KR102308466B1 - System for providing drone comprehensive service based on artificial intelligence and bigtata - Google Patents

Abstract

The present invention provides a system for providing a comprehensive drone service based on artificial intelligence and big data which can use all of at least one type of service associated with a drone on a single platform without knowledge on a drone. The system for providing a comprehensive drone service based on artificial intelligence and big data comprises: a user terminal requesting at least one type of service associated with a drone, selecting a service provider which has submitted one estimate among estimates of a reverse auction method for the requested service when the estimates are received to complete matching, and transmitting comments for receiving service as feedback when a deposit for service use is completed; at least one service provider terminal uploading at least one type of service associated with a drone, inputting an estimate for the requested service to transmit the estimate to the user terminal, and receiving money for expenses for provided service after providing service if selected from the user terminal; and a comprehensive service providing server including a storage unit receiving an upload for at least one type of service from at least one service provider terminal to map the service with the at least one service provider terminal to store the service, a request unit extracting at least one service provider terminal providing requested service to request an estimate if at least one type of service is requested from the user terminal, a transmission unit transmitting an estimate to the user terminal if the estimate is received from the at least one service provider terminal, a matching unit completing matching if a service provider which has submitted one estimate is selected from the user terminal, and a feedback management unit receiving comments for receiving service as feedback to upload the comments when a deposit is completed from the user terminal.

Description

A system for providing comprehensive drone services based on AIA and big data {SYSTEM FOR PROVIDING DRONE COMPREHENSIVE SERVICE BASED ON ARTIFICIAL INTELLIGENCE AND BIGTATA}

The present invention relates to a drone comprehensive service providing system based on AI and big data, and provides a platform that provides at least one type of service related to drones in an integrated manner.

A drone is an unmanned aerial vehicle that can fly and control by induction of wireless electromagnetic waves, and can also incorporate artificial intelligence technology. Drones were initially used for military reconnaissance purposes, but are increasingly being used as offensive weapons to destroy enemies by equipping drones with various weapons. Recently, these drones are being used for commercial purposes as flying vehicles with various types and performances depending on the purpose of use. As we enter the era of the 4th industrial revolution, the drone industry is emerging as one of the core industries of the future. Observation, public transport, daily life, leisure, etc. In addition to filming for broadcast movies, disaster safety, infrastructure inspections such as bridges, pylons, and construction sites, cadastral surveys, shoreline surveys, 3D mapping, and spatial information acquisition. The scope of use of drones is expanding.

At this time, methods for providing various services using drones have been researched and developed. October 24, 2018), when the drone rental management application is activated through the user terminal, the location information of the user terminal is collected, information about the drone station located near the user terminal is provided, and the drone station selection When information is input, information on available drones is provided, and when reservation input information is input, reservation confirmation information for the input drone is provided, authentication is performed on the user who requested drone service provision, and drone service is performed. Check the type of mission related to the request for provision, the location to perform the mission, and the drone to perform the mission, start the target drone to perform the mission, provision the information required for the mission to the target drone, and set the target drone on a mission Each configuration is disclosed for collecting information acquired while a target drone performs a mission after being dispatched to a destination.

However, since most people who want to use a drone without purchasing a drone are ordinary people, not experts, even if they rent it, they do not know how to control it and are not familiar with it, so they cannot control and steer it for the purpose. In addition, in order to use a drone, permission and authorization from a licensing authority are required, and it is impossible to properly prepare the necessary documents. Therefore, there is no platform that provides one-stop solutions for related services even though customers cannot use the drone properly even if they simply rent a drone. Also, if the rental is done without looking at or considering the weather, such as in the weather, the wind speed is strong and the rental drone crashes frequently. Accordingly, research and development of a platform that comprehensively provides drone-related services is required.

An embodiment of the present invention matches and connects a service provider that provides at least one type of service related to drones and a user who is a customer who wants to use the drone, but by allowing the provider to offer a price in a reverse auction method, the customer As the choice expands, quick decision-making can be reached, and service providers can start a business at any time and provide related services as long as they have the technology to provide drones and drones. As long as there is a terminal, you can have an opportunity to expand the source of income and support drone-related information or licensing on one platform. It can provide a method of providing a comprehensive service for drones based on AI and big data that can be used by all. 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-described technical problem, an embodiment of the present invention requests at least one type of service related to a drone, and when a reverse auction method estimate for the requested service is received, among the received quotations Upload at least one type of service related to a user terminal and drone that selects a service provider that submitted any one quotation, completes matching, and sends a review of service provision as feedback after completing payment for service use and inputting a quote for the requested service and transmitting it to the user terminal, and when selected from the user terminal, from at least one service provider terminal and at least one service provider terminal receiving a payment for the provided service after providing the service A storage unit for receiving at least one type of service, mapping it with at least one service provider terminal and storing it, and at least one service provider terminal providing the requested service when at least one type of service is requested from the user terminal A request unit that extracts and requests an estimate, a transmitter that transmits to the user terminal when a quotation is received from at least one service provider terminal, and a matching unit that completes matching when a service provider who submitted any one quotation from the user terminal is selected , and a comprehensive service providing server including a feedback management unit for receiving and uploading a review after receiving the service as feedback when the deposit is completed from the user terminal.

According to any one of the above-described problem solving means of the present invention, a service provider that provides at least one kind of service related to a drone and a user who is a customer who wants to use it are matched and connected, and the price is provided by a reverse auction method. By allowing the service provider to present it, customers can reach a quick decision-making process while having a wider range of options, and service providers can start a business at any time and provide related services as long as they have the technology to provide drones and drones. If you have a smart terminal, you can have an opportunity to expand the source of income, and because one platform can support drone-related information or licensing, at least one type of drone related to drones without knowledge of drones. services are all available on one platform.

1 is a diagram for explaining an AI and big data-based drone comprehensive service providing system according to an embodiment of the present invention.
FIG. 2 is a block diagram illustrating a comprehensive service providing server included in the system of FIG. 1 .
3 and 4 are diagrams for explaining an embodiment in which the AI and big data-based drone comprehensive service according to an embodiment of the present invention is implemented.
5 is an operation flowchart illustrating a method of providing a comprehensive service for a drone based on AI and big data 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 many 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. . Also, when a part "includes" a 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 a sense at or close to the numerical value when the manufacturing and material tolerances inherent in the stated meaning are presented, and serve to enhance the understanding of the present invention. To help, precise or absolute figures are used to prevent unfair use by unscrupulous infringers of the stated disclosure. As used throughout the specification of the present invention, the term “step for (to)” or “step for” 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 may be configured to reproduce one or more processors. Thus, as an example, '~' refers to 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.

In this specification, some of the operations or functions described as being performed by the terminal, apparatus, or device may be performed instead of in 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 an AI and big data-based drone comprehensive service providing system according to an embodiment of the present invention. Referring to FIG. 1 , the AI and big data-based drone comprehensive service providing system 1 may include at least one user terminal 100 , a comprehensive service providing server 300 , and at least one service provider terminal 400 . can However, since the AI and big data-based drone comprehensive service providing system 1 of FIG. 1 is only an embodiment of the present invention, the present invention is not limitedly interpreted through FIG. 1 .

In this case, each component of FIG. 1 is generally connected through a network 200 . For example, as shown in FIG. 1 , at least one user terminal 100 may be connected to the comprehensive service providing server 300 through the network 200 . In addition, the comprehensive service providing server 300 may be connected to at least one user terminal 100 and at least one service provider terminal 400 through the network 200 . Also, the at least one service provider terminal 400 may be connected to the comprehensive 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 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.

The at least one user terminal 100 may be a terminal of a service consumer who wants to use at least one kind of service related to a drone using a web page, an app page, a program or an application related to an AI and big data-based drone comprehensive service. have. In addition, the at least one user terminal 100 may be a terminal that can receive services such as shopping, matching for service use, weather information, licensing, navigation, etc. through the comprehensive service providing server 300 , The types of services available are not limited to those listed and are not excluded for reasons not listed.

Here, the at least one user terminal 100 may be implemented as a computer that can access 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 user terminal 100 may be implemented as a terminal capable of accessing a remote server or terminal through a network. At least one user terminal 100, 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) ) terminal, a smart phone, a smart pad, a tablet PC, etc. may include all kinds of handheld-based wireless communication devices.

The comprehensive service providing server 300 may be a server that provides an AI and big data-based drone comprehensive service web page, an app page, a program, or an application. In addition, the comprehensive service providing server 300 may be a server that collects information on at least one type of service that can be provided from the at least one service provider terminal 400 and generates a manpower pool. In addition, when the user terminal 100 searches for at least one type of service related to the drone, the comprehensive service providing server 300 searches for at least one service provider terminal 400 that has uploaded information corresponding thereto, and estimates may be a server that transmits to the at least one service provider terminal 400 . And, the comprehensive service providing server 300, when paying by selecting any one of the quotations collected by the reverse auction method in the user terminal 100, between the user terminal 100 and the at least one service provider terminal (400) After the matching is completed, the remaining amount excluding the fee may be transmitted to the service provider terminal 400 , and from the user terminal 100 , it may be a server that receives and uploads a review or rating on a service provided with the service provider. In addition, the comprehensive service providing server 300 operates a shopping mall that sells drones and remote controllers, manages usage history, manages live chat, provides weather and flight information, manages certification agencies, and AI chatbot And it may be a server that operates a real-time consultation based on big data and provides a comprehensive service that crawls and provides news about drones. In this case, for other comprehensive services, both users and service providers may be users.

Here, the comprehensive 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 service provider terminal 400 may be a terminal of a service provider that provides at least one service related to a drone using an AI and big data-based drone comprehensive service related web page, an app page, a program, or an application. In this case, the provided service is defined as including all kinds of services related to drones, such as shooting, control, advertisement, performance, rental, repair or delivery. In this case, in addition to delivery, a transport business and a delivery business may be included, and a transport business is also possible. Drone delivery and drone delivery are also possible, but not limited to those listed. At this time, the at least one service provider terminal 400 may be a terminal that uploads the type and detailed information of the service to be provided to the comprehensive service providing server 300 and inputs an estimate when a request for quotation is received, In this case, after providing the service to the user, it may be a terminal that receives a payment from the comprehensive service providing server 300 . In addition, the service provider terminal 400 may be a terminal of a user using at least one service provided by the comprehensive service providing server 300 , wherein the service available to the user is provided by the comprehensive service providing server 300 . other services. In addition, the service provider terminal 400 can proceed with the same process as the user terminal 100 , but for convenience of description, the description is limited to a role of providing a service.

Here, the at least one service provider terminal 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 service provider terminal 400 may be implemented as a terminal capable of accessing a remote server or terminal through a network. The at least one service provider terminal 400 is, for example, a wireless communication device that guarantees portability and mobility, such as navigation, Personal Communication System (PCS), Global System for Mobile communications (GSM), and Personal Digital Cellular (PDC). , 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, etc. may include all types of handheld-based wireless communication devices.

2 is a block diagram for explaining a comprehensive service providing server included in the system of FIG. 1, and FIGS. 3 and 4 are an embodiment in which AI and big data-based drone comprehensive service according to an embodiment of the present invention is implemented. It is a figure for demonstrating an example.

Referring to FIG. 2 , the comprehensive service providing server 300 includes a storage unit 310 , a request unit 311 , a transmission unit 313 , a matching unit 315 , a feedback management unit 317 , and a shopping mall management unit 320 . , usage history management unit 330, live talk management unit 340, weather and flight information providing unit 350, certification authority management unit 360, real-time consultation service unit 370, drone news service unit 380 and permission management unit (390).

The comprehensive service providing server 300 according to an embodiment of the present invention or another server (not shown) operating in conjunction with at least one user terminal 100 and at least one service provider terminal 400 uses AI and big data When transmitting a drone-based comprehensive service application, program, app page, web page, etc., at least one user terminal 100 and at least one service provider terminal 400, AI and big data-based drone comprehensive service application, program , can install or open app pages, web pages, and more. In addition, a service program may be driven in at least one user terminal 100 and at least one service provider terminal 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 storage unit 310 may receive at least one type of service uploaded from at least one service provider terminal 400 , map it to at least one service provider terminal 400 , and store it. In this case, the at least one service provider terminal 400 may upload at least one type of service related to the drone. At this time, at least one kind of service related to the drone may be a service including shooting, control, performance, rental, repair and delivery, but is not limited to the listed ones and is not excluded for reasons not listed.

When at least one type of service is requested from the user terminal 100 , the requesting unit 311 may extract at least one service provider terminal 400 providing the requested service and request an estimate. The user terminal 100 may request at least one type of service related to the drone. In this case, the user terminal 100 may request a service after inputting the location of the user terminal 100 , a device to be used, time, date, range, and the like. Accordingly, the requesting unit 311 extracts the service provider terminal 400 that provides at least one service that satisfies the conditions input by the user terminal 100 and sends a quotation, that is, the user sets the price in a reverse auction method. You can ask for a quote so we can set it up. Accordingly, the at least one service provider terminal 400 inputs a quote for the requested service and transmits it to the requesting unit 311 , and the requesting unit 311 transmits it to the user terminal 100 so that it can be selected. .

When there is no condition selection of the user terminal 100 , the request unit 311 may select and propose a keyword. Here, the requester 311 may use a Query Log-Based keyword suggestion, a Proximity-Based keyword suggestion, or a Meta Tag Crawlers-Based suggestion method. First of all, based on the search word log, log analysis refers to a service that extracts and analyzes various information such as the visit route accessed by Internet users, the access time period, and the number of connections. The keyword suggestion method based on the search word log is based on the analysis of keywords related or occurring simultaneously in the search word log of the search engine. For example, “Drone for shooting” is generally identified along with the keyword “Drone” in the search query log, which is a result suggested at the same time due to the high correlation between the keyword “Drone for shooting” and the keyword “Drone”. The keyword suggestion method based on the search query log is useful because it can identify the intention of the user in a timely manner, but since only a limited number of popular keywords are likely to be suggested to advertisers, in order to infer the similarity relationship between related keywords, the By applying a data mining technique, synonyms between keywords can be inferred and suggested to advertisers.

Second, the proximity-based method is a method of recommending a keyword from a search result with high similarity according to a search result for a keyword input by a user in a search engine. In this case, after understanding the basic meanings between words in advance, new keywords may be suggested based on relevance to the keywords, and similarity analysis between seed keywords and keywords is performed on the advertiser's website to recommend keywords with high relevance model can be provided. In addition, a large set of candidate keywords may be generated by using the search result of the seed keyword, and terms with low relevance may be further filtered and removed from the candidate keyword set.

The keyword suggestion method based on the meta tag crawler is a method of deriving keywords from the contents of the upper web page presented as a result of the seed keyword search. Here, the meta tag means the <meta> tag part added to the <head> section of the HTML page. After submitting website information to a search service such as a search engine based on keywords such as meta tags on major websites, after a certain period of time has elapsed, the data of visitors collected by the web metric tool is searched and analyzed, It may also be used to attract associated customers. Of course, there is no need to suggest keywords, and the above-described configuration may be replaced with another configuration.

The transmitter 313 may transmit to the user terminal 100 when a quote is received from the at least one service provider terminal 400 . In this case, when a reverse auction-type quotation for the requested service is received, the user terminal 100 may select a service provider that submitted any one of the received quotations to complete matching. For example, assuming that the user has presented conditions A, B, C, D, a list of service providers that satisfy conditions A, B, C, D is extracted, and the extracted service providers make price estimates in a reverse auction method. After transmitting to the user, the user receives a quote and selects a person (service provider) who presents the desired conditions such as price order.

The matching unit 315 may complete matching when a service provider that has submitted any one quotation is selected from the user terminal 100 . The user terminal 100 may select a service provider that satisfies a desired condition. For example, assuming that the user desires conditions A, B, C, and D, a person who presents the desired condition among service providers satisfying the conditions A, B, C, and D may be extracted. Alternatively, because the conditions A, B, C, and D are quantitatively satisfied but qualitatively different skills and services of different quality are provided, the user does not unconditionally choose the condition because the price is low, but the user wants the condition can be selected when appropriate. For example, a user may want to receive a service within 3 days, but may not select a service provider that satisfies all conditions A, B, C, and D if the schedule is not within 3 days.

When the deposit from the user terminal 100 is completed, the feedback management unit 317 may receive and upload a review of receiving the service as feedback. Accordingly, prospective customers can see the service provider's reviews and assess the level of the service and receive help in decision-making. The user terminal 100 may transmit a review of receiving the service as a feedback after completing the deposit for the service use, and at least one service provider terminal 400 provides the service when selected from the user terminal 100 . After providing the service, you can receive payment for the provided service.

The shopping mall management unit 320 may sell at least one type of product related to a drone including a drone, at least one part of the drone, a controller, insurance, and a book, and manage shopping carts, points, and coupons. In this case, not only drone parts, but also financial products, related products, and derivatives may be sold in the shopping mall. In this case, the shopping mall management unit 320 may perform target marketing after analyzing the purchase history and the target customer base, and may analyze which advertisement to be provided using the association rule algorithm. The association rule algorithm is one of the data mining analysis techniques, and it is an algorithm that reveals the correlation that, for example, a customer who bought product A is more likely to buy product B. In other words, it is to find the correlation rule between product A and product B. In this case, the association analysis can be used to find the correlation of each item based on evaluation criteria such as support, reliability, and improvement. The support of the association rule evaluation refers to the ratio of purchasing A, B, and C together among all customers, and is defined as IF A & B THEN C = P(A∩B∩C). Confidence refers to the proportion of customers who purchased C among customers who purchased A and B, and is defined as IF A & B THEN C = P(A∩B∩C)/P(A∩B) . Lift is the value obtained by dividing the ratio of customers who purchased C among customers who purchased A and B by the ratio of customers who purchased C among all customers. IF A & B THEN C = P(C|A∩ It is defined as B)/P(C). Using this, the shopping mall operation unit 320, when the execution unit 330, which will be described later, executes an advertisement, selects a target customer group or selects an advertisement to be provided to an arbitrary customer, a person who purchases the item A The probability of purchasing the product B can be estimated through the reliability of the association rule, and the effectiveness of advertisements can be increased by listing and providing items and industries/items whose indexes such as reliability exceed a preset percentage.

The usage history management unit 330 may provide a usage history using at least one type of service related to the drone in the user terminal 100 , and share, post, and transmit at least one data of the user terminal 100 . In this case, the usage history may be the contents of the service provided by the user, or may be the navigation result of the user renting a drone from the service provider and flying. In this case, the usage history management unit 330 may perform analysis using the clickstream data of the user terminal 100 . In general, an online activity expressed as web surfing refers to an activity of an Internet user visiting a website for activities such as information search and online purchase. The online behavior information of Internet users can be checked more objectively and accurately by using the clickstream data that records the route the user visited one or more websites, and the clickstream data includes information that cannot be obtained from a survey. has a

In other words, the clickstream data records a series of online activities such as which sites an Internet user visits, and how often a specific website is visited. In addition, clickstream data is obtained in the form of web log data from the server log of the company operating the website, or panel data from an institution that collects visit information of panels by installing software on the user's computer. It is obtained in the form of (Panel Data). Clickstream data in the form of weblog data includes information on the online activity record of Internet users such as the webpage address visited, access date and time, and the number of sessions. information on demographic characteristics of The clickstream data can be used to trace the movement path between various websites for Internet users to understand the movement path relationship or to model the movement route and predict whether the user will purchase the next visit.

A method of analyzing based on the above-described collected data and clickstream data will be described below. First, a support vector machine (SVM) may be used. SVM is a method that can classify data irrespective of linear or non-linear, and aims to find the optimal separation boundary (Hyperplane) as a criterion for classifying target values. SVM is generally used as a binary classification algorithm, but multinominal classification is also possible using a multi-class SVM (Multi-Class Support Vector Machine). The second is a neural network. A neural network is an algorithm inspired by a biological neural network, a high-performance classification method for models, and each neuron is connected to each other in a multi-layer perceptron structure. The third is logistic regression. This is binomial logistic regression and is a statistical technique used to classify a binary dependent variable, but it is also possible to classify a polynomial dependent variable with three or more categories using multinomial logistic regression. . The fourth is a decision tree, which may include segmentation, classification, prediction, dimensional reduction and variable selection. In particular, the dimensionality reduction and variable selection method is a method of selecting explanatory variables that have a relatively large influence on the prediction of the dependent variable by extracting the importance of the predictor variable from the decision tree to improve the performance of the predictive model when the number of explanatory variables is very large.

In addition, Principal Component Analysis, which converts variables into principal components through linear combination of highly correlated variables, as a representative dimensionality reduction method for reducing a high-dimensional data set to a lower dimension, measures the similarity of each object and Cluster analysis in which high objects form a group may be used, but it is not limited to the listed ones and is not excluded for reasons not listed.

The live talk management unit 340 performs information sharing using at least one of real-time postings, comments, and chatting in the user terminal 100 and at least one service provider terminal 400, and You can upload attachments. At this time, since the opinions and thoughts of many people are expressed in the comments, it is possible to try text mining and sentiment word prediction, and to analyze the comments with RNN to investigate public opinion on service providers or objects that become topics. For example, if a review or evaluation of Drone A is made in real-time comments or chats, the analysis result is mapped with Drone A and stored, so that it can be described in detail when selling or renting Drone A.

To this end, the live talk management unit 340 according to an embodiment of the present invention may further perform a method of analyzing the tendency of comments by performing morpheme analysis and constructing an emotion dictionary. In this case, morpheme analysis is used to analyze comments composed of Korean sentences, and morpheme analysis refers to dividing and decomposing entire sentences into morphemes, and analyzing only real morphemes that have meaning among the separated morphemes. If the sentence "to fly" exists, "flight" and "ga-" are the subject of analysis because they have meanings, but "-e" and "da" are not analyzed as they are not morphemes with meanings by themselves. . Accordingly, in the present invention, the tendency of the morpheme is analyzed according to the tendency of the sentence in which the morpheme is used. For morpheme analysis, a plurality of publicly available morpheme analyzers may be used, but one is not specified.

Disposition analysis analyzes the disposition towards the subject or topic of comments and is divided into positive, negative, and neutral. In this case, the tendency divided by hand may be applied to the training data, and the tendency of the experimental data may be analyzed through the morpheme included in the comment. On the other hand, the sentiment dictionary expresses the tendency of morphemes numerically. After analyzing the propensity for comment sentences, morphemes included in each sentence are separated through morpheme analysis. The propensity of each morpheme is calculated through the frequency in which the separated morphemes are used in sentences with positive, negative, and neutral propensities, and the calculated propensity index can be used as a variable of SVM through the transformation process in the sentence.

The comments, real-time chats, etc. collected by the live chat management unit 340 may be collected and used as experimental data. Data collection can be collected using a crawling method. Each comment data may include the number of comments, likes, and dislikes, and the tendency of the collected comments can be manually divided into positive, negative, and neutral for the article content. Next, the live talk management unit 340 needs to refine data and build a sentiment dictionary. In order to separate the collected comment data into morpheme units, the morpheme analyzer according to the above-described open technology may be used. The live talk management unit 340 may divide all sentences into morpheme units using a morpheme analyzer, and then calculate the frequency of appearance of each morpheme and the tendency of the sentences used. The propensity index of each morpheme can be calculated based on the frequency in which each morpheme is used in all comments and the propensity of the used comments.

The live talk management unit 340 may then calculate the emotional index using the sentiment dictionary. Using the sentiment dictionary built in the above process, the sentiment index of the experimental data sentence is calculated. After separating the experimental sentences into morphemes, the propensity index for each morpheme is found in the emotional dictionary and substituted. If a morpheme that does not exist in the emotional dictionary appears, the propensity index is assumed to be 0. At this time, the emotional index of the sentence is as shown in Equation 2 below. The emotional index of the calculated sentence and the tendency to be manually classified can be used as variables of the SVM.

In order to derive an experimental result, an experiment may be conducted using the SVM, but is not limited to the SVM. In order to apply the SVM, the results are derived by first classifying into three categories of positive/negative/neutral, and an experiment in which two classifications of negative and neutral are combined into one can be carried out in two categories of positive/negative. Of course, in addition to the above-described methods, various methods for determining whether comments, reviews, or real-time topics are negative or positive may be introduced, and the method is not limited thereto.

In addition, when classifying emotions, it is necessary to consider negative components that invert emotions in combination with emotional vocabulary. Negative sentences in Korean are divided into short negative sentences and long negative sentences according to the location of the negative element, and can be divided into ‘an’ negative sentence and ‘nail’ negative sentence according to the usage of the negative element. In short negative sentences, the negative is placed before the predicate like “I don’t like math.” In long negative sentences, like “I don’t like math.” negative is located And in this case, even though there is a root that expresses the affirmation of 'like/dislike', if you look at the whole sentence, it shows negative emotions. In this way, when negative negation and emotional vocabulary are formulas, emotional reversal occurs.

For example, in the combination of "don't/like", the sensibility of the emotional vocabulary is reversed when the emotional vocabulary is used as the dominant element. And the suffix "ji" connected to the negative emotion "fear" If ' is attached and the negative negative "do" is taken as the dominant element, the emotion is reversed from negative to positive. And if the verb has negative negative as the dominant element, the emotion of the emotional vocabulary is reversed. For example, 'stability' with positive emotions 'The verb 'find + ji' with the linking ending 'ji' is the dominant element, and this verb has the negative negation 'notha' as the dominant element (cannot find stability), and the emotion is reversed from positive to negative. Accordingly, it is also possible to classify the positive, negative, neutral, etc. of comments by considering negative components that invert emotions by combining with emotional vocabulary.

The weather and flight information providing unit 350 may provide real-time weather information and flight information. For example, in case of strong wind, rain or snow, the motor may be damaged by moisture, so it is not suitable for controlling drone flight. may reduce Of course, drones that fly through gusts of wind and heavy rain have also been developed, but this can be reported under the premise that most commercial drones are vulnerable to moisture and temperature. Basically, drones are greatly affected by the weather, so it checks the wind and rain or snow weather, and extracts the weather that most commercial drones can fly. can tell you

The weather and flight information providing unit 350 provides flight information, control area, map (map), and real-time global control information (controlled airspace, uncontrolled airspace, controlled airspace, caution airspace, etc.) to optimize service for drone flight. support and provide. It provides detailed information by linking and interworking with each region, maximizing the utility of the drone. For drone usability, it can provide area (map) information and recommended area service based on AI and big data, for example, it can be a good flying area, a popular flying area, a good photo area, etc. .

The certification authority management unit 360 processes company registration certified through the authentication of at least one institution that performs online training and offline training, and training for the user terminal 100 and the at least one service provider terminal 400 . You can manage at least one certification body that implements At this time, the education includes online and offline, provides materials and lectures, and includes education services related to drones such as certification, coding, and maintenance.

Here, when managing the certification authority, only the authorized authority can prove the integrity by creating and managing blocks in the block chain network. The certification authority management unit 360 may be configured as a private blockchain due to the nature of managing authentication, and since a small number of authorized people participate, it is a model with enhanced confidentiality, and the transaction speed can be increased only with trusted people. . At this time, the algorithm when generating and propagating blocks of the block chain can use a non-competition method due to the characteristics of the private block chain. For this, the PBFT consensus algorithm and the Ripple consensus algorithm can be used.

In the PBFT consensus algorithm, one elected leader node receives a transaction verified as valid using a verification node, propagates a consensus request to everyone, and obtains 2/3 votes to generate a block. The PBFT consensus algorithm developed the BFT algorithm of a distributed system that operates normally even if some abnormal nodes exist, so that it can be used in an asynchronous network. In addition, in PBFT, a leader or verification node can more accurately remove anomalous nodes with a higher probability through two broadcasting processes that propagate to the entire network and vote. The Ripple consensus algorithm is an asynchronous round-based protocol executed by a network verification server, and consists of a collection phase, a consensus phase, and a closing phase. In the collection stage, the verification server receives the transaction from the network, checks the validity of the signature and the correctness of related information, and broadcasts the proposal back to the network as a set of candidates. In the consensus stage, the servers agree on the proposals they have received by voting. In the closing stage, if the proposal gets more than 80% consent, the proposal is removed from the candidate set and formally registered in the ledger, and one round is closed. The Ripple consensus algorithm aims to be a real-time payment system and can process large amounts of payments quickly. Of course, it will go without saying that a method of verifying an educational institution can be used in various ways other than the above-described method.

The real-time consultation service unit 370 may provide a real-time consultation service to the user terminal 100 and at least one service provider terminal 400 based on an artificial intelligence (AI) chatbot and a big data platform. Here, of course, it will be said that it is not limited to real time. AI and big data have a complementary relationship with each other, and the real-time counseling service unit 370 collects raw data, and then includes unstructured data, structured data and semi-structured data included in the raw data. Semi-structured data may be refined, preprocessing including classification may be performed as meta data, and analysis including data mining may be performed on the preprocessed data. In addition, the real-time counseling service unit 370 may visualize and output the analyzed data.

At this time, data mining is a classification that predicts a class of new data by learning a training data set with a known class by exploring the inherent relationship between preprocessed data, or grouping data based on similarity without class information. clustering) can be performed. Of course, various other mining methods may exist, and mining may be performed differently depending on the type of big data to be collected and stored or the type of query to be requested later. The big data constructed in this way can be verified through artificial neural network deep learning or machine learning. Here, artificial neural network deep learning may be useful when analyzing image data.

At this time, the artificial neural network can use a convolutional neural network (CNN) structure, which is a network structure using a convolutional layer and is suitable for image processing. because it can In addition, text mining is a technology aimed at extracting and processing useful information from non-/semi-structured text data based on natural language processing technology. Through text mining technology, it is possible to extract meaningful information from a large collection of texts, identify the linkage with other information, find the category of text, or obtain results beyond simple information search. Using this, in the medical advisory service according to an embodiment of the present invention, large-capacity language resources and statistical and regular algorithms can be used to analyze an identifier or natural language input as a query and to discover hidden information therein. In addition, cluster analysis can be used to finally discover a group of similar characteristics while merging objects with similar characteristics. It enables classification through cluster analysis, identifies the characteristics of the cluster, and then asks for a new query. When is input, objects included in the new query can be classified.

Chatbot is a compound word of chat and robot, and refers to a conversational system that interacts with humans based on artificial intelligence. With the development of artificial intelligence technology, chatbots have become able to perform more complex tasks as machine learning or deep learning technology is applied to chatbots to understand the user's questions, understand their intent, and provide appropriate answers. In addition, due to the proliferation of smartphones and the rapid increase of mobile messenger users, most smartphone users are using messenger apps. If you use a messenger app to provide chatbot services, you can provide chatbot services to users in a familiar environment without installing a new app. became possible Accordingly, existing messenger companies are developing messenger platforms with artificial intelligence technology as well as releasing their respective messenger platform APIs to preoccupy the chatbot market.

Chatbots can be classified into rule-based chatbots and machine learning-based chatbots according to the operation method, one-time Q&A chatbots and continuous conversation chatbots according to the information exchange method, and search model chatbots and generative model chatbots according to the answer generation method. The rule-based chatbot operates based on predefined rules, and includes an interpretation rule for interpreting the user's input, a reaction rule for reacting to the user's input, or a rule for generating a response. Machine learning-based chatbots use machine learning algorithms to understand natural language and generate or select appropriate answers. The NLP (Natural Language Process) module plays a role in decomposing the natural language input by the user using various linguistic resources, and the NLU (Natural Language Understanding) module identifies the meaning of the decomposed natural language to provide answers with refined information. It is passed to the final classification model or generative model for generation. Furthermore, using the output of the NLU module, the machine learning algorithm selects an answer previously defined, or the Natural Language Generation (NLG) module generates a new answer. Machine learning-based chatbots are capable of high-level conversations, but they can include high-level natural language processing technology, and many linguistic resources and data must be prepared in advance for the NLP module and NLU module (corpus dictionary, morpheme dictionary, semantic dictionary)

In addition, machine learning modules created to perform specific tasks often need to be newly developed depending on the application field, and most of them are difficult to recycle. A one-time question-and-answer chatbot does not require a conversation management function and works similarly to a search engine that provides answers that are most relevant to a question. Most of the FAQ chatbots that provide fixed answers to frequently asked questions are designed in a one-time Q&A format. A continuous conversational chatbot has a conversation start and end, collects information from the user to achieve a specific purpose, and ends the conversation when a final response is made based on the collected information. Since it is impossible for a chatbot to give all responses on a variety of topics, the format (scenario) of a structured conversation is mostly determined according to the topic of a specific conversation. A chatbot system that operates according to a set scenario is called a frame-based discourse system. The frame-based discourse system constructs a slot, which is a set of information for answering a user's question, generates a question based on the slot, and the discourse can be developed according to a state in which required information is collected.

The search-based chatbot works by selecting and presenting the most appropriate answer among the answers stored in the existing knowledge base according to the user's question. A generation-based chatbot generates and provides a new answer that is not previously defined according to the user's question. The generative model chatbot has a large degree of freedom in generating answers, so it tends to make grammatical errors or generate unusual answers. For example, it is a search-based chatbot or a hybrid method that combines a search model and a generative model, and deep learning algorithms (Encoder-Decoder, Seq2Seq) can be applied.

For AI chatbots, conversational agents may use character-based conversational artificial intelligence. Conversational artificial intelligence that recognizes situations based on context can be used. Through continuous conversation, it is possible to understand the situation of conversation and express subjective opinions and emotions based on this. In this case, the interactive agent includes a plurality of unit agents, and each agent may be further subdivided into a knowledge base and an inference engine. The conversational agent composed of each unit agent reads and understands the conversation of the other party, and recognizes the overall conversation situation in consideration of one's own emotional state. Through this, it can proceed in the order of devising a response strategy, establishing an action plan and executing it.

First, the target language analysis agent is an agent that analyzes the meaning of the target and the emotions of the target through the sentences received from the other party. This agent grasps the meaning and emotion that the other party wants to convey through fragmentary analysis and in-depth analysis from the decision-making agent's feedback and the other party's remarks, and delivers them to the conversational situation judgment agent. Fragment analysis refers to a semantic and emotional analysis through the sentences received from the current counterpart. In-depth analysis is an analysis module for inferring the partner's actual intentions and emotions by accumulating the intentions and emotions of the partner updated through the feedback received from the situational awareness agent. Because in-depth analysis consists of only the values of fragment analysis at the beginning of the conversation, preconceived notions about the subject are reflected, and as the conversation progresses, it is updated to match the intention and emotion of the actual subject.

The second is a self-emotion identification agent, which is an agent for modeling changes in AI's own emotions through sentences received from the other party. Like the target language analysis agent, this agent also uses fragment analysis and in-depth analysis to understand the AI's own emotions from the other person's remarks and delivers them to the conversational situation determination agent. Modeling through a fragmentary reaction is a momentary emotional change that occurs through a strong reaction over a certain level of the other person. This affects sudden emotional changes or instantaneous expression of emotions caused by strong stimuli. Modeling through in-depth reaction models the emotional change that occurs and accumulates from the situation in which the conversation with the other party is in progress.

The third is a dialogue situation determination agent, which grasps the dialogue situation through the meaning and emotional state received from the target language analysis agent and the self-emotion identification agent, and the feedback of the decision-making agent, and delivers it to the decision-making agent do. In addition, feedback on the situation identified by the target language analysis agent and self-emotion identification agent is provided to update each in-depth analysis module. The fourth is a decision-making agent, which is an agent that determines the intention of the next statement, including the purpose of artificial intelligence's utterance, in the situation grasped through the conversational situation-judging agent. The decision-making agent provides feedback to the reasoning engine of the target language analysis agent and the dialogue situation determination agent to achieve a subjective interpretation of a given situation. In order to achieve its own purpose, artificial intelligence makes decisions through simulation through the emotion model created by the target language analysis agent and the self-emotion identification agent.

The fifth is the response generating agent, which is an agent that generates the intention of the next statement determined through the decision-making agent at the level of the sentence. The sixth is a sentence expression agent. The sentence expression agent is an agent that transforms the resulting sentence of the response generating agent to fit the grammar and specific accent. In the case of learning and training each of these agents, it can be modeled to enable progressively in-depth conversations by the re-learning and retrained contents, and the preset preemptive dialogue is like a parrot through continuous training and re-learning in addition to the same sentence. It is possible to build a database so that diversity can be felt like a real person rather than an artificial intelligence speaker who only speaks the same thing.

The drone news service unit 380 may crawl at least one real-time news using a drone as a keyword or a search word with a web crawler to provide drone-related real-time news. A web crawler is a computer program that browses the World Wide Web in an organized and automated way. The work of a web crawler is called web crawling or spidering, and it is a form of bot or software agent. There are two main types of web crawlers: general web crawlers and distributed web crawlers. When explaining the basic operation of a web crawler, it starts by fetching a URL from the URL Frontier module and fetching a web page of the URL using the HTTP protocol. Then, the Fetch module stores the web page in temporary storage, the Parser module extracts the text and links, and the text is sent to the Indexer. In the case of a link, whether it should be added to the URL frontier is judged by going through the Content Seen, URL Filter, and Duplication URL Element modules. At this time, it is virtually impossible to crawl all web documents with a general web crawler. more can be used.

Distributed web crawler is largely divided into two types, one of which is centralized and the other is P2P (or Fully-Distributed). A centralized distributed web crawler is a structure in which the URL manager acts like a server and the crawler acts as a client. After downloading the document from the crawler, extracting the OutLink URL and passing it to the URL manager, the URL manager checks whether the URL of the downloaded document is the URL and removes the URL duplication. In other words, the URL manager takes over the URL duplication and URL management in the general web crawler. On the other hand, in the P2P method, each crawler has a completely independent structure. In the P2P method, each crawler operates like a general web crawler. Each crawler downloads documents, extracts OutLink URLs, and deduplicates URLs. Each crawler operates independently. To do this, the list of downloaded URLs managed by each crawler must be mutually exclusive. Otherwise, the phenomenon of downloading the same document from different crawlers will occur. As a way to solve this, each crawler can manage the download URL domains by dividing them exclusively. In other words, it is a method of managing only what belongs to the download domain and passing the rest of the URLs to other crawlers. If this method is used, each crawler can operate independently.

Next, you need to extract the web content. The web content extraction technology provides a function to automatically extract the product name, author, publication date, main text, and detailed information of the resell product, which is the content to be used for information analysis from the web document. . A web content extraction system is a device that extracts only content by automatically producing rules for extracting content. A Rule Generator that automatically generates content extraction rules, and a Navigation Content Eliminator that removes navigation content from a given web document. , a content extraction rule and a content extractor that extracts content through keyword similarity comparison.

In this case, the drone comprehensive service of the present invention may provide a language compatible service for users around the world, and may provide country-specific applications. In addition, the payment system may include all of regular payment, billing payment, no passbook, credit card, virtual account, mobile phone payment, simple payment, and the like.

The permission management unit 390 uploads documents for requesting, submitting, and recording at least one type of drone-related service to a preset permission institution, and responds to any one of permission, suspension, and modification requests of the preset permission institution Permission can be granted by re-uploading the revised document. At this time, the drone service includes shooting, delivery, delivery, transportation, control, rescue, rescue, relief, rental, maintenance, repair, and aviation service for all aviation-related business such as the government, institutions, and the Aviation Administration, flight approval, aerial photography permission, device Report, insurance (product) subscription, application for business registration approval, etc. are uploaded to the server, and the server automatically transmits the related information to the server linked to the institution. It is a system that connects with governments and institutions to provide simple and fast service.

Hereinafter, an operation process according to the configuration of the comprehensive service providing server of FIG. 2 will be described in detail with reference to FIGS. 3 and 4 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. 3A , a comprehensive service according to an embodiment of the present invention aims to provide all services related to a drone. And, it is possible to support the entire process from education to permission and use by linking each subject as shown in FIG. 3B and linking educational institutions and permission-related institutions. In addition, in order to prevent a situation in which a burden on the consumer as shown in Fig. 3c occurs, a backup is provided in various fields such as advertisement, content, navigation, and check items as shown in Fig. 4a. In addition, real-time consultation and quotation are possible based on the multilingual system as shown in FIG. 4B, and services for all matters such as global control, weather information, shopping mall connection for product purchase, emergency request, and flight permit application can be provided. have.

When using the platform according to an embodiment of the present invention as shown in FIG. 4C , consumers can lower the amount they spend, and the scope of the service provider is expanded to not only companies but also individuals, so demand creation is possible. In addition, it is possible to search and consult in your native language in real time for matters essential for flight. The applicant has already secured users, and if individuals, organizations, institutions and companies are added, the demand is expected to increase. And, as shown in Fig. 4d, by providing not only B2C but also B2B contracts and services, we secure continuous users and expand the market. It makes it possible for anyone to have a source of income, even when unemployment is extreme.

The matters not described for the AI and big data-based drone comprehensive service provision method of FIGS. 2 to 4 are the same as or described for the AI and big data-based drone comprehensive service provision method through FIG. 1 above. Since it can be easily inferred from the contents, the following description will be omitted.

5 is a diagram illustrating a process in which data is transmitted/received between components included in the AI and big data-based drone comprehensive service providing system 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 the 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 comprehensive service providing server receives at least one type of service from at least one service provider terminal, maps it with at least one service provider terminal, and stores it ( S5100 ), and stores at least one type of service from the user terminal ( S5100 ). When the service of is requested, at least one service provider terminal providing the requested service is extracted and an estimate is requested (S5200).

In addition, the comprehensive service providing server, when a quotation is received from at least one service provider terminal, transmits it to the user terminal (S5300), and completes matching when a service provider who submitted any one quotation is selected from the user terminal (S5400) ).

Finally, the comprehensive service providing server receives and uploads, as feedback, a review after receiving the service when the deposit is completed from the user terminal (S5500).

The order between the above-described steps (S5100 to S5500) is only an example, and is not limited thereto. That is, the order between the above-described steps ( S5100 to S5500 ) may be mutually changed, and some of these steps may be simultaneously executed or deleted.

Matters not described with respect to the AI and big data-based drone comprehensive service provision method of FIG. 5 are the same as or described for the AI and big data-based drone comprehensive service provision method through FIGS. 1 to 4 above. Since it can be easily inferred from the contents, the following description will be omitted.

The AI and big data-based drone comprehensive service providing method according to the embodiment described with reference to FIG. 5 is also 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 be 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 AI and big data-based drone comprehensive service providing method according to an embodiment of the present invention described above is applied to 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 by the application store server, an application or an application (ie, a program) directly installed in the master terminal through an application providing server such as a web server related to the service by the user. In this sense, the AI and big data-based drone comprehensive service providing method according to an embodiment of the present invention described above is implemented as an application (ie, program) installed by default in a terminal or directly installed by a user, and is installed on a computer such as a terminal. It can 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 (10)

When at least one type of service related to the drone is requested, and a reverse auction type of quotation for the requested service is received, the service provider that submitted any one of the received quotations is selected to complete matching, and the service is used a user terminal that transmits a feedback of receiving a service after completing the deposit for the user terminal;
Uploading at least one type of service related to the drone, inputting a quote for the requested service, transmitting it to the user terminal, and receiving a payment for the service provided after providing the service when selected from the user terminal at least one service provider terminal; and
A storage unit for receiving at least one type of service from at least one service provider terminal, mapping it with the at least one service provider terminal and storing it, and when at least one type of service is requested from the user terminal, the requested service A requesting unit for requesting an estimate by extracting at least one service provider terminal providing a comprehensive service providing server comprising: a matching unit that completes matching when a submitted service provider is selected;
including,
The comprehensive service providing server,
a live talk management unit for performing information sharing using at least one of real-time postings, comments, and chatting in the user terminal and at least one service provider terminal, and uploading attachments of content including photos and videos;
A certification institution that processes company registration certified through authentication of at least one institution that performs online and offline education, and manages at least one certification institution that conducts education on the user terminal and at least one service provider terminal Management;
a real-time counseling service unit that provides a real-time counseling service to the user terminal and at least one service provider terminal based on an artificial intelligence (AI) chatbot and a big data platform;
a drone news service unit that provides real-time news related to drones by crawling at least one real-time news using a drone as a keyword or a search term with a web crawler;
Upload documents for requesting, submitting, and recording at least one kind of service related to the drone to a preset permitting institution, and upload the documents modified in response to any one of the permission, hold, and correction requests of the preset permitting institution Permission management department that receives permission by re-uploading;
a shopping mall operation unit that sells at least one kind of product related to the drone, including a drone, at least one part of the drone, a controller, insurance, and a book, and manages a shopping cart, points, and coupons;
a usage history management unit that provides usage details of at least one type of service related to the drone in the user terminal, and shares, posts, and transmits at least one data of the user terminal;
Weather and flight information providing unit that provides real-time weather information and flight information;
further comprising,
At least one kind of service related to the drone is a service including shooting, control, performance, rental, repair and delivery,
The web crawler is a P2P (or Fully-Distributed) based distributed web crawler,
The shopping mall operation unit analyzes the purchase history and target customer base to perform target marketing, but estimates the association rule reliability based on the association rule algorithm, and any one of items, industries, and items for which the association rule reliability exceeds a preset value. providing the above to the user terminal as an advertisement,
When the live talk management unit performs information sharing by using at least one of real-time postings, comments, and chatting in the user terminal and at least one service provider terminal, the real-time posting, comments, and chatting are related to a specific drone. Characterized in that the morpheme analysis and sentiment dictionary construction is carried out to analyze whether a review or evaluation is made, and the result is mapped with the specific drone and stored, and described in addition to details when selling or renting the specific drone AI and big data-based drone comprehensive service provision system. delete delete delete delete delete delete delete delete delete

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