the embodiment is only one of various embodiments of the present invention and is not limited thereto.

Referring to FIG. 3 , (a) when an accident occurs, the storage service providing server 300 collects at least one sensor data and at least one vehicle data to analyze the collision, and accordingly, at least one accident handling agency When sending a rescue call to the server 400 , it is possible to estimate and transmit the driver's state according to the current crash state. Alternatively, only the crash status is transmitted and the severity of the crash can be estimated by the accident handling agency. Since the raw data is directly sent to each insurance company, police station, fire department, etc., after the accident, the user does not have to file an insurance accident handling report with the insurance company. In the absence of a rescue signal, it is possible to automatically contact you without sending a rescue signal. In addition, as shown in FIG. 4 , by automatically generating and synchronizing metadata, it is possible to avoid wasting manpower and time when analyzing an accident or performing the role of a black box.

The matters not described with respect to the method for providing an image storage service using the acceleration sensor of FIGS. 2 to 4 are the same as those described for the method for providing an image storage service using the acceleration sensor with reference to FIG. 1 or from the contents described above. Since it can be easily inferred, the following description will be omitted.

5 is a diagram illustrating a process in which data is transmitted/received between components included in the system for providing an image storage service using the acceleration sensor of FIG. 1 according to an embodiment of the present invention. Hereinafter, an example of a process in which data is transmitted and received between each component will be described with reference to FIG. 5, but the present application is not limited to such an embodiment, and the example shown in FIG. 5 according to various embodiments described above will be described. It is apparent to those skilled in the art that the data transmission/reception process may be changed.

Referring to FIG. 5 , the storage service providing server detects an accident through at least one sensor attached to the vehicle and vehicle data ( S5100 ).

Then, the storage service providing server analyzes the driver's reaction and vehicle operation state using at least one sensor and vehicle data after sensing (S5200).

In addition, the storage service providing server stores at least one sensor and vehicle data to be synchronized with the metadata (S5300), and stores image data captured by the camera to be synchronized with the at least one sensor and vehicle data (S5400).

The order between the above-described steps ( S5100 to S5400 ) is merely an example and is not limited thereto. That is, the order between the above-described steps ( S5100 to S5400 ) may be mutually changed, and some of these steps may be simultaneously executed or deleted.

Matters that are not described with respect to the method for providing an image storage service using the acceleration sensor of FIG. 5 are the same as those described for the method of providing an image storage service using the acceleration sensor with reference to FIGS. 1 to 4 or from the contents described above. Since it can be easily inferred, the following description will be omitted.

The method for providing an image storage service using an acceleration sensor according to an embodiment described with reference to FIG. 5 may also be implemented in the form of a recording medium including instructions executable by a computer, such as an application or program module executed by a computer. can Computer-readable media can be any available media that can be accessed by a computer and includes both volatile and nonvolatile media, removable and non-removable media. Also, computer-readable media may include all computer storage media. Computer storage media includes 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.

The method for providing an image storage service using an acceleration sensor according to an embodiment of the present invention described above is performed by using an application basically installed in a terminal (which may include a program included in a platform or operating system, etc. basically installed in the terminal). may be executed, and may be executed by an application (ie, a program) directly installed in the master terminal by a user through an application providing server such as an application store server, an application or a web server related to the corresponding service. In this sense, the method for providing an image storage service using an acceleration sensor according to an embodiment of the present invention described above is implemented as an application (that is, a program) installed basically in a terminal or directly installed by a user, and is transmitted to a computer such as a terminal. It may be recorded on a readable recording medium.

The above description of the present invention is for illustration, and those of ordinary skill in the art to which the present invention pertains can understand that it can be easily modified into other specific forms without changing the technical spirit or essential features of the present invention. will be. Therefore, it should be understood that the embodiments described above are illustrative in all respects and not restrictive. For example, each component described as a single type may be implemented in a dispersed form, and likewise components described as distributed may be implemented in a combined form.

The scope of the present invention is indicated by the following claims rather than the above detailed description, and all changes or modifications derived from the meaning and scope of the claims and their equivalent concepts should be interpreted as being included in the scope of the present invention. do.

Claims (6)

A camera that records the accident as metadata (MetaData) when photographing the front of the vehicle and detecting an accident; and
An accident detection unit that detects an accident through at least one sensor attached to the vehicle and vehicle data, and a collision that analyzes a driver reaction and vehicle operation state using the at least one sensor and vehicle data after detecting the accident by the accident detection unit An accident analysis unit, a storage unit for storing the at least one sensor and vehicle data to be synchronized with the metadata, and an image for storing image data captured by the camera in the storage unit to be synchronized with the at least one sensor and vehicle data Including a; image storage service providing server including a management unit;
The storage unit stores the summarized video frame so that the user can generate metadata, compares the metadata generated by the user with the actual metadata, and allows the user to modify the metadata when there is a discrepancy, and provides the user with With respect to the metadata generated by
The at least one sensor may include: a longitudinal and lateral acceleration sensor for detecting a collision of the vehicle and analyzing a dynamic motion; It includes; a gyro sensor for analysis of the driver's reaction and vehicle operation state;
The vehicle data for analyzing the driver's reaction and vehicle operation state is at least one type of data capable of determining a steering angle, direction lights and braking, acceleration, gear selection, and engine RPM,
The crash accident analysis unit manages vehicle information and accident information, and includes an event information and an accident analysis function for inputting basic information of a vehicle accident, so as to perform a function for analyzing the movement of the vehicle, the vehicle information and accident information includes an accident list, case number, vehicle information, accident information file, and accident information, and when collecting vehicle movement information among vehicle information and analyzing accident driving information, sensing information to analyze and visually express vehicle movement information analysis and display as a three-dimensional driving trajectory, and for analyzing the sensing information, noise filtering of raw data including the at least one sensor data and vehicle data is performed, and the noise filtering is An image storage service providing system using an acceleration sensor, characterized in that it is configured to process by applying a K-means algorithm and a Kalman filter algorithm.
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