KR20230127439A - Big-data constructing and using system and method for road conditions applying black-box or special mounted camera in vehicles - Google Patents

Abstract

The present invention acquires and accumulates many types of data on the road while driving using a built-in camera or a separately mounted camera provided in a black box installed in a vehicle traveling on national roads, analyzes the accumulated data, and converts it into big data. It relates to a system and method for building and utilizing big data on road conditions using a black box in a vehicle or a separately installed camera, which is implemented to be used in various ways by using AI vision recognition. Classify and collect road situation images through AI vision recognition of road conditions while driving using a camera mounted thereon; The big data construction unit extracts and accumulates road situation data from the road situation images classified and collected by the AI vision recognition unit, and builds big data; And the big data utilization unit reads the big data built by the big data construction unit and provides corresponding services for each service type.

Description

Big-data constructing and using system and method for road conditions applying black-box or special mounted camera in vehicles}

The technical field of the present invention relates to a system and method for constructing and utilizing big data on road conditions using a black box in a vehicle or a separately mounted camera. Acquiring and accumulating many types of data on the road while driving using a built-in camera or a separately installed camera, analyzing the accumulated data and converting it into big data to utilize an in-vehicle black box or a separately installed camera for various uses It is about a system and method for building and utilizing big data on road conditions.

As GPS technology develops and the spread of portable wireless devices rapidly increases, the technology of the road management system that applies it is also developing. The road management system collects conditions for each road using GPS information of a road manager's vehicle or portable wireless device, analyzes the collected data, processes the collected data into road information, and provides it to the road manager.

For example, a road guidance management system provides the driver with the shortest distance based on a route stored in a navigation device and a fixed driving time. The shortest distance is provided to the driver. However, this real-time road guidance management system only provides information related to the driving time along the driving route, that is, when congestion occurs on a specific road, whether it is congestion due to a simple increase in traffic volume, an accident, or road construction. It is not possible to accurately determine the cause of road congestion due to traffic congestion or the like. In addition, since the real-time road guidance management system updates information at the time when congestion occurs, it is difficult to provide real-time traffic congestion due to an unexpected accident. Accordingly, it will be said that a road management system and method using image big data taken from the outside of a vehicle are needed in order to more immediately analyze the situation for each road, update the road information, and provide it to the road manager.

Korean Patent Registration No. 10-1833359 (registered on February 22, 2018) discloses a method and apparatus for collecting traffic information using big data of external images of a vehicle, including at least one generating object classification information representing information on at least one of a location, type, and state of an object; Based on the object classification information, generating situation analysis information that is information obtained by analyzing an external situation of the vehicle; and selectively transmitting the situation analysis information to the server based on whether the situation analysis information corresponds to a traffic obstruction event, which is an event that obstructs the passage of a vehicle. The step of including the lane obstruction ratio, which is the ratio between the number of lanes obstructed from traffic and the total number of lanes, and the expected duration until the external situation is cleared up in the situation analysis information, and transmitting the situation analysis information to the server is the situation analysis information It is characterized in that it is determined whether the situation analysis information corresponds to a traffic obstruction event based on at least one of the lane obstruction ratio and the expected duration included in the traffic obstruction event. According to the disclosed technology, it is possible to analyze big data of images taken from the outside of the vehicle using a deep learning algorithm, and use the analysis result to interpret the external situation of the road, and without a separate user input, the outside of the road Traffic information can be automatically collected from the situation.

Korean Patent Registration No. 10-2192420 (registered on December 11, 2020) is a cost-effective black ice big data collection, more accurate black ice prediction analysis based on big data, black ice information sharing, and control for black ice removal. It is possible to build and provide an integrated system related to black ice, and collect black ice analysis data during road patrol by installing sensors on patrol vehicles owned by each branch of the road construction, located at intervals of about 70 km, in a cost-effective way. It is possible to collect big data for black ice analysis, and by collecting black ice presence data on the road through the patrol vehicle application, it is possible to accurately and variously set the black ice judgment standard value, thereby making it more accurate in the future. It is possible to predict black ice, and notify drivers and road managers of black ice danger zones in real time based on the collected big data. User convenience can be enhanced by providing various user interfaces (UIs) on the map, such as outputting black ice danger zones by color and outputting detailed data of registered danger zones. and through big data-based road management using black boxes for notification vehicles, road managers can pre-spray calcium chloride in areas where black ice is predicted, thereby preemptively securing winter traffic safety. A hazardous area management system is disclosed. According to the disclosed technology, a black ice data collection device that collects black ice analysis data in conjunction with a GPS location while driving on a road; and a black ice management server that receives black ice analysis data for the GPS location from the black ice data collection device through the network, analyzes the black ice analysis data, and sets black ice prediction information for the GPS location; The black ice analysis data includes black ice data collection device ID, temperature and humidity sensor ID, data collection time, GPS information, air temperature, road surface temperature and humidity; The black ice analysis data further includes state information indicating whether or not there is black ice at the GPS location; State information is acquired based on an external input in the black ice data collection device; The black ice management server includes a receiving unit that receives black ice analysis data from a black ice data collection device; a storage unit for storing black ice analysis data; and an analyzer configured to set black ice determination reference values for GPS locations or black ice prediction information based on the black ice analysis data; The black ice determination reference value for the GPS location is at least one of a predetermined humidity value, a predetermined road surface temperature value, a predetermined air temperature value, and a predetermined difference between the air temperature and the road surface temperature; The black ice determination criterion for the GPS location is characterized in that it is set based on black ice analysis data corresponding to state information indicating the existence of black ice.

In the conventional technology as described above, traffic information is collected using external image big data of the vehicle, or a black box for a vehicle is used to preemptively secure traffic safety in winter, such as managing a black ice risk area. , It performs only one function, but it is diverse, such as tracking crime, stolen or delinquent vehicles, checking vehicles that have broken down or accidents, checking traffic accidents, road kills or road damage, linking towing or maintenance services, and providing accident or alternative routes. It still has some downsides that I can't use. In addition, in the prior art, not only is there no benefit to a provider that provides data obtained through a vehicle black box, but it is difficult to actually collect data, such as using a paid communication network for data transmission.

Korean Patent Registration No. 10-1833359 Korean Patent Registration No. 10-2192420

The problem to be solved by the present invention is to solve the above-mentioned necessity or disadvantage, using a built-in camera provided in a black box built into a vehicle traveling on national roads or a separately mounted camera to drive a road while driving A system and method for constructing and utilizing big data for road conditions using a black box in a vehicle or a separately installed camera that acquires and accumulates many types of data from the vehicle, analyzes and transforms the accumulated data into big data, and uses it in various ways. is to provide

As a means for solving the above problems, according to one feature of the present invention, a road situation image is generated through AI vision recognition of the road situation while driving using a built-in camera of a black box built into a vehicle or a separately mounted camera. AI vision recognition unit for classification and collection; A big data construction unit for constructing big data by extracting and accumulating road situation data from road situation images classified and collected by the AI vision recognition unit; And a big data utilization unit for reading the big data built in the big data construction unit and providing corresponding services for each service type, building big data for road conditions using a black box in the vehicle or a separately installed camera. and a utilization system.

In one embodiment, the AI vision recognition unit is characterized in that it recognizes road conditions, vehicle conditions, and road surrounding conditions as road conditions during driving.

In one embodiment, the AI vision recognition unit is characterized by including location information using a GPS module in a road condition image obtained using a built-in camera of a vehicle black box or a separately mounted camera.

In one embodiment, the AI vision recognition unit is characterized in that the classification image information transmitted from the big data construction unit is stored in an internal memory for each type of road management service and service code corresponding to the type of service.

In one embodiment, the AI vision recognition unit, based on the classified image information stored in the internal memory, obtains a road condition image using a built-in camera of a vehicle black box or a separately mounted camera, which corresponds to a certain road management service. recognition, and collects road condition images by classifying them according to service types.

In one embodiment, the AI vision recognition unit checks the service type of the road condition image acquired using the built-in camera of the vehicle black box or a separately installed camera, and sends a service code corresponding to the checked service type to the road condition image. It is characterized in that it is included and transmitted to the big data building unit.

In one embodiment, the AI vision recognition unit is provided in a black box for a vehicle to perform AI vision recognition of a situation around the road while driving and recognition of an accident state on the road, and is provided with a free communication module for short-range communication to enable the vehicle driver's mobile By performing a short-range communication connection with a terminal or a communication module built into a vehicle, a road situation image (eg, service classification, location information, an image related to a service among input images, etc. Including) is characterized in that for transmitting to the big data building unit.

In one embodiment, the AI vision recognition unit is provided with a free communication module for short-range communication to perform a short-range communication connection to a free communication network, and transmits a road condition image to the big data construction unit through a free communication network.

In one embodiment, the AI vision recognition unit is provided in a black box for a vehicle, and includes a paid communication module for remote communication, and performs a remote communication connection with the big data construction unit through the paid communication module to display an image of a road situation. characterized in that it is transmitted to the big data construction unit.

In one embodiment, the AI vision recognition unit is provided in a separate road management server and is characterized in that it receives a road condition image obtained using a built-in camera of a vehicle black box or a separately mounted camera.

In one embodiment, the AI vision recognition unit checks whether the AI vision recognition unit installed in the accident vehicle is operating normally in the case of a breakdown or accident vehicle confirmation service or a traffic accident when checking the service type of the road condition image. It is characterized by generating a normal confirmation message for confirmation and transmitting it to the AI vision recognition unit installed in the accident vehicle.

In one embodiment, the AI vision recognition unit, when receiving a normal confirmation message from the AI vision recognition unit installed in another vehicle, generates a normal notification message to inform that it is normally driven and is installed in another vehicle characterized in that it is transmitted to the AI vision recognition unit.

In one embodiment, the AI vision recognition unit, when receiving a normal notification message within a predetermined time after transmitting the normal confirmation message, recognizes it as a minor state and generates an accident notification command to notify the surroundings of the accident to the accident vehicle characterized in that it is transmitted to the AI vision recognition unit installed in

In one embodiment, the AI vision recognition unit, when receiving an accident notification command transmitted from an AI vision recognition unit installed in another vehicle, transmits it to the vehicle ECU according to the received accident notification command to turn on the vehicle warning light It is characterized by giving or sounding a vehicle horn.

In one embodiment, if the AI vision recognition unit does not receive a normal notification message even after a predetermined time elapses after transmitting the normal confirmation message, it recognizes it as a serious condition and generates a message requesting help to the driver. It is characterized in that it outputs through an output means or generates an accident notification message to notify a serious state and transmits it to a related institution or person concerned.

In one embodiment, the big data construction unit determines which road management service corresponds to a road condition image acquired using a built-in camera of a black box for a vehicle or a separately installed camera, service type and service Classification image information corresponding to each service code corresponding to the type is set and registered, and the set-registered classification image information is transmitted to the AI vision recognition unit.

In one embodiment, the big data construction unit responds to each service type and service code corresponding to the service type in order to classify and extract road condition data of service types that can be obtained on the road while driving by service type. It is characterized in that standard extraction data to be extracted from the road condition image is set and registered.

In one embodiment, the big data construction unit checks the service code included in the road condition image transmitted from the AI vision recognition unit, checks standard extraction data corresponding to the checked service code, and checks the checked standard extraction data Based on this, the road condition data corresponding to the service code identified in the road condition image transmitted from the AI vision recognition unit is extracted, and the extracted road condition data is analyzed, converted into big data, and stored to build AI vision recognition driving big data. to be

In one embodiment, the big data construction unit improves recognition accuracy through data learning; By continuously learning the road condition image transmitted from the AI vision recognition unit and the road condition data extracted from the road condition image, classification image information corresponding to the service type and service code corresponding to the service type and service type and service type It is characterized in that the standard extraction data to be extracted from the road condition image is upgraded and registered for each service code corresponding to the corresponding service code.

In one embodiment, the big data construction unit extracts vehicle color, vehicle type, and license plate number as road situation data from the road situation image transmitted from the AI vision recognition unit in case of crime, theft or delinquent vehicle tracking service. characterized by

In one embodiment, the vehicle number of theft, crime, or arrears is periodically transmitted from the big data construction unit to the AI vision recognition unit, and the AI vision recognition unit recognizes the vehicle number from the input image and the recognized vehicle number It is characterized in that the information is transmitted to the big data construction unit when the received license plate number coincides with the received vehicle number.

In one embodiment, the big data construction unit, in the case of a breakdown or accident vehicle confirmation service, vehicle bonnet opening, vehicle emergency light lighting, smoke, flame, falling objects as road situation data from the road situation image transmitted from the AI vision recognition unit It is characterized by extracting information of.

In one embodiment, the big data construction unit, in the case of a traffic accident, road kill or road damage confirmation service, uses road situation data from the road situation image transmitted from the AI vision recognition unit to determine vehicle crashes, dead animals, and road damage. It is characterized by extracting information.

In one embodiment, the big data construction unit performs cloud management for large-capacity information management according to a solution for classifying and managing road situation data extracted from road situation images transmitted from the AI vision recognition unit, and large-capacity traffic distribution technology It is characterized in that application load balancing is performed using , and valid information determination algorithms for removing redundant information and filtering misrecognized information for road condition data are performed.

In one embodiment, the big data utilization unit is a road management service, crime, theft or delinquent vehicle tracking service, breakdown or accident vehicle confirmation service, traffic accident, road kill or road damage confirmation service, towing or maintenance service linkage service, It is characterized by providing a retention or alternative route providing service.

In one embodiment, the big data utilization unit processes the big data built in the big data construction unit according to the type of road management service and each service code corresponding to the type of service, so that it is provided as a road management service. It is characterized in that data is processed into road management data corresponding to each service type and service code corresponding to the service type, and a provision data form to be provided is set and registered.

In one embodiment, the big data utilization unit is characterized by setting and registering interlocking information for linking with a related institution or person concerned for each type of service and service code corresponding to the type of service.

In one embodiment, the big data utilization unit checks the provided data form corresponding to the type of road management service and service code corresponding to the service type, and reads from the big data construction unit based on the checked provided data form. Big data is processed into road management data corresponding to each service type and service code corresponding to the service type and provided, and the corresponding interlocking information is used for each service type and service code corresponding to the service type to communicate with related organizations or related parties. It is characterized in that it interlocks and provides processed road management data to interlocked organizations or related parties.

In one embodiment, the big data utilization unit analyzes vehicle accident-prone areas using the big data built by the big data construction unit, analyzes road conditions by season and region, and provides the data to related organizations.

In one embodiment, the big data utilization unit receives information on a crime, theft or arrears vehicle from the police or the National Tax Service, detects a crime, theft or arrears vehicle, and recognizes an accident situation through license plate recognition in the AI vision recognition unit. It is characterized by providing a crime, theft or delinquent vehicle tracking service to the police or the National Tax Service by using the big data built by the big data construction unit by AI vision situation detection through

In one embodiment, the big data utilization unit uses the big data built by the big data construction unit by recognizing driving obstruction in construction and driving obstruction situations and traffic accident recognition in traffic accident situations in the AI vision recognition unit It is characterized by providing a navigation service or an alternative route providing service to a navigation provider or Korea Expressway Corporation.

In one embodiment, the big data utilization unit, to a provider that provides a road condition image obtained using a built-in camera of a vehicle black box or a separately installed camera, provides shared vehicle quality assurance, accident prevention service quality improvement, and vehicle purchase benefits. In addition, it is characterized by granting points that can provide benefits of insurance premium discounts in preparation for video provision and utilization.

In one embodiment, the big data utilization unit is characterized in that it grants 1 point for each number of road situation images provided to the big data construction unit and 2 points for each number of actually used images to the provider.

As a means for solving the above problems, according to another feature of the present invention, the AI vision recognition unit performs AI vision recognition for road conditions while driving using a built-in camera of a black box built into a vehicle or a separately mounted camera. Classifying and collecting road situation images through the; Building big data by extracting and accumulating road situation data from the road situation images classified and collected by the AI vision recognition unit by the big data construction unit; and big data utilization unit reading the big data built by the big data construction unit and providing corresponding services for each type of service. It provides construction and utilization methods.

As an effect of the present invention, many types of data are acquired and accumulated on the road while driving using a built-in camera or a separately mounted camera provided in a black box built into a vehicle traveling on national roads, and the accumulated data By providing a system and method for constructing and utilizing big data on road conditions using a black box in a vehicle or a separately installed camera, which is implemented to be used in various ways by analyzing and converting big data, crime, theft or delinquent vehicle tracking, breakdown or accident It can be used in a variety of ways, such as vehicle identification, traffic accident, road kill or road damage confirmation, towing or maintenance service connection, accident or alternative route provision, etc. Also, benefits are provided to providers who provide data acquired through vehicle black boxes. And it is possible to provide convenience in collecting data by transmitting data using a vehicle built-in communication module or wireless terminal connection through a local area network.

1 is a diagram illustrating a system for constructing and utilizing big data for road conditions using a black box in a vehicle or a separately mounted camera according to an embodiment of the present invention.
FIG. 2 is a diagram illustrating the AI vision recognition unit in FIG. 1 as a first example.
FIG. 3 is a diagram illustrating the AI vision recognition unit in FIG. 1 as a second example.
4 is a diagram illustrating the big data utilization unit in FIG. 1 as an example.
5 is a diagram illustrating a method of constructing and utilizing big data for road conditions using a black box in a vehicle or a separately mounted camera according to an embodiment of the present invention.
6 and 7 are diagrams illustrating a method of constructing and utilizing big data on road conditions using a black box in a vehicle or a separately mounted camera according to an embodiment of the present invention as an example of information sharing with public institutions.
8 and 9 are diagrams illustrating a method of constructing and utilizing big data on road conditions using a black box in a vehicle or a separately mounted camera according to an embodiment of the present invention as an example of caution/caution driving information.

Hereinafter, with reference to the accompanying drawings, embodiments of the present invention will be described in detail so that those skilled in the art can easily carry out the present invention. However, since the description of the present invention is only an embodiment for structural or functional description, the scope of the present invention should not be construed as being limited by the embodiments described in the text. That is, since the embodiment can be changed in various ways and can have various forms, it should be understood that the scope of the present invention includes equivalents capable of realizing the technical idea. In addition, since the object or effect presented in the present invention does not mean that a specific embodiment should include all of them or only such effects, the scope of the present invention should not be construed as being limited thereto.

The meaning of terms described in the present invention should be understood as follows.

Terms such as "first" and "second" are used to distinguish one component from another, and the scope of rights should not be limited by these terms. For example, a first element may be termed a second element, and similarly, a second element may be termed a first element. It should be understood that when an element is referred to as “connected” to another element, it may be directly connected to the other element, but other elements may exist in the middle. On the other hand, when an element is referred to as being “directly connected” to another element, it should be understood that no intervening elements exist. Meanwhile, other expressions describing the relationship between components, such as “between” and “immediately between” or “adjacent to” and “directly adjacent to” should be interpreted similarly.

Singular expressions should be understood to include plural expressions unless the context clearly dictates otherwise, and terms such as “comprise” or “having” refer to a described feature, number, step, operation, component, part, or It should be understood that it is intended to indicate that a combination exists, and does not preclude the possibility of the presence or addition of one or more other features, numbers, steps, operations, components, parts, or combinations thereof.

All terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present invention belongs, unless defined otherwise. Terms defined in commonly used dictionaries should be interpreted as consistent with meanings in the context of related art, and cannot be interpreted as having ideal or excessively formal meanings unless explicitly defined in the present invention.

Now, a system and method for constructing and utilizing big data for road conditions using a black box in a vehicle or a separately mounted camera according to an embodiment of the present invention will be described in detail with reference to drawings.

1 is a diagram illustrating a system for constructing and utilizing big data for road conditions using a black box in a vehicle or a separately mounted camera according to an embodiment of the present invention, and FIG. 2 is a diagram illustrating an AI vision recognition unit in FIG. 1 It is a diagram for explaining one example, FIG. 3 is a diagram for explaining the AI vision recognition unit in FIG. 1 as a second example, and FIG. 4 is a diagram for explaining the big data utilization unit in FIG. 1 as an example.

1 to 4, the big data construction and utilization system 100 for road conditions using a black box in a vehicle or a separately mounted camera includes an AI (artificial intelligence) vision recognition unit 110, It includes a big data construction unit 120 and a big data utilization unit 130.

The AI vision recognition unit 110 uses the built-in camera of the black box built into the vehicle or a separately installed camera to measure the AI for road conditions (ie, road or vehicle conditions, including all conditions around the road, etc.) while driving. Through vision recognition, road situation images are classified and collected, and the classified and collected road situation images (eg, including service classification, location information, and service-related images among input images) are stored in the big data construction unit (120 ) is passed on.

In one embodiment, the AI vision recognition unit 110 may store the classification image information transmitted from the big data construction unit 120 in internal memory for each type of road management service and service code corresponding to the type of service.

In one embodiment, the AI vision recognition unit 110 determines which road management service ( That is, it is possible to check whether the image corresponds to the type of service), and thus road condition images obtained using a built-in camera of a vehicle black box or a separately installed camera can be classified and collected according to the type of service.

In one embodiment, the AI vision recognition unit 110 may check the service type of the road condition image acquired using the built-in camera of the vehicle black box or a separately installed camera, and the service corresponding to the checked service type. The code may be included in the classified and collected road condition image and transmitted to the big data construction unit 120 .

In one embodiment, as shown in FIG. 2, the AI vision recognition unit 110 is provided in a black box for a vehicle and can perform AI vision recognition of a situation around the road while driving and recognition of an accident state on the road, etc. , In this case, by providing a free communication module for short-range communication and performing a short-range communication connection with a mobile terminal of the vehicle driver or a communication module built in the vehicle, the road classified and collected through the mobile terminal or the communication module built in the vehicle The situation image can be transmitted to the big data construction unit 120, and otherwise, the free communication module is used to perform a short-range communication connection to a free communication network such as wifi, and the road conditions collected in the classification through the free communication network The image may be transmitted to the big data construction unit 120.

In one embodiment, the AI vision recognition unit 110 is provided in the vehicle black box, but when a paid communication module for remote communication is also provided, it is connected to the big data construction unit 120 and remote communication through the corresponding paid communication module. may be performed to transmit the classified and collected road condition image to the big data construction unit 120 .

In one embodiment, the AI vision recognition unit 110, as shown in FIG. 3, may be provided in a separate road management server together with the big data construction unit 120, in which case a black box for a vehicle is built in. A road condition image (which may include location information using a GPS module, etc.) obtained using a camera or a separately mounted camera may be transmitted using the above-described method or the like.

In an embodiment, the AI vision recognition unit 110 recognizes the AI vision recognition installed in the accident vehicle in the case of a breakdown or accident vehicle confirmation service or a traffic accident when checking the service type of the acquired road condition image. A normal confirmation message for confirming whether the unit 110 is operating normally can be generated and transmitted to the AI vision recognition unit 110 installed in the accident vehicle.

In one embodiment, when the AI vision recognition unit 110 receives a normal confirmation message transmitted from the AI vision recognition unit 110 installed in another vehicle, it is normal to inform that it is normally driven. A notification message can be generated and transmitted to the AI vision recognition unit 110 installed in another vehicle.

In one embodiment, the AI vision recognition unit 110, when receiving a normal notification message within a predetermined time (eg, 5 seconds) after transmitting the normal confirmation message, recognizes the accident as a minor state, and the surroundings It is possible to generate an accident notification command for notifying the accident and transmit it to the AI vision recognition unit 110 installed in the accident vehicle.

In one embodiment, when the AI vision recognition unit 110 receives an accident notification command transmitted from the AI vision recognition unit 110 installed in another vehicle, the vehicle ECU according to the received accident notification command. Accident notification may be performed by turning on a vehicle warning light or sounding a vehicle horn.

In one embodiment, when the AI vision recognition unit 110 does not receive the normal notification message even after a predetermined time (eg, 5 seconds) has elapsed after sending the normal confirmation message, it recognizes it as a serious state and , A message requesting help may be generated and output through an output means such as an LCD or a speaker, or an accident notification message may be generated and transmitted to related organizations or persons concerned.

The big data construction unit 120 includes road situation data from the road situation image transmitted from the AI vision recognition unit 110 (eg, including service classification, location information, and service-related images among input images). is extracted and accumulated to construct big data.

In one embodiment, the big data construction unit 120 determines which road management service (ie, service type) (eg, crime , stolen or delinquent vehicle tracking service, breakdown or accident vehicle confirmation service, traffic accident, road kill or road damage confirmation service, towing or maintenance service linkage service, accident or alternative route provision service, etc.) For this purpose, classification image information corresponding to the service type and service code corresponding to the service type may be set and registered, and the setting-registered classification image information may be delivered to the AI vision recognition unit 110.

In one embodiment, the big data construction unit 120 classifies and extracts road condition data of many service types that can be obtained on the road while driving by service type, and the service type and service code corresponding to the service type. Correspondingly, standard extraction data to be extracted from the road condition image may be set and registered.

In one embodiment, the big data construction unit 120 may check the service code included in the road condition image transmitted from the AI vision recognition unit 110, and also check the standard extraction data corresponding to the checked service code. Therefore, based on the identified standard extraction data, road condition data corresponding to the identified service code may be extracted from the road condition image transmitted from the AI vision recognition unit 110, and the extracted road condition data may be analyzed. It can be converted into big data and stored to build AI vision recognition driving big data.

In one embodiment, the big data construction unit 120 improves recognition accuracy through data learning; By continuously learning the road situation image transmitted from the AI vision recognition unit 110 and the road situation data extracted from the road situation image transmitted from the AI vision recognition unit 110, each service type and service code corresponding to the service type Corresponding classification image information, service type, and standard extraction data to be extracted from road condition images can be upgraded and registered in response to each service code corresponding to the service type. reliability can be improved.

In one embodiment, in the case of a crime, theft or delinquent vehicle tracking service, the big data construction unit 120 converts vehicle color, vehicle type, You can extract the license plate number, etc.

In one embodiment, the big data construction unit 120, in the case of a breakdown or accident vehicle confirmation service, the vehicle bonnet is opened, the vehicle emergency light is turned on, Information on smoke, flames, and falling objects can be extracted.

In one embodiment, in the case of a traffic accident, road kill or road damage confirmation service, the big data construction unit 120 converts road situation data from the road situation image transmitted from the AI vision recognition unit 110 to vehicle collision, animal It can extract information such as dead bodies and road damage.

In one embodiment, the big data construction unit 120 is cloud management for large-capacity information management according to a solution for classifying and managing road situation data extracted from road situation images transmitted from the AI vision recognition unit 110. ), can perform application load balancing using a large-capacity traffic distribution technology, and can perform valid information determination algorithms such as removal of redundant information on road condition data and filtering of misrecognized information. can do.

The big data utilization unit 130 reads the big data built by the big data construction unit 120 and provides services corresponding to each type of service (e.g., crime, theft or delinquent vehicle tracking service, breakdown or accident vehicle identification). service, traffic accident, road kill or road damage confirmation service, towing or maintenance service connection service, accident or alternative route provision service, etc.).

In one embodiment, the big data utilization unit 130 processes the big data built in the big data construction unit 120 according to the type of road management service and the service code corresponding to the service type, and provides it as a road management service. In order to do this, big data can be processed into road management data corresponding to the service type and service code corresponding to the service type, and the provided data form to be provided can be set and registered, and also corresponding to the service type and service type. For each service code to be used, interlocking information for linking with related organizations or related persons (eg, police, National Tax Service, Korea Expressway Corporation, towing company, maintenance company, navigation provider, etc.) may be set and registered.

In one embodiment, the big data utilization unit 130 may check the type of road management service and the provided data form corresponding to each service code corresponding to the type of service, and based on the identified provided data form, the big data The big data read from the construction unit 120 may be processed into road management data corresponding to the service type and service code corresponding to the service type, and provided. At this time, as shown in FIG. 4, the service type and the service type may be provided. For each service code corresponding to, it is possible to link with a related agency or related person using corresponding interlocking information, and to provide the processed road management data to the related related institution or related person.

In one embodiment, the big data utilization unit 130 analyzes vehicle accident-prone areas using the big data built by the big data construction unit 120 and analyzes the road conditions by season and region to the related institutions (for example, , Korea Expressway Corporation, etc.)

In one embodiment, the big data utilization unit 130 receives information on crime, theft or delinquent vehicles from the police or the National Tax Service, and recognizes the license plate in the AI vision recognition unit 110 for crime, theft or delinquent vehicles. Real-time information sharing and intelligent data by providing a crime, theft or delinquent vehicle tracking service to the police or the National Tax Service using the big data built by the big data construction unit 120 by AI vision situation detection through detection and accident situation recognition. It can be transmitted to make it easy to grasp the real-time movement route.

In one embodiment, the big data utilization unit 130, the big data construction unit 120 by recognizing traffic accidents such as traffic accident situations and driving obstruction recognition such as construction and driving obstruction situations in the AI vision recognition unit 110 ), it is possible to easily provide intelligent safe driving information, accident information, alternative route information, etc. by providing an accident or alternative route service to a navigation provider or Korea Expressway Corporation using big data built in ).

In one embodiment, the big data utilization unit 130 provides a provider that provides a road condition image obtained using a built-in camera of a vehicle black box or a separately mounted camera, quality assurance of shared vehicles, improvement of accident prevention service quality, Points that can provide benefits such as vehicle purchase benefits and insurance premium discounts may be given in preparation for video provision and utilization. For example, 1 point for each number of road condition images provided to the big data construction unit 120 and 2 points for each number of actually utilized by the big data utilization unit 130 may be provided.

In one embodiment, the big data utilization unit 130 may perform data control and notification operation algorithms, such as analyzing demand information of a demand company or institution, processing it into corresponding information, and managing communication interfaces between heterogeneous servers. can

Big data construction and utilization system 100 for road conditions using a black box in a vehicle or a separately mounted camera having the configuration described above, for example, in the National Tax Service, the big data construction unit 120 or when the National Police Agency delivers the stolen vehicle information to the big data construction unit 120, the big data construction unit 120 receives the delinquent vehicle information or the stolen vehicle information and stores it in the database, and at the same time AI vision It is transmitted to the recognition unit 110, and accordingly, the AI vision recognition unit 110 receives the information of the delinquent vehicle or the stolen vehicle information, and based on this, recognizes the target through AI vision recognition and builds big data The unit 120 is notified, and accordingly, the big data construction unit 120 confirms the target recognition notification and transmits a request for location and image to the AI vision recognition unit 110, and AI vision recognition The unit 110 receives the request and notifies the location and image of the target (ie, delinquent or stolen vehicle information) to the big data construction unit 120, and accordingly, the big data construction unit 120 After receiving the location and image (i.e., delinquent vehicle information) and verifying the received recognition information (recognition information verification through synthesis and analysis of multiple information), it is stored in the database and at the same time, the big data utilization unit ( 130), and thus, vehicle information (including location and image information) to be reported by the big data utilization unit 130 can be generated and transmitted to the National Tax Service or the National Police Agency.

Big data construction and utilization system 100 for road conditions using a black box in a vehicle or a separately mounted camera having the configuration described above, in the case of theft, crime, and vehicle number of arrears, the big data construction unit 120 to the AI vision recognition unit 110 periodically, and when the AI vision recognition unit 110 recognizes the vehicle number in the input image and the recognized vehicle number matches the received vehicle number, that Information may be transmitted to the big data building unit 120.

The big data construction and utilization system 100 for road conditions using a black box in a vehicle or a separately mounted camera having the configuration described above is, for example, through AI vision recognition in the AI vision recognition unit 110. It recognizes road conditions such as accidents, congestion, and road damage and notifies them to the big data construction unit 120, and accordingly, the big data construction unit 120 checks the road situation recognition notification and requests for location and video. is transmitted to the AI vision recognition unit 110, and then the AI vision recognition unit 110 receives the request and informs the big data construction unit 120 of the location and image of the target, and accordingly, the big data After receiving the location and image of the target from the construction unit 120 and verifying the received recognition information (recognition information verification through synthesis and analysis of multiple information), store it in the database and use big data at the same time It is transmitted to the unit 130, and thus, the road condition information (including location and image information) to be reported by the big data utilization unit 130 can be generated and transmitted to the road construction, and also vehicles around the location As driving information for informing, it may be generated as warning or caution driving information and transmitted to a device (eg, navigation) (or AI vision recognition unit 110) provided in vehicles around the corresponding location.

The big data construction and utilization system 100 for road conditions using a black box in a vehicle or a separately mounted camera having the configuration described above is a built-in black box installed in a vehicle driving on national roads. By acquiring and accumulating many types of data on the road while driving using a camera or a separately installed camera, analyzing the accumulated data and converting it into big data for various uses, crime, theft or delinquent vehicle tracking, breakdown or accident It can be used in a variety of ways, such as vehicle identification, traffic accident, road kill or road damage confirmation, towing or maintenance service connection, accident or alternative route provision, etc. Also, benefits are provided to providers who provide data acquired through vehicle black boxes. and transmits data using a built-in vehicle communication module or a wireless terminal connection through a local area network, thereby providing convenience in collecting data.

5 is a diagram illustrating a method of constructing and utilizing big data on road conditions using a black box in a vehicle or a separately mounted camera according to an embodiment of the present invention, and FIGS. 6 and 7 are for an embodiment of the present invention. 8 and 9 are views illustrating a method of constructing and utilizing big data on road conditions using a black box or a separately mounted camera in a vehicle according to an example of information sharing with public institutions, and FIGS. It is a diagram explaining how to build and utilize big data on road conditions using a black box or a separately installed camera as an example of caution/caution driving information.

5 to 9, the AI vision recognition unit 110 uses a built-in camera of a black box built into a vehicle or a separately installed camera to drive on road conditions (ie, road or vehicle conditions, road surrounding conditions, etc.) (including all), classify and collect road situation images through AI vision recognition, and include the classified and collected road situation images (eg, service classification, location information, images related to services among input images, etc.) ) is delivered to the big data building unit 120 (S501).

In transmitting the road condition image in step S501 described above, in the big data construction unit 120, the road condition image acquired using the built-in camera of the vehicle black box or a separately installed camera is used to provide a certain road management service (i.e., service type) (e.g., crime, stolen or delinquent vehicle tracking service, breakdown or accident vehicle checking service, traffic accident, road kill or road damage checking service, towing or maintenance service linkage service, accident or alternative route provision service, etc.) In order to confirm whether it is a corresponding image, classification image information corresponding to the service type and service code corresponding to the service type may be set and registered, and the AI vision recognition unit 110 ) can be transmitted. Accordingly, in the AI vision recognition unit 110, the classification image information transmitted from the big data construction unit 120 may be stored in the internal memory for each type of road management service and service code corresponding to the type of service.

In transmitting the road condition image in step S501 described above, in the AI vision recognition unit 110, the road obtained using the built-in camera of the vehicle black box or a separately mounted camera based on the classification image information stored in the internal memory It is possible to check which road management service (i.e., service type) the situation image corresponds to, and collect road situation images acquired using the built-in camera of the vehicle black box or a separately installed camera by service type. can do.

In transmitting the road situation image in the above-described step S501, the AI vision recognition unit 110 can check the service type of the road situation image obtained using the built-in camera of the vehicle black box or a separately installed camera. A service code corresponding to the confirmed service type may be included in the classified and collected road condition image and transmitted to the big data construction unit 120 .

In transmitting the road situation image in the above-described step S501, when the vehicle black box has a free communication module for short-distance communication, the AI vision recognition unit 110 recognizes the AI vision for the situation around the road while driving. and recognizing an accident state on the road. In this case, a short-range communication connection is performed with a mobile terminal of the vehicle driver or a communication module built into the vehicle using the corresponding free communication module, and the mobile terminal or built-in communication in the vehicle is performed. Through the module, the classified and collected road condition image may be transmitted to the big data construction unit 120 .

In transmitting the road condition image in the above-described step S501, when a free communication module for short-range communication is provided, the AI vision recognition unit 110 connects to a free communication network such as wifi by using the free communication module. By doing so, the classified and collected road condition image may be transmitted to the big data construction unit 120 through the corresponding free communication network.

In transmitting the road condition image in the above-described step S501, if it is provided in the vehicle black box and a paid communication module for long-distance communication is also provided, the AI vision recognition unit 110 builds big data through the corresponding paid communication module. By performing a remote communication connection with the unit 120, the classified and collected road condition image may be transmitted to the big data construction unit 120.

In delivering the road condition image in the above-described step S501, if it is provided in the vehicle black box and is provided in a separate road management server together with the big data construction unit 120, the AI vision recognition unit 110 for the vehicle A road condition image (which may include location information using a GPS module, etc.) obtained using a built-in camera of a black box or a separately installed camera may be transmitted using the above-described method or the like.

In delivering the road condition image in the above-described step S501, as shown in FIGS. 6 and 7, the National Tax Service delivers delinquent vehicle information to the big data construction unit 120, or the National Police Agency builds big data for stolen vehicle information. When delivered to the unit 120, the big data construction unit 120 receives the corresponding delinquent vehicle information or the corresponding stolen vehicle information, stores it in the database, and transmits it to the AI vision recognition unit 110. Accordingly, the AI vision recognition unit 110 receives the corresponding delinquent vehicle information or the corresponding stolen vehicle information, recognizes the target through AI vision recognition based on this, and notifies the big data construction unit 120. there is. Accordingly, the big data construction unit 120 may check the target recognition notification from the AI vision recognition unit 110 and transmit a request for a location and an image to the AI vision recognition unit 110 . Then, the AI vision recognition unit 110 will receive a request from the big data construction unit 120 and notify the big data construction unit 120 of the target's location and image (ie, delinquent or stolen vehicle information). can

In transmitting the road condition image in step S501 described above, as shown in FIGS. 8 and 9 , the AI vision recognition unit 110 recognizes road conditions such as accidents, congestion, and road damage through AI vision recognition. This can be notified to the big data construction unit 120. Accordingly, the big data construction unit 120 may check the road situation recognition notification from the AI vision recognition unit 110 and transmit a request for a location and an image to the AI vision recognition unit 110. Then, the AI vision recognition unit 110 may receive a request from the big data construction unit 120 and notify the big data construction unit 120 of the location and image of the target.

When the road condition image is transmitted in the above-described step S501, the big data construction unit 120 transmits the road condition image (eg, service classification, location information, and input image) from the AI vision recognition unit 110. Including images related to the service, etc.), road condition data is extracted and accumulated to construct big data (S502).

In constructing the big data in step S502 described above, in the big data construction unit 120, in order to classify and extract the road condition data of many service types that can be obtained on the road while driving by service type, the service type and Standard extraction data to be extracted from the road condition image may be set and registered for each service code corresponding to the type of service.

In constructing the big data in step S502 described above, in the big data construction unit 120, the service code included in the road condition image transmitted from the AI vision recognition unit 110 can be checked, and the checked service code Corresponding standard extraction data can be checked, and based on the confirmed standard extraction data, road condition data corresponding to the identified service code can be extracted from the road condition image transmitted from the AI vision recognition unit 110, The extracted road condition data can be analyzed, turned into big data, and stored to build AI vision recognition driving big data.

In constructing the big data in step S502 described above, the big data construction unit 120 improves recognition accuracy through data learning; By continuously learning the road situation image transmitted from the AI vision recognition unit 110 and the road situation data extracted from the road situation image transmitted from the AI vision recognition unit 110, each service type and service code corresponding to the service type Corresponding classification image information, service type, and standard extraction data to be extracted from road condition images can be upgraded and registered in response to each service code corresponding to the service type. reliability can be improved.

In constructing the big data in step S502 described above, in the case of a crime, theft or delinquent vehicle tracking service, in the big data construction unit 120, the road situation data from the road situation image transmitted from the AI vision recognition unit 110 You can extract vehicle color, vehicle type, license plate number, etc.

In constructing the big data in the above-described step S502, in the case of a breakdown or accident vehicle confirmation service, the big data construction unit 120 converts the road situation data from the road situation image transmitted from the AI vision recognition unit 110 to the vehicle It can extract information such as bonnet opening, vehicle emergency lights on, smoke, flames, and falling objects.

In constructing big data in the above-described step S502, in the case of a traffic accident, road kill or road damage confirmation service, in the big data construction unit 120, the road condition image transmitted from the AI vision recognition unit 110 is a road. As situational data, information such as vehicle collisions, dead animals, and road damages can be extracted.

In building the big data in step S502 described above, the big data construction unit 120 manages large-capacity information according to a solution for classifying and managing the road situation data extracted from the road situation image transmitted from the AI vision recognition unit 110. It is possible to perform cloud management for, application load balancing using high-capacity traffic distribution technology, removal of redundant information on road condition data, filtering of misrecognized information, etc. It is possible to perform the valid information determination algorithm of.

In constructing the big data in step S502 described above, as shown in FIGS. 6 and 7, in the big data construction unit 120, the location and image of the target notified from the AI vision recognition unit 110 (ie, delinquent vehicle information), verify the received recognition information (recognition information verification through synthesis and analysis of multiple information), store it in the database, and inform the big data utilization unit 130 at the same time. there is.

In constructing the big data in step S502 described above, as shown in FIGS. 8 and 9 , the big data construction unit 120 receives the location and image of the target from the AI vision recognition unit 110 and transmits the corresponding data. After verification of the received recognition information (recognition information verification through synthesis and analysis of multiple information) is performed, the big data utilization unit 130 may be notified while storing the information in the database.

After constructing the big data in step S502 described above, the big data utilization unit 130 reads the big data constructed in the big data establishment unit 120 and provides a corresponding service for each type of service (e.g., crime, Stolen or delinquent vehicle tracking service, breakdown or accident vehicle confirmation service, traffic accident, road kill or road damage confirmation service, towing or maintenance service connection service, accident or alternative route provision service, etc.) are provided (S503).

In providing the road management service in the above-described step S503, in the big data utilization unit 130, the big data built in the big data construction unit 120 is classified according to the type of road management service and the service code corresponding to the service type. In order to process it appropriately and provide it as a road management service, big data can be processed into road management data corresponding to each service type and service code corresponding to the service type, and a provision data form to be provided can be set and registered, In addition, for each type of service and service code corresponding to the type of service, interlocking information for linking with related organizations or related parties (eg, police, National Tax Service, Korea Expressway Corporation, towing companies, maintenance companies, navigation providers, etc.) You can set up and register.

In providing the road management service in the above-described step S503, the big data utilization unit 130 can check the type of road management service and the provided data form corresponding to each service code corresponding to the type of service. Based on the provided data form, the big data read from the big data construction unit 120 may be processed into road management data corresponding to each service type and service code corresponding to the service type, and provided.

In providing the road management service in the above-described step S503, the big data utilization unit 130 interworks with related institutions or related parties by using interlocking information corresponding to each service type and service code corresponding to the service type, and The processed road management data can be provided to the relevant related organizations or related parties.

In providing the road management service in step S503 described above, the big data utilization unit 130 uses the big data built in the big data construction unit 120 to analyze vehicle accident-prone areas and determine seasonal and regional road conditions. It can be analyzed and provided to related organizations (eg, Korea Expressway Corporation, etc.).

In providing the road management service in the above-described step S503, the big data utilization unit 130 receives information on crime, theft or delinquent vehicles from the police or the National Tax Service, and recognizes license plates in the AI vision recognition unit 110. Crime, theft or delinquent vehicle detection through AI vision situation detection through accident situation recognition, crime, theft or arrears vehicle tracking service using the big data built in the big data construction unit 120 Provided to the police or the National Tax Service By giving, it is possible to share real-time information and transmit it as intelligent data so that real-time movement route identification can be facilitated.

In providing the road management service in step S503 described above, in the big data utilization unit 130, traffic accident recognition such as construction and driving obstruction recognition in the AI vision recognition unit 110 and traffic accident situations By using the big data built by the big data construction unit 120 by providing a navigation or alternative route providing service to a navigation provider or Korea Expressway Corporation, intelligent safe driving information, accident information, alternative route information, etc. are easily provided can provide

In providing the road management service in step S503 described above, in the big data utilization unit 130, the shared vehicle quality Points that can provide benefits such as warranty, accident prevention service quality improvement, vehicle purchase benefit, insurance premium discount, etc. can be given in preparation for video provision and utilization. For example, 1 point for each number of road condition images provided to the big data construction unit 120 and 2 points for each number of actually utilized by the big data utilization unit 130 may be provided.

In providing the road management service in the above-described step S503, the big data utilization unit 130 analyzes the requested information of the demand company or institution, processes it into corresponding information, and manages the communication interface between heterogeneous servers. Control and notification operation algorithms can be performed.

In providing the road management service in the above-described step S503, as shown in FIGS. 6 and 7, the big data utilization unit 130 receives a notification from the big data construction unit 120 and reports it. Vehicle information (including location and image information) may be generated and transmitted to the National Tax Service or the National Police Agency.

In providing the road management service in the above-described step S503, as shown in FIGS. 8 and 9, the big data utilization unit 130 receives a notification from the big data construction unit 120 and reports it. Road condition information (including location and image information) can be generated and transmitted to the road construction, and as driving information to inform surrounding vehicles of the location, it is generated as warning or caution driving information to nearby vehicles at the location. It may be transmitted to a device (eg, navigation) (or AI vision recognition unit 110) provided in the.

As described above, the embodiments of the present invention are not implemented only through the above-described device and/or operating method, but through a program for realizing functions corresponding to the configuration of the embodiment of the present invention and a recording medium on which the program is recorded. It may be implemented, and such an implementation can be easily implemented by an expert in the technical field to which the present invention belongs based on the description of the above-described embodiment. Although the embodiments of the present invention have been described in detail above, the scope of the present invention is not limited thereto, and various modifications and improvements of those skilled in the art using the basic concept of the present invention defined in the following claims are also included in the scope of the present invention. that fall within the scope of the right.

100: Big data construction and utilization system for road conditions using a black box or a separately mounted camera in the vehicle
110: AI vision recognition unit
120: Big data construction unit
130: big data utilization unit

Claims (5)

An AI vision recognition unit for classifying and collecting road situation images through AI vision recognition for road conditions while driving using a built-in camera of a black box built into the vehicle or a separately mounted camera;
A big data construction unit for constructing big data by extracting and accumulating road situation data from road situation images classified and collected by the AI vision recognition unit; and
Building big data on road conditions using a black box in the vehicle or a separately installed camera including a big data utilization unit to read the big data built in the big data construction unit and provide corresponding services for each service type, and utilization system.
The method of claim 1, wherein the AI vision recognition unit,
A system for constructing and utilizing big data for road conditions using a black box in a vehicle or a separately mounted camera, characterized by recognizing road conditions, vehicle conditions, and road surrounding conditions as road conditions while driving.
The method of claim 1, wherein the AI vision recognition unit,
For road conditions using a black box in a vehicle or a separately mounted camera, characterized in that the location information using the GPS module is included in the road situation image acquired using the built-in camera of the vehicle black box or a separately mounted camera Big data construction and utilization system.
The method of claim 1, wherein the AI vision recognition unit,
The classification image information transmitted from the big data construction unit is stored in the internal memory for each type of road management service and service code corresponding to the type of service. A system for building and utilizing big data.
AI vision recognition unit classifying and collecting road situation images through AI vision recognition for road conditions while driving using a built-in camera of a black box built into a vehicle or a separately mounted camera;
Building big data by extracting and accumulating road situation data from the road situation images classified and collected by the AI vision recognition unit by the big data construction unit; and
Building big data on road conditions using a black box in the vehicle or a separately installed camera, including the step of reading the big data built by the big data building unit by the big data utilization unit and providing corresponding services for each service type and how to use it.