Ai pole having distribution control intelligence with spontaneous polarization effect antenna

Abstract

To provide an AI pole having a distribution control intelligence with a spontaneous polarization effect antenna (SOMPA).SOLUTION: An AI pole having a distribution control intelligence with a spontaneous polarization effect antenna comprises: a device part including a camera and a sensor part; and a distribution control intelligence part in which data and a video image signal to be collected by the device part are analyzed based on each function-specific AI algorithm, and the analysis information is integrated with analysis information of an IoT sensor terminal or / and WiFi terminal data, received from a gateway system, to perform integration analysis, and which makes real-time decisions based on the analysis result. The AI pole further comprises a gateway system that is equipped with SOMPA, collects data from external IoT sensor terminals or / and the WiFi terminal data, and transmits the data to the distribution control intelligence part.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present invention relates to an AI pole with distributed control intelligence equipped with a polarized current effect antenna, which improves the radio wave environment by being equipped with a polarized current effect antenna, has distributed control intelligence that enables cooperation between AI poles such as joint analysis and data sharing by utilizing edge computing technology, and can provide a variety of innovative services such as facility management, safety management, and data collection in the vicinity of the AI ​​pole. [Background technology]

[0002] A smart pole is defined in a broader sense than smart streetlights, and is a type of streetlight that adds energy-saving LED lighting, CCTV, and wireless internet broadcasting functions to existing streetlights. It is a type of pole that combines the latest ICT (Information and Communications Technologies) technologies such as WiFi, IoT (Internet of Things), intelligent CCTV, and smart crosswalks with poles that serve as various road facilities (traffic lights, street lights, CCTV, and security lights).

[0003] AI Pole is a core device that can autonomously manage the pole and develop various smart city services by combining AI technology and edge computing technology with smart pole.

[0004] AI poles are evolving by pursuing the integration of 5G and communications technologies, big data and artificial intelligence technologies, environmentally friendly and energy-efficient designs, multi-function sensors and improved IoT capabilities.

[0005] In addition, AI Poles make urban life more convenient and safer by providing a variety of functions, including wireless charging facilities, safety cameras, environmental sensors and public WiFi.

[0006] In the future, AI poles are expected to provide more diverse functions and integrated services, promote urban intelligence, and further expand their positive impacts, such as contributing to energy conservation and environmental protection through the creation of smart cities.

[0007] AI poles for smart cities are a core technology that will revolutionize the existing urban environment, and many cities are expected to adopt AI poles to improve urban management and the quality of life of their citizens.

[0008] Edge computing means that computing resources are located close to where the data is generated, i.e., close to the "edge" of the data.

[0009] The goal is to process data on the device that generates it, or on an edge computing device, instead of transmitting the data to a central server such as a central data center or cloud.

[0010] This allows for real-time response and data processing, providing faster response times in bandwidth-limited situations.

[0011] In addition, some data can be processed at the edge instead of being transmitted to a central data center due to privacy issues.

[0012] Edge computing can be applied in a variety of industrial fields.

[0013] For example, smart grids can use edge computing to manage and optimize energy production and usage.

[0014] Additionally, in the smart healthcare field, edge computing can be used for patient monitoring and real-time data processing by medical devices.

[0015] In the manufacturing industry, edge computing can be used for monitoring and controlling production lines, and it also plays an important role in autonomous vehicles, smart cities, etc.

[0016] AI poles with distributed control intelligence based on edge computing can make and act on their own decisions through data collection and other means in distributed installation environments such as roads, public places, around urban rivers, and construction sites, and can interact with each other through network connections and provide a variety of smart city application services by linking with the control system and cloud.

[0017] The main functions of the AI ​​pole with distributed control intelligence are as follows: (1) Environmental sensing and monitoring function: Senses and monitors surrounding environmental data to collect relevant information (2) Autonomous operation and adjustment function: Operate and adjust autonomously in response to environmental changes (3) Networked cooperation and communication functions: Supports efficient communication and data exchange with other AI poles. (4) Automated cooperation and coordination within the network: Multiple AI poles work together in an automated manner

[0018] There are practical issues with using 5G communication networks to build AI poles with distributed control intelligence and realize smart cities, such as the significant construction and operating costs required.

[0019] To solve these problems, it is essential to build private wireless networks in cities using unlicensed bands.

[0020] However, building private wireless networks in unlicensed bands poses many difficulties due to problems such as mutual radio interference, limited coverage due to obstacles, and low reliability.

[0021] This problem can be solved by coupling with an antenna using the polarized current effect based on Korean Patent Registration No. 10-1017690 (polarized current effect and its applications).

[0022] The electro-polarization effect refers to a method disclosed by the applicant for controlling the direction of electric current flowing in a conductor.

[0023] If such a bias current effect is utilized in a communication circuit, it is possible to eliminate the need for passive elements such as a filter duplexer and an isolator in the output section, which are necessary when constructing a communication circuit and a communication device. This has the advantage that the loss generated by such passive elements can be reduced, thereby improving the performance of the communication device. Furthermore, by omitting the passive elements, it is possible to realize a communication device that is cost-effective and lightweight.

[0024] In addition to enabling long-distance communication, scattering phenomena caused by rain, fog, dust, etc. can be prevented, and scattering phenomena caused by obstacles such as signs and facilities in urban areas can also be prevented, resulting in the effect of creating a stable wireless communication environment.

[0025] In light of this background, the present invention proposes an AI pole that is equipped with a polarized effect antenna to improve the radio wave environment, and is equipped with edge computing technology to have distributed control intelligence that enables cooperation between AI poles, such as joint analysis and data sharing, and can provide a variety of innovative services, such as facility management, safety management, and data collection in the vicinity of the AI ​​pole. [Prior art documents] [Patent documents]

[0026] [Patent Document 1] Korean Patent No. 10-2571119 [Patent Document 2] Korean Patent No. 10-1890814 [Patent Document 3] Korean Patent No. 10-2477381 [Patent Document 4] Korean Patent No. 10-1017690 [Patent Document 5] Korean Patent No. 10-1591920 [Patent Document 6] Korean Patent No. 10-2422163 Summary of the Invention [Problem to be solved by the invention]

[0027] The present invention has been devised under the above-mentioned background, and an object of the present invention is to provide an AI pole with a polarized effect antenna and distributed control intelligence that improves the radio wave environment by installing a polarized effect antenna, has distributed control intelligence that enables cooperation such as joint analysis and data sharing between AI poles by utilizing edge computing technology, and provides a variety of innovative services such as facility management, safety management, and data collection in the vicinity of the AI ​​pole. [Means for solving the problem]

[0028] In order to achieve this object, the present invention includes a device unit including a camera and a sensor unit, and a distributed control intelligence unit that analyzes data and video signals collected by the device unit based on AI algorithms for each function, integrates the analysis information with analysis information of IoT sensor terminals and / or WiFi terminal data received from the gateway system to perform an integrated analysis, and makes real-time decisions based on the analysis results, and is characterized in that it further includes a gateway system equipped with SOMPA to collect data from external IoT sensor terminals and / or WiFi terminal data and transmit it to the distributed control intelligence unit.

[0029] According to the present invention, the distributed control intelligence unit comprises: The device includes an interface unit that transmits and receives data to and from IoT sensor terminals and / or WiFi terminals via a device unit or a gateway system, collects data, and processes signals; a control unit that controls the operation of the distributed control intelligence unit and the flow of data between each detailed function, manages security, manages the device unit and IoT sensor terminals and / or WiFi terminals, and manages the gateway system; an intelligence analysis unit that analyzes sensor data and images input through the device unit based on AI algorithms for each function, integrates analytical information of IoT sensor terminal and / or WiFi terminal data received from the gateway system to perform an integrated analysis, and makes real-time decisions based on the analysis results; and an interlocking processing unit that connects to and transmits and receives data with multiple external AI poles, connects to and transmits and receives data with gateway systems, edge network controllers, and external servers, and connects to and transmits and receives data with external signage systems.

[0030] In addition, according to the present invention, the gateway system is composed of a WiFi access point, and the WiFi access point is equipped with SOMPA and uses the SOMPA to wirelessly transmit and receive information with external WiFi terminals, external AI poles, signage systems, and public kiosk systems, and is characterized in that it connects to external control systems, service systems, external servers, etc. through an Ethernet I / F to transmit necessary information to the distributed control intelligence unit of the AI ​​pole.

[0031] According to the present invention, the gateway system is composed of an AI edge gateway, which includes an IoT RF gateway and a WiFi access point equipped with SOMPA and wirelessly transmits and receives information with external IoT sensor terminals, WiFi terminals, external AI poles, signage systems, and public kiosk systems using the SOMPA, and is characterized in that it connects to external control systems, service systems, external servers, etc. through the Ethernet I / F of the edge control unit and transmits necessary information to the distributed control intelligence unit of the AI ​​pole via the edge linkage processing unit.

[0032] According to the present invention, the process of sharing and analyzing data between AI poles, making decisions, and executing the process described in claim 1 is characterized in that the process includes a first process in which the AI ​​pole collects data on the surrounding environment input through a device unit or an external gateway system, a second process in which the AI ​​pole analyzes the data collected in the first process and determines whether or not to share the data with an external AI pole, a third process in which the AI ​​pole transmits and shares the data to the external AI pole if sharing with the external AI pole is determined in the second process, a fourth process in which the data analyzed by the external AI pole in the third process is integrated with the analysis result to identify a pattern and understand a situation, a fifth process in which a decision is made based on an AI rule based on the integrated data jointly analyzed and the understanding of the situation in the fourth process, a sixth process in which the AI ​​pole performs an operation based on the decision made in the fifth process, a seventh process in which the operation result performed in the sixth process is stored, and an eighth process in which the algorithm learns the result data in the seventh process, and based on the data accumulated over time, the algorithm is corrected to improve the algorithm more accurately, and the correction is reflected as feedback in the decision-making.

[0033] Also, according to the present invention, the third step includes the steps of transmitting the collected data to an external AI poll, analyzing the data received at the external AI poll, and generating an analysis result by integrating the analysis performed at the external AI poll with the data analysis performed at the AI ​​poll that provided the collected data.

[0034] In addition, according to the present invention, the eighth step includes a step of transmitting the performed result to an external server, a step of the external server accumulating, storing and analyzing the result data, a step of complementing the AI ​​rule after the step of accumulating, storing and analyzing the result data, and a step of applying the complemented and corrected AI rule to a rule intelligence engine and reflecting it in the fifth step of establishing a decision. Effect of the Invention

[0035] In this way, the present invention provides the effect of dramatically improving the radio wave environment by using a polarization effect antenna (SOMPA) and building a stable wireless communication environment, which makes it possible to reduce the cost of building a network and build an unlicensed communication infrastructure that enables stable, high-quality, and high-performance communication.

[0036] In addition, the present invention has a system configuration in which learning and inference are completely separated, and frequent re-learning due to rapid changes in the learning model can be performed separately on a high-performance server. The AI ​​pole executes only lightweight inference rules, making it possible to efficiently utilize AI technology even with limited edge computing performance.

[0037] In addition, the distributed control intelligence technology of the present invention can analyze and make judgments on a large amount of data in a distributed environment, making it possible to make more accurate decisions and respond appropriately to situations.

[0038] Furthermore, the present invention is equipped with technology that can analyze collected sensor data based on its own inference rules, judge the situation, and make decisions autonomously, thereby enabling the vehicle to respond appropriately to the environment without human intervention.

[0039] In addition, the AI ​​pole with distributed control intelligence according to the present invention provides the effect of reducing operating costs through automated operations and efficient resource utilization.

[0040] Furthermore, the AI ​​pole with distributed control intelligence of the present invention improves urban efficiency in various aspects such as traffic flow, environmental monitoring, and safety management, while improving the operation and management of smart cities. [Brief description of the drawings]

[0041] [Figure 1] FIG. 1 is an outline drawing of an AI pole with distributed control intelligence and polarizing effect antenna according to one embodiment of the present invention. [Diagram 2] FIG. 2 is a circuit block diagram of an AI pole with distributed control intelligence and a polarizing effect antenna according to an embodiment of the present invention. [Diagram 3] FIG. 3 is a detailed diagram of a WiFi access point according to one embodiment of the gateway system of FIG. [Figure 4] FIG. 4 is a diagram showing an AI edge gateway according to another embodiment of the gateway system of FIG. [Diagram 5] FIG. 5 is a diagram showing a manhole smart node system for explaining the SOMPA technology applied to the present invention. [Figure 6] FIG. 6 is a diagram showing a configuration for testing the system shown in FIG. [Figure 7] FIG. 7 is a diagram showing a configuration in which the SOMPA of FIG. 5 is actually installed inside a manhole. [Figure 8] FIG. 8 is a table showing the results of technical comparison performance measurements between the SOMPA applied to the present invention and a conventional omni-antenna. [Figure 9] FIG. 9 is a flow chart showing a process of sharing and analyzing data between AI poles, making decisions, and executing the decisions according to the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0042] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings.

[0043] First, when assigning reference numerals to components in each drawing, it should be noted that the same reference numerals are used for the same components even if they are shown in different drawings. Furthermore, when describing the present invention, detailed descriptions of related publicly known functions or configurations are omitted if it is determined that such descriptions may unnecessarily obscure the gist of the present invention.

[0044] FIG. 1 is an outline drawing of an AI pole with distributed control intelligence and polarizing effect antenna according to one embodiment of the present invention.

[0045] As shown in the figure, the AI ​​pole 100 of the present invention is: It includes a base part 210 fixed to the ground, a pillar part 211 formed vertically on the upper part of the base part 210, an arm part 212 formed horizontally on one side of the upper part of the pillar part 211, and a drone station part 213 formed on the upper end of the pillar part 211.

[0046] In addition, a speaker 214, a signage 215, and an SOS button 216 are formed on the pillar portion 211, a plurality of cameras 217, an electronic board 218, and a warning light 219 are installed on the arm portion 212, and a battery portion 221, a charging portion 222, a street light controller 223, and a number of sensor portions 224 are mounted inside or on the surface of the base portion 210 and the pillar portion 211.

[0047] In addition, a gateway system 400 having a polarized effect antenna may be further installed on the upper end of the pole 211 .

[0048] The AI ​​pole 100 having such an external shape includes a device section 200 and a distributed control intelligence section 300 as shown in FIG.

[0049] The device section 200 includes a speaker 214 , a signage 215 , an SOS button 216 , a number of cameras 217 , an electronic board 218 , a warning light 219 , a battery section 221 , a charging section 222 , a street light controller 223 , and a number of sensor sections 224 .

[0050] The speaker 214 and the signage 215 output the audio signal and the signage signal transmitted from the distributed control intelligence unit 300, respectively.

[0051] The SOS button 216 generates an SOS key signal when the button is pressed, and transmits the SOS key signal to the distributed control intelligence unit 300 .

[0052] The light board 218 and the warning light 219 perform display or turn on / off the warning light according to commands transmitted from the distributed control intelligence unit 300 .

[0053] The multiple cameras 217 capture images of the surroundings and transmit the captured image signals to the distributed control intelligence unit 330, and the multiple sensor units 224 detect the surrounding temperature, humidity, etc. and transmit the detected signals to the distributed control intelligence unit 330.

[0054] The battery unit 221 and the charging unit 222 are managed under the control of the distributed control intelligence unit 300 to perform a charging function, and the street light controller 223 controls turning on and off the street lights under the control of the distributed control intelligence unit 300 .

[0055] The distributed control intelligence unit 300 includes an interface unit 310 , a control unit 320 , an intelligence analysis unit 330 , and an interlocking processing unit 340 .

[0056] The interface unit 310 transmits and receives data to and from IoT sensor terminals and / or WiFi terminals via the device unit 200 or the gateway system 400, collects data, and processes signals.

[0057] The control unit 320 controls the operation of the distributed control intelligence unit 300 and the flow of data between each detailed function, manages security, manages the device unit 200 and IoT sensor terminals and / or WiFi terminals, manages the gateway system 400, etc.

[0058] The intelligent analysis unit 330 analyzes the sensor data and images input through the device unit 200 based on AI algorithms for each function, integrates the analysis information of the IoT sensor terminal and / or WiFi terminal data received from the gateway system 400, performs an integrated analysis, and makes real-time decisions based on the analysis results.

[0059] The interlocking processor 340 performs connection and data transmission / reception with a number of external AI poles, connection and data transmission / reception with the gateway system 400, edge network controller, and external servers, and connection and data transmission / reception with an external signage system.

[0060] The gateway system 400 connected to the AI ​​pole 100 configured in this manner may be a WiFi access point 410 or an AI edge gateway 420.

[0061] As shown in FIG. 3, the WiFi access point 410 is equipped with an antenna that uses the electro-polarization effect (hereinafter referred to as “SOMPA” or “electro-polarization effect antenna”), and uses the SOMPA to wirelessly transmit and receive information with external WiFi terminals, external AI poles, signage systems, and public kiosk systems, and connects to external control systems, service systems, external servers, etc. through an Ethernet I / F (interface) 412 to transmit necessary information to the distributed control intelligence unit 300 of the AI ​​pole 100.

[0062] In addition, as shown in FIG. 4, the AI ​​edge gateway 420 includes an IoT RF gateway 421 and a WiFi access point 422 that are equipped with SOMPA and use the SOMPA to wirelessly transmit and receive information with external IoT sensor terminals, WiFi terminals, external AI poles, signage systems, and public kiosk systems, and connects to external control systems, service systems, external servers, etc. via the Ethernet I / F of the edge control unit 423 and transmits necessary information to the distributed control intelligence unit 300 of the AI ​​pole 100 via the edge linkage processing unit.

[0063] Incidentally, the SOMPA technology utilizing the electric current polarization effect is based on the applicant's Korean Patent Publication No. 10-1017690 (Electric current polarization effect and its applications), and SOMPA is disclosed in Korean Patent Publication No. 10-1591920 (Directional MIMO antenna utilizing electric current polarization effect) and Korean Patent Publication No. 10-2422163 (Omni-directional antenna utilizing electric current polarization effect).

[0064] The MIMO (Multi-Input Multi-Output) antenna of Korean Patent No. 10-1591920 is a structure that radiates radio waves in a certain direction by aligning the phase of the array of antenna radiators to improve antenna gain, and provides the effect of directing radio waves only in a specific direction, thereby increasing the service distance in a specific direction. The omni antenna of Korean Patent No. 10-2422163 improves on the patch antenna that uses the polarized effect to radiate radio waves in a perfect circle in all directions 360°, thereby facilitating service in open areas and suppressing radio wave scattering to provide excellent long-distance and obstacle-overcoming characteristics.

[0065] Such SOMPA has demonstrated outstanding performance when combined with WiFi terminals, WiFi access points, IoT terminals, IoT RF gateways, etc.

[0066] In other words, by utilizing the bias current effect in a communication circuit, there is an advantage in that it is not necessary to use passive elements such as a filter duplexer and an isolator in the output section, which are necessary when constructing a communication circuit and a communication device. This reduces the loss generated by such passive elements, thereby improving the performance of the communication device. Furthermore, by omitting the passive elements, it is possible to realize a communication device that is cost-effective and lightweight.

[0067] In addition to enabling long-distance communication, scattering phenomena caused by rain, fog, dust, etc. can be prevented, and scattering phenomena caused by obstacles such as signs and facilities in urban areas can also be prevented, resulting in the effect of creating a stable wireless communication environment.

[0068] To verify its effectiveness, a terminal combining LoRa® technology and SOMPA technology was installed underground, and monitoring data on facilities such as internal cables was transmitted through a manhole to an IoT gateway located 100m outside, and performance was measured.

[0069] Figure 5 is a diagram showing a manhole smart node system for explaining the SOMPA technology applied to the present invention, Figure 6 is a diagram showing a test configuration of the system of Figure 6, and Figure 7 is a diagram showing a configuration in which the SOMPA of Figure 5 is actually installed inside a manhole.

[0070] The manhole smart node system is a disaster prevention IoT system that installs a sensor node inside a manhole to transmit and receive data on the internal condition of the manhole to the ground in order to grasp the safety condition inside the manhole of an underground power distribution line.

[0071] Up until now, various types of antennas have been applied and tested, but radio communication was not possible through the thick double manhole, so a wired method was used to drill a manhole and connect an optical cable. However, by applying SOMPA technology, there is no need to drill a manhole at all, and it was confirmed that its performance far surpasses that of AI technology.

[0072] That is, as shown in the technical comparison performance measurement result table of the SOMPA applied to the present invention and the conventional omni-antenna in FIG. 8, the SOMPA technology method installed inside the manhole without drilling a hole can achieve a performance improvement of 20 dB compared to the method of using an AI antenna to drill a manhole and transmit.

[0073] Meanwhile, the AI ​​Pole 100 configured in this manner acquires, stores and analyzes data on the surrounding situation to provide alarms, notifications, public WiFi services, and other services such as citizen safety management and traffic management.

[0074] In addition, AI can be used to perform a comprehensive analysis of collected sensor data and video data, enabling more thorough analysis of the surrounding situation and making decisions.

[0075] It also works in conjunction with other surrounding AI poles to analyze the data it acquires, and integrates and analyzes the results to make appropriate decisions and take action.

[0076] In addition, by combining SOMPA technology, the wireless connection range of the AI ​​pole will be expanded, overcoming obstacles and providing services such as underground buried object management.

[0077] In addition, one of the characteristic configurations of the present invention is the function of the AI ​​pole 100 transmitting and sharing data collected from situations based on AI to other AI poles, thereby jointly analyzing the situation, making decisions, and then executing them.

[0078] Decision-making and execution will be carried out by the AI ​​pole that is determined to be most suitable for the situation after analyzing the situation.

[0079] For example, consider a situation in which two AI poles work together to find a person.

[0080] The first AI pole runs an AI image analysis algorithm to recognize similar facial features and clothing among a large number of moving people, but if it cannot clearly identify them, it transmits the recognized data to the second AI pole along its route. The second AI pole determines whether or not the person is the person being searched for based on the transmitted data and newly recognized data, and transmits the result to the control system.

[0081] FIG. 9 is a flow chart showing a process of sharing and analyzing data between AI poles, making decisions, and executing the decisions according to the present invention.

[0082] As shown in the figure, the process of sharing and analyzing data between AI poles, making decisions, and executing them according to the present invention is as follows: The AI ​​pole 100 includes a first process S10 for collecting data on the surrounding environment input through an interface unit 310 or an external gateway system 400, a second process S20 for analyzing the data collected in the first process S10 and determining whether or not to share the data with an external AI pole, a third process S30 for transmitting and sharing the data to the external AI pole if it is determined in the second process S20 that the data should be shared with the external AI pole, a fourth process S40 for integrating the data analyzed by the external AI pole in the third process S30 with the analysis result to identify a pattern and understand the situation, and The method includes a fifth process S50 of establishing a decision based on an AI rule based on the integrated data jointly analyzed by the process S40 and an understanding of the situation; a sixth process S60 of the AI ​​pole 100 performing an action based on the decision established by the fifth process S50; a seventh process S70 of storing a result of the action performed by the sixth process S60; and an eighth process S80 of correcting the complement of the AI ​​rule so that the algorithm is improved more accurately based on the data accumulated over time by the seventh process S70, and feeding the corrected complement of the AI ​​rule back into the decision-making.

[0083] More specifically, the first process S10 collects surrounding information through the sensor unit 224, camera 217, etc. of the interface unit 310, or collects surrounding environment data input through an external gateway system 400, i.e., data input through an IoT sensor terminal or a WiFi terminal.

[0084] The second process S20 is a process of analyzing the data collected in the first process S10 to determine whether or not the data should be shared with an external AI poll, and includes a step S21 of determining whether or not to share and analyze the data with an external AI poll, and a step S22 of analyzing the input collected data if sharing and analysis with the external AI poll is not necessary.

[0085] The third process S30 is a process of transmitting and sharing data to an external AI poll if sharing with an external AI poll is determined in the second process S20, and includes a step S31 of transmitting collected data to the external AI poll, a step S32 of analyzing the data received from the external AI poll, and a step S34 of generating an analysis result by integrating the analysis performed at the external AI poll with a data analysis performed at the AI ​​poll 100 that provided the collected data (S33).

[0086] The collected data is then sent to other external AI poles through an AI-based algorithm, and the data is then shared through the network to other poles.

[0087] The fourth step S40 is a step of integrating the data analyzed by the external AI poll in the third step S30 with the analysis result to identify patterns and understand the situation, and the data received from the external AI poll is jointly analyzed and used to understand the situation, which means integrating data to identify patterns and understand the situation.

[0088] The fifth process S50 is a process of establishing a decision based on AI rules based on the integrated data jointly analyzed by the fourth process S40 and understanding of the situation, and the AI ​​pole 100 makes an integrated decision based on the jointly analyzed data and understanding of the situation. This decision is made by the AI ​​pole determined by the algorithm and includes response measures and adjustments to the surrounding environment.

[0089] The sixth step S60 is a step in which the AI ​​Pole 100 performs an operation based on the decision made in the fifth step S50, and the AI ​​Pole 100 takes a response measure to the environment, such as adjusting lighting or camera angle, activating an alarm system, or issuing a warning to an administrator.

[0090] The seventh step S70 is a step of storing the operation result performed by the sixth step S60, and the eighth step S80 is a step of modifying the AI ​​rule complement so that the algorithm learns the result data by the seventh step S70 and improves the algorithm more accurately based on the data accumulated over time, and feedbacking and reflecting the same in the decision-making. The eighth step S80 includes a step S81 of transmitting the performed result to an external server, a step S82 of the external server accumulating, storing and analyzing the result data, a step S83 of complementing the AI ​​rule after the step S82 of accumulating, storing and analyzing the result data, and a step S84 of applying the complemented and modified AI rule to a rule intelligence engine and reflecting the same in the fifth step S50 of establishing a decision-making.

[0091] As the algorithm learns over time and data about the environment is accumulated, the algorithm can be adjusted and modified. This involves the process of improving the algorithm to operate more accurately, and this process is carried out on an external AI server connected to the network, and all data from the AI ​​poll is stored in a data hub.

[0092] This step-by-step process will enable the AI ​​pole's AI edge situational awareness and sharing algorithms to enable multiple poles to interact with each other to achieve better situational understanding and decision-making.

[0093] Although limited embodiments of the present invention have been described above, those skilled in the art should note that the present invention is not limited to these embodiments, and various other embodiments are anticipated. [Explanation of symbols]

[0094] 100 AI pole 200 Device Division 210 Base 211 Column section 212 Arm section 213 Drone Station Department 214 Speakers 215 Signage 216 SOS button 217 Camera 218 Electric board 219 Warning light 300 Distributed Control Intelligence Department 310 Interface section 320 Control Unit 330 Intelligence Analysis Department 340 Interlocking Processing Unit 400 Gateway System 410 WiFi Access Point 420 AI Edge Gateway

Claims

1. A device unit including a camera and a sensor unit; The data and video signals collected by the device unit are analyzed based on AI algorithms for each function, and the analysis information is integrated with analysis information of the IoT sensor terminal and / or WiFi terminal data received from the gateway system to perform an integrated analysis, and a distributed control intelligence unit is included that makes real-time decisions based on the analysis results; An AI pole with distributed control intelligence and a polarizing effect antenna, further comprising a gateway system equipped with a SOMPA that collects data from external IoT sensor terminals and / or WiFi terminal data and transmits the data to the distributed control intelligence.

2. The distributed control intelligence unit includes: An interface unit that transmits and receives data to and from an IoT sensor terminal and / or a WiFi terminal via a device unit or a gateway system, collects data, and processes signals; A control unit that controls the operation of the distributed control intelligence unit and the flow of data between each detailed function, manages security, manages the device unit and IoT sensor terminals and / or WiFi terminals, manages a gateway system, etc.; an intelligent analysis unit that analyzes the sensor data and images input through the device unit based on AI algorithms for each function, integrates the analysis information of the IoT sensor terminal and / or WiFi terminal data received from the gateway system, performs an integrated analysis, and makes real-time decisions based on the analysis results; The AI ​​pole with distributed control intelligence and a polarization effect antenna as described in claim 1, characterized in that it includes an interlocking processing unit that connects to a plurality of external AI poles and transmits and receives data, connects to a gateway system, an edge network controller, an external server, etc., and transmits and receives data, and connects to an external signage system and transmits and receives data, etc.

3. The gateway system is configured with a WiFi access point, The WiFi access point is equipped with SOMPA and uses the SOMPA to wirelessly transmit and receive information to and from an external WiFi terminal, an external AI pole, a signage system, and a public kiosk system; The AI ​​pole with distributed control intelligence and a polarization effect antenna as described in claim 1, characterized in that it is connected to an external control system, a service system, an external server, etc. through an Ethernet I / F to transmit necessary information to the distributed control intelligence unit of the AI ​​pole.

4. The gateway system is composed of an AI edge gateway, The AI ​​edge gateway includes an IoT RF gateway and a WiFi access point equipped with SOMPA and using the SOMPA to wirelessly transmit and receive information with external IoT sensor terminals, WiFi terminals, external AI poles, signage systems, and public kiosk systems, and connects to external control systems, service systems, external servers, etc. through the Ethernet I / F of the edge control unit and transmits necessary information to the distributed control intelligence unit of the AI ​​pole via the edge linkage processing unit. The AI ​​pole with distributed control intelligence and a polarization effect antenna as described in claim 1.

5. A process for sharing and analyzing data between AI poles according to claim 1, and making and executing decisions, A first step of collecting data on the surrounding environment inputted through a device unit or an external gateway system by the AI ​​pole; A second step of analyzing the data collected in the first step and determining whether or not to share the data with an external AI poll; a third step of transmitting data to the external AI pole to share the data if sharing with the external AI pole is determined in the second step; A fourth process of integrating the data analyzed by the external AI poll in the third process with the analysis results to identify patterns and understand the situation; A fifth process of establishing a decision based on AI rules based on the integrated data jointly analyzed by the fourth process and understanding of the situation; A sixth step in which the AI ​​pole performs an operation based on the decision-making established by the fifth step; A seventh step of storing the result of the operation performed by the sixth step; The seventh step is performed by the algorithm learning the result data, and the eighth step is performed by correcting the AI ​​rule complement so that the algorithm is improved more accurately based on the data accumulated over time, and feeding back the result to the decision-making.

6. The third step includes transmitting the collected data to an external AI poll; Analyzing the received data at an external AI poll; The AI ​​pole with distributed control intelligence and a polarization effect antenna as described in claim 5, further comprising a step of integrating the analysis performed by the external AI pole with the data analysis performed by the AI ​​pole that provided the collected data to generate an analysis result.

7. The eighth step includes transmitting the performed result to an external server; The external server stores and analyzes the result data; After accumulating, storing and analyzing the result data, a step of complementing the AI ​​rule; The AI ​​pole with distributed control intelligence and a polarizing effect antenna as described in claim 5, further comprising a step of applying the supplemented and corrected AI rule to a rule intelligence engine and reflecting the result in a fifth process of establishing a decision.

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