KR20240039954A - Satellite-based location information correction method and system - Google Patents

Abstract

In order to solve the problems described above, the satellite-based location information correction method according to the present invention includes the steps of receiving GPS information using a GPS device, and in response to receiving the GPS information, requesting location prediction data from the AI processing unit. obtaining the location prediction data from the AI processing unit, determining location accuracy based on the location prediction data, and if the location accuracy is less than the threshold, satellite information from a satellite based augmentation system (SBAS) satellite. It may be characterized by comprising the step of receiving and correcting the GPS information using the satellite information.

Description

Satellite-based location information correction method and system {SATELLITE-BASED LOCATION INFORMATION CORRECTION METHOD AND SYSTEM}

The present invention relates to a method and system for correcting satellite-based location information. More specifically, it relates to a method and system for performing position correction using a satellite based augmentation system (SBAS) according to preset conditions using artificial intelligence (AI).

In accordance with the 4th Industrial Revolution and hyper-connected society trends, IoT technology is being applied to various industrial fields, and WoT (Web of Thing), which aims to connect all connectable objects to the web, has recently become a hot topic.

IoT access technology refers to a technology that can autonomously share information between devices without artificial human intervention, and it is expected that approximately 30 billion objects will be able to connect and share information by 2025.

In IoT access technology, information collection technology using wireless communication technology is receiving particular attention. In addition to Wi-Fi and Bluetooth technologies, which are widely used to date, LTE-MTC (LTE Machine-MTC) has recently been developed to complement the shortcomings of existing technologies. Low-power long-distance communication (LPWA) and technologies such as Type Communication, IoT, and Lora are emerging as next-generation Internet of Things access technologies.

IoT technology, which previously could not be applied due to limitations in battery and communication distance, has expanded its scope of application thanks to LPWA technology, and recently, real-time control has become possible to apply from high-priced to low- and mid-priced assets.

Meanwhile, in the case of technologies and products using existing IoT technology, high-speed communication, constant battery supply, and high communication costs were problems.

Currently, the Internet of Things technology demanded by customers is low in capacity, and they want Internet of Things technology, which is an expansion technology of the Internet of Things that can provide simple information at low speed and low power, extend battery life, and reduce terminal prices and communication operating costs. Especially in the asset management market. There is high demand for low-power/low-cost communication technology.

From a technical perspective, it is being developed into Long Range (Outdoor) technology and Short or Middle Range (Indoor) technology depending on communication coverage and operating environment. Due to the nature of IoT devices, they mainly use batteries with small capacity, so data is limited in power. LPWAN (Low Power Wide Area Network) technology, which can perform communication and requires little facility investment, is attracting attention.

Each LPWAN technology needs to be competitive in terms of frequency acquisition cost, infrastructure installation cost, terminal production cost, communication quality, and communication speed.

Additionally, precise location correction technology is needed to provide the Internet of Things technology currently demanded by customers.

However, general commercial GPS modules cannot guarantee accuracy of less than 5M position error even in an open sky environment, and this GPS position error does not sufficiently satisfy field requirements requiring LBS (Location-based service) technology. .

Correction is performed using auxiliary positioning information such as cell positioning and WI-FI, but there are limitations to real-time correction due to limitations in the terminal battery.

Therefore, there is a need for the development of low-cost communication and cost-reduced IoT terminals, and the development of new technologies to complement the functional limitations of GPS.

The present invention is intended to solve the problems of the LBS (Location-based service) technology of the prior art, and provides a satellite-based error correction system that enables the implementation of an IoT device for outdoor hybrid positioning using the SBAS (Satellite Based Augmentation System) function. The purpose is to provide a system and method for position correction.

The present invention is a system and method for location correction using a satellite-based error correction system that can minimize errors that may occur due to GPS error in IoT terminals by applying SBAS technology to reduce GPS error within a certain range. The purpose is to provide.

The present invention provides an IoT terminal for LPWA-based asset management and outdoor positioning capable of low-cost, low-power communication, and an asset control service platform that integrates and collects and manages outdoor positioning and asset status information (impact, detachment, battery). The purpose is to provide a system and method for position correction using a satellite-based error correction system that can be constructed.

The present invention implements an IoT terminal and asset control service platform that enables asset control services to be provided through web/mobile on a cloud basis, and provides location correction using a satellite-based error correction system that is advantageous for early construction and operation in the actual field. The purpose is to provide a system and method for

The purpose of the present invention is to provide a system and method for satellite-based location correction that omits the location correction process using SBAS technology when assets are congested for a long time and utilizes a highly reliable predicted location using a machine learning-based model. There is.

Other objects of the present invention are not limited to the objects mentioned above, and other objects not mentioned will be clearly understood by those skilled in the art from the description below.

The satellite-based location information correction method according to the present invention for achieving the above purpose includes receiving GPS information using a GPS device, and in response to receiving the GPS information, requesting location prediction data from the AI processing unit. obtaining the location prediction data from the AI processing unit, determining location accuracy based on the location prediction data, and if the location accuracy is less than the threshold, satellite information from a satellite based augmentation system (SBAS) satellite. It may be characterized by comprising the step of receiving and correcting the GPS information using the satellite information.

Furthermore, the GPS information includes data based on a specific standard, and the step of requesting the location prediction data from the AI processing unit further includes transmitting at least some of the data based on the specific standard to the AI processing unit. It can be characterized as:

Furthermore, the AI processing unit may include an artificial neural network for generating the location prediction data, and the location prediction data may be characterized in that at least part of the data is input to the artificial neural network and output from the artificial neural network. You can.

Furthermore, the artificial neural network may be characterized by learning how to generate the location prediction data by receiving data included in GPS information.

Furthermore, if the location accuracy is greater than a preset threshold, the method may further include turning off power to the GPS device.

Furthermore, correcting the GPS information using the satellite information includes acquiring a plurality of satellite information during a predetermined period of time, and correcting the GPS information based on the acquired plurality of satellite information. More may be included.

Furthermore, the GPS information is received according to a designated period through the GPS device, and includes the step of correcting the GPS information based on an average value of the plurality of satellite information acquired according to the designated period during the predetermined time. can do.

Furthermore, receiving the GPS information using the GPS device may include activating the GPS device, searching for a GPS signal using the activated GPS device, and in response to the GPS signal being searched for. , may further include receiving the GPS information from GPS satellites.

According to the present invention, a satellite-based location information correction system includes a control unit, wherein the control unit of the satellite-based location information correction system receives GPS information using a GPS device, and in response to receiving the GPS information, Request location prediction data from the AI processing unit, obtain the location prediction data from the AI processing unit, determine location accuracy based on the location prediction data, and if the location accuracy is less than the threshold, SBAS (satellite based augmentation) system) It is possible to receive satellite information from a satellite and correct the GPS information using the satellite information.

A program executed by one or more processes in an electronic device according to the present invention and stored in a computer-readable recording medium, the program comprising: receiving GPS information using a GPS device; receiving the GPS information; In response, requesting location prediction data from an AI processing unit, obtaining the location prediction data from the AI processing unit, and determining location accuracy based on the location prediction data, and when the location accuracy is less than the threshold. , may include instructions for receiving satellite information from a satellite based augmentation system (SBAS) satellite and correcting the GPS information using the satellite information.

[0033] The system and method for position correction using the satellite-based error correction system according to the present invention as described above has the following effects.

First, it makes it possible to implement an IoT device for outdoor hybrid positioning using the SBAS (Satellite Based Augmentation System) function.

Second, by applying SBAS technology, GPS errors can be reduced to within a certain range, thereby minimizing errors that may occur due to GPS errors in IoT terminals.

Third, we provide IoT terminals for LPWA-based asset management and outdoor positioning that enable low-cost, low-power communication, and provide an efficient asset control service platform that collects and manages outdoor positioning and asset status information (impact, detachment, battery). so that it can be built.

Fourth, by implementing an IoT terminal and asset control service platform that can provide asset control services through web/mobile on a cloud basis, it is advantageous for early construction and operation in the actual field.

Fifth, the asset control service is applied to sites that require management of various types of assets, such as industrial gas and other chemical manufacturing suppliers, shipyards/heavy industry yards, airports and port yards, and reduces the ratio of manpower input for asset management. Cost reduction/management efficiency can be increased by preventing asset theft.

Sixth, by using a machine learning-based model, the location correction process using the SBAS function can be omitted, thereby saving system resources and increasing the efficiency of the process for utilizing location information.

Figure 1a is an overall configuration diagram of a system for position correction using a satellite-based error correction system according to the present invention.
Figure 1b is a detailed configuration diagram of an IoT terminal according to the present invention.
Figure 2 is a flowchart showing a position correction method using a satellite-based error correction system according to an embodiment of the present invention.
Figure 3 is a flowchart showing the operation of the AI processing unit according to an embodiment of the present invention.
Figure 4 is a flowchart showing a position correction method using a satellite-based error correction system according to another embodiment of the present invention.
Figures 5a and 5b are configuration diagrams for explaining the load balancing process according to the present invention.
6 to 9 are detailed flowcharts of the terminal registration process according to the present invention.

Hereinafter, embodiments disclosed in the present specification will be described in detail with reference to the accompanying drawings. However, identical or similar components will be assigned the same reference numbers regardless of drawing symbols, and duplicate descriptions thereof will be omitted. The suffixes “module” and “part” for components used in the following description are given or used interchangeably only for the ease of preparing the specification, and do not have distinct meanings or roles in themselves. Additionally, in describing the embodiments disclosed in this specification, if it is determined that detailed descriptions of related known technologies may obscure the gist of the embodiments disclosed in this specification, the detailed descriptions will be omitted. In addition, the attached drawings are only for easy understanding of the embodiments disclosed in this specification, and the technical idea disclosed in this specification is not limited by the attached drawings, and all changes included in the spirit and technical scope of the present invention are not limited. , should be understood to include equivalents or substitutes.

Terms containing ordinal numbers, such as first, second, etc., may be used to describe various components, but the components are not limited by the terms. The above terms are used only for the purpose of distinguishing one component from another.

When a component is said to be "connected" or "connected" to another component, it is understood that it may be directly connected to or connected to the other component, but that other components may exist in between. It should be. On the other hand, when it is mentioned that a component is “directly connected” or “directly connected” to another component, it should be understood that there are no other components in between.

Singular expressions include plural expressions unless the context clearly dictates otherwise.

In this application, terms such as “comprise” or “have” are intended to designate the presence of features, numbers, steps, operations, components, parts, or combinations thereof described in the specification, but are not intended to indicate the presence of one or more other features. It should be understood that this does not exclude in advance the possibility of the existence or addition of elements, numbers, steps, operations, components, parts, or combinations thereof.

Hereinafter, a preferred embodiment of the system and method for position correction using the satellite-based error correction system according to the present invention will be described in detail as follows.

The characteristics and advantages of the system and method for position correction using the satellite-based error correction system according to the present invention will become apparent through the detailed description of each embodiment below.

Figure 1a is an overall configuration diagram of a system for position correction using a satellite-based error correction system according to the present invention, and Figure 1b is a detailed configuration diagram of an IoT terminal according to the present invention.

The device and method for location correction using a satellite-based error correction system according to the present invention provides an IoT terminal for LPWA-based asset management and outdoor positioning capable of low-cost, low-power communication, and integrates outdoor positioning and asset status information. This is to efficiently build an asset management service platform that collects and manages assets.

To this end, the present invention may include a configuration that first secures location data through GPS and then secondarily corrects the primarily collected location data of GPS using SBAS.

The present invention does not include data with many errors due to the initial surrounding environment when capturing GPS and SBAS, and transmits the location information to the server (platform) after calculating the average location value to increase the reliability of the overall location data. It can be included.

In particular, since the number of terminals that can connect to the base station at the same time is limited to n, load balancing logic can be applied to reduce the probability of overload when terminals with the same period connect to the base station at the same time. there is.

Since the satellite-based error correction system (SBAS: Satellite Based Augmentation System) used in the present invention involves the occurrence of errors due to various factors in the signals provided by GPS (Global Positioning System) navigation satellites, it is necessary to monitor GPS signals and use provided messages. It is a system that can be used for safe aircraft operation through an integrity function for etc., an accuracy improvement function by differential correction of various errors, etc., and a ranging signal provision function for navigation signal availability and continuity.

The signal transmitted from SBAS includes correction information and integrity information. Types of correction information include fast correction (FC), long-term correction (LTC), and ionospheric correction information.

FC is correction information for short-term signal changes and can be applied to GNSS pseudorange information. LTC is provided in the form of correction information and rate of change of correction information for satellite orbits and clocks, and can be directly applied to GNSS satellite orbits and clocks calculated from navigation messages. SBAS ionospheric correction information is included in MT 26, and includes correction information for the ionospheric map in the form of grid points and GIVE (grid ionosphere vertical error), which indicates the estimation accuracy of the ionospheric correction information.

As shown in FIG. 1A, the system for position correction using the satellite-based error correction system according to the present invention includes location and correction information providing means (100) that provides GPS satellite information and broadcasts the received SBAS signal to users within the service area. ) and the GPS signal of the location and correction information providing means 100 and the SBAS correction and integrity information received from the geostationary satellite, calculate a reliable and accurate location, and operate the corrected location data through a mobile communication network. The IoT terminal 200 transmits to the server, generates correction information for correcting orbital and clock errors and ionospheric delay errors for GPS satellites to be used by users for location calculation, and generates integrity information to determine whether there is an abnormality in the GPS signal. It includes a location information processing means 300 that transmits the information to the location and correction information providing means 100.

Here, the location and correction information providing means 100 includes the GPS satellite 10 that provides GPS satellite information to the IoT terminal 200, and the correction information and integrity information generated by the central processing station are included in the international standard SBAS message. It is transmitted to the satellite communication station and includes a geostationary SBAS satellite 50 that broadcasts the received SBAS signal to users within the service area when the SBAS message is loaded on the SBAS signal and transmitted to the geostationary orbit satellite.

And the location information processing means 300 utilizes the information collected from the reference station 20 and the reference station 20, which receive GPS signals, generate navigation data and distance measurements, and transmit them to the central processing station 30. A central processing station (30) that generates correction information for correcting orbital and clock errors and ionospheric delay errors for the GPS satellites (10) to be used by users for location calculation, and generates integrity information to determine whether there is an abnormality in the GPS signal. And, when the correction information and integrity information generated by the central processing station (30) are included and delivered in the international standard SBAS message, the satellite communication station (40) transmits the BAS message to the geostationary satellite by carrying it in an SBAS signal with characteristics similar to GPS. Includes.

And the detailed configuration of the IoT terminal 200 is as shown in FIG. 1B.

The IoT terminal 200 has a GPS location information processing unit 200a that acquires location information by receiving GPS satellite information provided from the GPS satellite 10, and processes SBAS correction information received from the geostationary SBAS satellite 50. SBAS correction information processing unit 200b, which processes integrity information received from the geostationary SBAS satellite 50 so that it can be used for position calculation, and GPS signal and geostationary information processing unit 200c, which processes integrity information so that it can be used for position calculation. A position calculation unit 200d that calculates a reliable and accurate location using the SBAS correction and integrity information received from the orbital SBAS satellite 50, and the position data corrected by the position calculation unit 200d to the base station 60 and It includes a correction location data transmission unit 200e that transmits to the user operation server 70 through a mobile communication network.

The system for position correction using the satellite-based error correction system according to the present invention having the above configuration performs the operation for position correction as follows.

(A) First, the IoT terminal 200 acquires location information by receiving GPS satellite information from the GPS satellite 10. (B) Next, GPS signals are received from each of the reference stations 20 distributed over a wide area to generate navigation data and distance measurements.

(C) Delivered to the central processing office (30).

The central processing station 30 utilizes the information collected from the reference station to generate correction information for correcting orbital and clock errors and ionospheric delay errors for GPS satellites that users will use for location calculation and to determine whether there is an abnormality in the GPS signal. Generates integrity information for

(D) The correction information and integrity information generated by the central processing station (30) are included in the international standard SBAS message and transmitted to the satellite communication station (40).

(E) The satellite communication station 40 transmits the SBAS message to the geostationary orbit SBAS satellite 50 in an SBAS signal with characteristics similar to GPS.

(F) The geostationary SBAS satellite 50 broadcasts the received SBAS signal to users within the service area.

The IoT terminal calculates a reliable and accurate location using GPS signals and SBAS correction and integrity information received from geostationary satellites.

(G) The location data corrected in the IoT terminal is transmitted to the user operation server 70 through a mobile communication network.

The device and method for location correction using the satellite-based error correction system according to the present invention can provide asset control services through web/mobile on a cloud basis through the following applications.

For example, turn on and attach the IoT terminal to the asset control target, monitor the asset control target according to the set cycle protocol, and set the default 8-hour cycle to save battery, but an event occurs (detachment or detachment of the terminal, shock exceeding the threshold) etc.), monitoring data can be configured to be transmitted every hour, and a load balancing operation process can be applied when operating IoT terminals.

The asset management service field to which the present invention is applied may be the following fields.

The asset control service is applied to sites that require management of various types of assets, such as industrial gas and other chemical manufacturing and supply companies, shipyards/heavy industry yards, airports and port yards, to reduce the ratio of manpower input for asset management and to manage assets. It is possible to reduce costs and increase management efficiency through theft prevention.

For example, asset control services for airport yards and industrial rental cars (ladder trucks, construction vehicles) are available.

Targeting large domestic construction companies and airlines, location tracking and unauthorized use control services are available for expensive mobile assets at aviation and construction sites.

It is possible to manage assets and use it as a basic platform for dispatch services by attaching a terminal to small cargo carriers such as carts, carriers, pallets, and air cargo ULDs.

As another example, cargo and chassis control services are available in ports (port areas such as Busan, Incheon, and Ulsan) and logistics.

In other words, it is possible to service customers (port authorities, logistics companies) by identifying the location of assets such as container loading chassis or empty containers within the port and then developing an asset control service for dispatch.

As another example, expensive asset control services are available for companies related to heavy industry and shipbuilding equipment.

A detailed description of the position correction method using a satellite-based error correction system according to an embodiment of the present invention is as follows.

Figure 2 is a flowchart showing a position correction method using a satellite-based error correction system according to an embodiment of the present invention.

Specifically, the GPS ON step (S201), the GPS location search step (S202), the GPS location acquisition step (S203), the location prediction data request step (S213), the response data confirmation step (S223), and the location acquisition step using SBAS (S204). ), constant time tracking step (S205), location information memory storage step (S206), location information average value calculation step (S207), NMEA (national marine electronics association) data AI processing unit transmission step (S217), GPS OFF step (S208) , location correction is performed using SBAS according to GPS On/Off, including the location information transmission step (S209) and the equipment termination step (S210).

First, in the GPS ON step (S201), GPS is turned on for the set GPS operation time. At this time, the GPS operation time considers the time until the location is acquired using the SBAS satellite.

Next, in the GPS location search step (S202), signals are searched to obtain the location from GPS satellites.

And the operation in the GPS location acquisition step (S203) is as follows.

If the IoT terminal is indoors or in a GPS shadow area, it cannot obtain its location through GPS satellites. If the location cannot be acquired during the GPS operation time due to this environment, the IoT terminal determines that it cannot receive GPS and turns GPS off.

Verification of whether GPS location has been acquired is determined through a message using the NMEA Protocol.

When acquiring a GPS location, location prediction data can be requested from the AI processing unit 220 in the location data request step (S213). More specifically, prediction data about the location of the IoT terminal can be requested from the AI processing unit 220. When requesting location prediction data, GPS speed, horizontal dilution of precision (HDOP), vertical dilution of precision (VDOP), and latitude/longitude values among NMEA (national marine electronics association) data can be transmitted to the AI processing unit 220.

At this time, the AI processing unit 220 may be referred to as a component disposed within the IoT terminal 200, but is not limited thereto and may be referred to as a separate server.

Next, response data may be received from the AI processing unit 220 in the response data confirmation step (S223). By checking the response data received from the AI processing unit 220 in the response data confirmation step (S223), the accuracy between the location prediction data and the GPS location can be determined.

At this time, if the accuracy between the location prediction data received from the AI processing unit 220 and the GPS location is greater than or equal to a predetermined threshold (e.g., 90%), the GPS device may be turned off.

On the other hand, if the accuracy between the location prediction data received from the AI processing unit 220 and the GPS location is less than a predetermined threshold (e.g., 90%), the location is continuously tracked until the location using the SBAS satellite is acquired.

Next, in the location acquisition step using SBAS (S204), if the location cannot be acquired using the SBAS satellite during the GPS operation time, the last tracked location is stored in memory.

When location information is acquired using the SBAS satellite, tracking is conducted for an additional period of time.

And in the constant time tracking step (S205), the location is tracked for a certain amount of time (seconds) to increase location accuracy.

Next, in the location information memory storage step (S206), the last piece of location information tracked according to the GPS collection cycle is stored in memory.

The location information collected at each GPS collection cycle is stored in memory.

Then, in the location information average value calculation step (S207), the location is corrected by adding up all the location information stored for each GPS collection cycle and dividing it by the number of times it has been stored (n) to calculate the average value.

Furthermore, in the NMEA data AI processing unit transmission step (S217), the corrected location and NMEA data can be transmitted to the AI processing unit 220. More specifically, by transmitting NMEA data according to the corrected GPS location information to the AI processing unit 220 in the NMEA data AI processing unit transmission step (S217), the algorithm model 330 of the AI processing unit 220 can be learned. . A detailed description of this will be provided later in Figure 3 below.

Next, in the GPS OFF step (S208), GPS is turned off to reduce IoT terminal current consumption.

Then, in the location information transmission step (S209), the corrected location data is transmitted to the operation server through a mobile communication network.

The equipment shutdown step (S210) is when the IoT terminal is terminated by the user or the IoT terminal enters sleep mode during the next GPS collection cycle.

Figure 3 is a flowchart showing the operation of the AI processing unit according to an embodiment of the present invention.

Specifically, the AI processing unit 220 performs a request type determination step (S301), a requirements inspection step (S302), a location information prediction step (S303), a prediction information verification step (S304), a judgment information transmission step (S305), and data classification. Including step S306, location prediction of the IoT terminal 200 may be performed.

First, in the request type determination step (S301), it is possible to determine whether the type of the received request is new data delivery or predicted data request.

If the type of request received in the request type determination step (S301) is a prediction data request, an operation to generate location prediction data may be performed.

First, it can be determined (or checked) whether the NMEA GPS information received in the requirements checking step (S302) meets pre-specified requirements. For example, it can be determined whether the GPS speed is 1 or less and the HDOP is 1 to 2 from the NMEA data received in the requirements check step (S302).

If the GPS information meets pre-specified requirements, an operation to generate location prediction data can be performed.

By inputting NMEA GPS information (e.g., latitude/longitude values, HDOP, VDOP) into the machine learning-based algorithm model 330 (or artificial neural network) in the location information prediction step (S303), the IoT terminal 200 location can be predicted.

More specifically, in the location information prediction step (S303), NMEA GPS information is applied to the algorithm model 330 trained through a plurality of algorithms 320 (e.g., KNN (k-nearest neighbor), Decision Tree, and Logistic Regression). You can generate location prediction data by entering it.

Next, in the prediction information verification step (S304), the prediction values output from the algorithm model 330 may be verified. More specifically, in the prediction information verification step (S304), the average of the prediction probability values for the values determined by each of the plurality of algorithms 320 of the algorithm model 330 is calculated through soft voting, and the An output value with a probability value can be determined as location prediction data.

Furthermore, in the determination information transmission step (S305), the accuracy of the location prediction data and the GPS location value can be determined, and the location prediction data and accuracy value can be transmitted to the satellite-based error correction system.

On the other hand, if the GPS information does not meet the pre-specified requirements, information that the delivered GPS information does not meet the pre-specified requirements can be transmitted to the satellite-based error correction system.

Meanwhile, if the type of request received in the request type determination step (S301) is new data delivery, an operation to increase location prediction accuracy can be performed by learning the algorithm model 330.

In the data classification step (S306), the received GPS information and NMEA data can be classified into data sets suitable for each of the plurality of algorithms (320).

Classified data can be used for learning each algorithm by being input into each algorithm (e.g. KNN, Decision Tree, Logistic Regression).

A plurality of algorithms 320 learned using classified data constitute an algorithm model 330, and the algorithm model 330 can be used to generate location prediction data in the location information prediction step (S303).

A position correction method using a satellite-based error correction system according to another embodiment of the present invention will be described as follows.

Figure 4 is a flowchart showing a position correction method using a satellite-based error correction system according to another embodiment of the present invention.

Referring to FIG. 4, location correction using SBAS can be performed according to Always GPS On of the present invention.

Specifically, the GPS ON step (S401), the GPS location search step (S402), the GPS location acquisition step (S403), the location prediction data request step (S413), the response data confirmation step (S423), and the location acquisition step using SBAS (S404). ), constant time tracking step (S405), location information memory storage step (S406), N location information storage step (S407), NMEA data AI processing unit 220 transmission step (S417), location information average value calculation step (S408) , Including the location information transmission step (S409), location correction is performed using SBAS according to Always GPS On.

First, in the GPS ON step (S301), the GPS function of the IoT terminal 200 is operated.

And in the GPS location search step (S302), signals are searched to obtain the location from GPS satellites.

Next, the operation in the GPS location acquisition step (S303) is as follows.

If the IoT terminal 200 is indoors or in a GPS shadow area, the location cannot be acquired through GPS satellites. If the location cannot be acquired during the GPS operating time due to this environment, the IoT terminal 200 determines that GPS reception is not possible and transmits information that the location cannot be confirmed to the server through the mobile communication network.

Verification of whether GPS location has been acquired is determined through a message using the NMEA Protocol.

When acquiring GPS location, In the location data request step (S413), location prediction data may be requested from the AI processing unit 220. More specifically, prediction data about the location of the IoT terminal can be requested from the AI processing unit 220. When requesting location prediction data, GPS speed, horizontal dilution of precision (HDOP), vertical dilution of precision (VDOP), and latitude/longitude values among NMEA (national marine electronics association) data can be transmitted to the AI processing unit 220.

Next, response data may be received from the AI processing unit 220 in the response data confirmation step (S423). By checking the response data received from the AI processing unit 220 in the response data confirmation step (S423), the accuracy between the location prediction data and the GPS location can be determined.

At this time, if the accuracy between the location prediction data received from the AI processing unit 220 and the GPS location is greater than or equal to a predetermined threshold (e.g., 90%), the GPS location may be transmitted to the operation server through a mobile communication network.

On the other hand, if the accuracy between the location prediction data received from the AI processing unit 220 and the GPS location is less than a predetermined threshold (e.g., 90%), the location is continuously tracked until the location using the SBAS satellite is acquired.

And in the location acquisition step using SBAS (S404), if the location cannot be acquired using the SBAS satellite, the location tracked until the end is stored in memory.

When location information is acquired using the SBAS satellite, it is tracked for an additional period of time.

Next, in the constant time tracking step (S405), the location is tracked for a certain amount of time (seconds) to increase location accuracy.

Then, in the location information memory storage step (S406), one piece of tracked location information is stored in memory.

And in the N location information storage step (S407), it is checked whether the stored location information is the set value n.

If the number of saves is not n, the location is tracked for the set time.

Next, in the location information average value calculation step (S408), when the number of storage times is n, the location is corrected by adding up all n pieces of stored location information and dividing by the number of storage times (n) to calculate the average value.

Furthermore, in the NMEA data AI processing unit transmission step (S417), the corrected location and NMEA data can be transmitted to the AI processing unit 220. More specifically, by transmitting NMEA data according to the corrected GPS location information to the AI processing unit 220 in the NMEA data AI processing unit transmission step (S417), the algorithm model 330 of the AI processing unit 220 can be learned. .

Then, in the location information transmission step (S409), the corrected location data is transmitted to the operation server through a mobile communication network.

The load balancing process according to the present invention will be described in detail as follows.

Figures 5a and 5b are configuration diagrams for explaining the load balancing process according to the present invention.

The reason for applying the load balancing process to the system and method for position correction using the satellite-based error correction system according to the present invention is as follows.

The goal is to maintain network coverage by applying load balancing to terminals in order not to exceed the number (n) of terminals that can be connected simultaneously according to the NB-IoT network (base station) coverage specifications.

The load balancing process may include the following components:

First, load balancing is applied based on the terminal sleep time.

Second, the load balancing application time is set within ±5% of the terminal sleep time.

For example, if the sleep time of the terminal is 1440 (24 hours) minutes, ±5% (72 minutes) of 1440 minutes is applied and the device is randomly measured within 1368 minutes to 1512 minutes and enters sleep mode for that amount of time. do.

Third, network overload is reduced by taking advantage of the different wake-up times for each terminal from sleep mode.

The terminal registration process according to the present invention will be described in detail as follows.

6 to 9 are detailed flowcharts of the terminal registration process according to the present invention.

Figure 6 shows the terminal network (base station) registration retry process.

(A1) The terminal performs network (base station) registration for data transmission. The terminal checks network registration using AT Command.

Here, AT Command is a command communication protocol used to check the status of each other in wireless communication.

The (B1) terminal waits for a response to (A1) from the network for n seconds. The network that receives the connection signal from the terminal sends a response to the terminal as to whether network access is possible.

There may be no network response due to terminal or network problems.

If (C1) network registration fails, the section (A1 ~ C1) is repeated n times. In (B1), if there is no response or network access is not possible, it is considered a network registration failure.

(D1) If network registration fails despite repeating the section (A1~C1) n times, the terminal communication module is reset. The reason for resetting the communication module is to prevent network registration failure due to a problem with the terminal's communication module, assuming that there is no network problem.

(E1) If network registration fails despite repeating the section (A1~D1) n times, it waits for n seconds and turns off the communication modem.

If network registration fails even after repeating the network registration attempt n times, due to the nature of the wireless terminal, for battery management purposes, the communication module is switched to the off state after waiting for n seconds, and after n seconds, the process is performed from step (A1) according to the process flow chart.

If network registration fails despite repeating the (F1) (A1~E1) section n times, the terminal enters sleep mode.

The condition for the terminal to enter sleep mode is that all processes have been completed normally, or, as in this case, if the normal process is not reached even after repeated attempts n times, it is determined that network connection is impossible and the terminal enters sleep mode for n seconds. . This is done at the battery management level.

FIG. 7 shows a terminal server registration retry process assuming that the initial terminal network registration process of FIG. 6 was completed normally.

(A2) The terminal performs network (base station) registration for data transmission.

(B2) Register the terminal to the server.

All terminals must have their information stored and registered on the server to enable normal data transmission/reception. Communication between the terminal and the server uses the Coap protocol, and when registering the terminal server, the terminal first transmits data to the server.

The (C2) terminal waits for a response to (B2) from the server for n seconds.

The server that receives the connection signal from the terminal sends a response to the terminal as to whether the server can be connected. There may be no server response due to a terminal, network, or server problem.

(D2) If terminal server registration fails, section (B2~D2) is repeated n times. In (C2), if there is no response even after repeating n times or the server cannot be connected, it is considered a terminal server registration failure.

(E2) If registration with the terminal server fails despite repeating the section (B2~D2) n times, the terminal communication module is reset.

The reason for resetting the communication module is to prevent server registration failure due to a problem with the terminal's communication module, assuming that there are no problems with the network and server.

If server registration fails despite repeating the section (F2) (B2~E2) n times, it waits for n seconds and turns off the communication module.

If the terminal server registration fails even after repeating the terminal server registration attempt n times, due to the nature of the wireless terminal, for battery management purposes, the communication module is switched to the off state after waiting for n seconds, and after n seconds, the process is performed according to the process flow chart starting from step (A2). .

If registration with the terminal server fails despite repeating the section (G2) (A2 ~ F2) n times, the terminal enters sleep mode.

The condition for the terminal to enter sleep mode is that all processes have been completed normally, or, as in this case, if the normal process is not reached even after n attempts, it is determined that connection to the server is impossible and the terminal enters sleep mode for n seconds. . This is done as a battery management measure.

FIG. 8 shows a remote command setting retry process performed under the assumption that the initial terminal network registration and terminal server registration processes of FIGS. 6 and 7 were completed normally.

(A3) The terminal performs network (base station) registration for data transmission.

(B3) Register the terminal to the server.

(C3) The server transmits the terminal command information set in the server to the terminal.

Values included in the command information include terminal transmission cycle, shock threshold, vibration collection cycle, and event mode off value.

Here, the terminal transmission period is the data transmission period setting of the terminal, the shock threshold is the upper limit setting of the shock threshold occurring in the terminal, and the vibration collection period is the time corresponding to n seconds for the terminal to collect and store vibration data every n seconds. Set the value.

In addition, event mode off causes the terminal to enter event mode when shock or detachment occurs, and the value is set so that it can return to normal mode when the user makes a mistake or enters unintentional event mode.

(D3) The terminal waits for a response to (C3) from the server for n seconds.

(E3) If receiving remote command setting information from the server fails, the section (C3~E3) is repeated n times. If remote command information is not received from (D3), remote command setup is considered a failure.

If there is a failure in the (F3) (E3) section, that is, the remote command setting fails, the terminal moves to part (D4) of the terminal status information transmission process of FIG. 8, the terminal status information confirmation process.

Figure 9 shows a terminal status information delivery retry process performed under the assumption that the initial terminal network registration, terminal server registration, and remote command setting processes were completed normally.

(A4) The terminal performs network (base station) registration procedures for data transmission.

(B4) Register the terminal to the server.

(C4) Transmits terminal command information set on the server.

(D4) Register (transmit) terminal status information data. The terminal transmits terminal status information data to the server.

Status information data includes terminal status data such as location (GPS/Cell ID) value, time, impact value, and detachment/attachment status.

(E4) The terminal waits for a response to (D4) from the server for n seconds. There may be no server response due to a terminal, network, or server problem.

(F4) If transmission of terminal status information fails, the section (D4~F4) is repeated n times. In (F4), if there is no response even after repeating n times or if terminal status information cannot be confirmed, the terminal status information confirmation procedure is considered a failure.

(G4) If transmission of terminal status information fails despite repeating the section (D4~F4) n times, the terminal communication module is reset.

The reason for resetting the communication module is to prevent terminal status information confirmation (transmission) failure due to a problem with the terminal's communication module, assuming that there are no problems with the network and server.

(H4) If checking the terminal status information fails despite n attempts, turn off the communication module for battery management, wait for n seconds, and then perform the process again from step (A4) according to the process flow chart.

(I4) If checking the terminal status information fails even after repeating the process n times (A4~F4), the terminal enters sleep mode for n seconds for battery management, and after n seconds, the process is performed according to the process flow chart starting from process (A4). do.

(J4) If checking the terminal status information fails despite repeating the section (A4~I4) n times, the terminal enters sleep mode.

The condition for the terminal to enter sleep mode is that the process has been completed normally, or, as in this case, if the normal process is not reached even after repeated attempts n times, due to the nature of the wireless terminal, the terminal enters sleep mode for n seconds for battery management. .

The system and method for position correction using the satellite-based error correction system according to the present invention described above enables the implementation of an IoT device for outdoor hybrid positioning using the SBAS (Satellite Based Augmentation System) function, and provides low-cost, low-power communication. It provides IoT terminals for LPWA-based asset management and outdoor positioning, and builds an asset control service platform that comprehensively collects and manages outdoor positioning and asset status information (impact, detachment, battery).

Meanwhile, computer-readable media includes all types of recording devices that store data that can be read by a computer system. Examples of computer-readable media include HDD (Hard Disk Drive), SSD (Solid State Disk), SDD (Silicon Disk Drive), ROM, RAM, CD-ROM, magnetic tape, floppy disk, optical data storage device, etc. There is.

Furthermore, the computer-readable medium may be a server or cloud storage that includes storage and can be accessed by electronic devices through communication. In this case, the computer can download the program according to the present invention from a server or cloud storage through wired or wireless communication.

Furthermore, in the present invention, the computer described above is an electronic device equipped with a processor, that is, a CPU (Central Processing Unit), and there is no particular limitation on its type.

Meanwhile, the above detailed description should not be construed as restrictive in all respects and should be considered illustrative. The scope of the present invention should be determined by reasonable interpretation of the appended claims, and all changes within the equivalent scope of the present invention are included in the scope of the present invention.

Claims (10)

In a satellite-based location information correction method,
Receiving GPS information using a GPS device;
In response to receiving the GPS information, requesting location prediction data from an AI processing unit;
Obtaining the location prediction data from the AI processing unit and determining location accuracy based on the location prediction data; and
If the location accuracy is less than the threshold, receiving satellite information from a satellite based augmentation system (SBAS) satellite, and correcting the GPS information using the satellite information, satellite-based location information. How to calibrate. According to paragraph 1,
The GPS information includes data based on specific standards,
The step of requesting the location prediction data from the AI processing unit further includes transmitting at least some of the data based on the specific standard to the AI processing unit. According to paragraph 2,
The AI processing unit includes an artificial neural network for generating the location prediction data,
The location prediction data is a satellite-based location information correction method, characterized in that at least some of the data is input to the artificial neural network and output from the artificial neural network. According to paragraph 3,
The artificial neural network is a satellite-based location information correction method, characterized in that it receives data included in GPS information and learns how to generate the location prediction data. According to paragraph 1,
Satellite-based location information correction method further comprising turning off power to the GPS device when the location accuracy is greater than a preset threshold. According to paragraph 1,
The step of correcting the GPS information using the satellite information is:
Acquiring a plurality of satellite information during a predetermined period of time,
A method for correcting satellite-based location information, further comprising correcting the GPS information based on the acquired plurality of satellite information. According to clause 6,
The GPS information is received according to a specified period through the GPS device,
A satellite-based location information correction method comprising correcting the GPS information based on an average value of the plurality of satellite information acquired according to the designated period during the predetermined time. According to paragraph 1,
The steps of receiving the GPS information using the GPS device are:
activating the GPS device,
searching for a GPS signal using the activated GPS device, and
In response to the GPS signal being searched, the satellite-based location information correction method further comprising receiving the GPS information from a GPS satellite. In a satellite-based location information correction system,
The control unit of the satellite-based location information correction system,
Receive GPS information using a GPS device,
In response to receiving the GPS information, request location prediction data from the AI processing unit,
Obtaining the location prediction data from the AI processing unit, determining location accuracy based on the location prediction data,
A satellite-based location information correction system that receives satellite information from a satellite based augmentation system (SBAS) satellite and corrects the GPS information using the satellite information when the location accuracy is less than the threshold value. A program that is executed by one or more processes in an electronic device and stored on a computer-readable recording medium,
The above program is,
Receiving GPS information using a GPS device;
In response to receiving the GPS information, requesting location prediction data from an AI processing unit;
Obtaining the location prediction data from the AI processing unit and determining location accuracy based on the location prediction data; and
If the location accuracy is less than the threshold value, a computer comprising instructions for receiving satellite information from a satellite based augmentation system (SBAS) satellite and correcting the GPS information using the satellite information. A program stored on a recording medium that can be read.