Railway station regulating equipment control method, system and device

Abstract

The present invention provides a method, system and device for controlling regulating equipment of a railway station, the method comprising: obtaining environmental information, passenger flow information and operating status information of regulating equipment of the railway station, and using them as business information; transmitting the business information to an edge computing processing unit through a 5G communication network; the edge computing processing unit processes the business information, predicts the environment and passenger flow based on the processed environmental information, passenger flow information and a pre-stored recurrent neural network algorithm, and sends the operating status information of the regulating equipment and the obtained prediction results to an application unit; the application unit generates an equipment adjustment instruction based on the operating status information and the prediction results of the regulating equipment, and the control unit controls the railway station equipment to execute the equipment adjustment instruction. The present invention can realize the deployment of the corresponding business of "environment-passenger flow-equipment" locally at the station and meet the intelligent equipment management of fast response and real-time service.

Description

Technical Field

[0001] The present invention relates to the field of railway operation technology, and in particular to a railway station regulating equipment control method and system. Background Art

[0002] At present, the business information of railway stations is mainly transmitted by traditional wired communication, that is, the station collects business data and transmits it to the railway bureau, and each railway bureau then transmits the business data of the station to the cloud platform deployed in the Wuqing main data center. After the cloud platform processes the business data, it generates operation instructions and sends the operation instructions to each station through each railway bureau. This business processing method not only has problems such as long data transmission cycle, large computing load of cloud platform, high deployment cost, large construction volume, and difficult operation and maintenance, but also to avoid overloading of the cloud platform, the cloud platform only processes the business data of important businesses, such as train arrival and departure plans, train adjustment plans, and water supply and sewage suction plans, etc. Non-important business data such as station environment, passenger flow and equipment operation status are usually directly stored in the computer room of each station and are not processed.

[0003] At present, the operation and adjustment equipment of the station, such as security scanners, air conditioners and lighting, are usually adjusted manually by station staff. However, this method not only has a certain lag, but also consumes a lot of human resources. Therefore, there is an urgent need for a method of intelligent management of station operation equipment with real-time service and rapid response, so as to automatically adjust the station equipment and improve the environmental comfort of the station. Summary of the invention

[0004] In view of this, an embodiment of the present invention provides a railway station regulating equipment control method and system, so as to feedback and process operational business information such as "environment-passenger flow-equipment" in real time and quickly at the station, reduce the computing load of the cloud platform and reduce the network transmission load of business data, and realize automatic regulation of railway station operating equipment.

[0005] One aspect of the present invention provides a railway station regulating equipment control method, the method comprising the following steps:

[0006] Using the 5G communication network, environmental information of different areas of the railway station is obtained from the environmental monitoring unit, passenger flow image information of different areas of the railway station is obtained from the passenger flow monitoring unit to obtain passenger flow information based on the passenger flow image information, and operating status information of the railway station regulation equipment is obtained from the equipment monitoring unit, and the business information is transmitted to the edge computing processing unit; wherein the business information includes: the obtained environmental information, passenger flow information and operating status information of the regulation equipment;

[0007] The edge computing processing unit processes the business information to obtain processed environmental information, processed passenger flow information, and processed operating status information of the regulating equipment, and predicts the environment and passenger flow of the railway station based on the processed environmental information, processed passenger flow information, and a pre-stored recurrent neural network algorithm, and sends the processed business information, the obtained environmental prediction results, and the passenger flow prediction results to the application unit;

[0008] The application unit generates a device adjustment instruction based on the environmental prediction result, the passenger flow prediction result and the processed operation status information of the adjustment device, and sends the device adjustment instruction to the control unit of the railway station;

[0009] The control unit controls the railway station regulation equipment to execute equipment regulation instructions.

[0010] In some embodiments of the present invention, the method further includes: the device monitoring unit feeds back the execution result of the device adjustment instruction by the adjustment device to the application unit, and updates the operation status information of the adjustment device of the device monitoring unit.

[0011] In some embodiments of the present invention, using a 5G communication network, environmental information of different areas of a railway station is obtained from an environmental monitoring unit, passenger flow image information of different areas of the railway station is obtained from a passenger flow monitoring unit to obtain passenger flow information based on the passenger flow image information, and operating status information of a railway station adjustment device is obtained from an equipment monitoring unit, and business information is transmitted to an edge computing processing unit, including:

[0012] The 5G communication module is used to obtain environmental information, passenger flow information and equipment operation status information from the environmental monitoring unit, passenger flow monitoring unit and equipment monitoring unit respectively, and the collected environmental information, passenger flow information and equipment operation status information are used as business information, and the business information is transmitted to the edge computing processing unit through the 5G customer front-end equipment and the 5G access network;

[0013] The edge computing processing unit is connected to the 5G access network and 5G core network respectively through optical cables.

[0014] In some embodiments of the present invention, the method also includes: the cloud platform regularly obtains updated recurrent neural network algorithms from the Internet through the 5G core network, and pushes the obtained algorithms to the edge computing processing unit, thereby pre-storing the recurrent neural network algorithms; wherein the Internet and the 5G core network are connected via wired communication; the cloud platform is respectively connected to the edge computing processing unit and the 5G core network via wired communication.

[0015] In some embodiments of the present invention, the edge computing processing unit obtains processed environmental information, processed passenger flow information, and processed operating status information of the regulating device by processing the business information, including:

[0016] The edge computing processing unit stores the business information, and the edge computing processing unit processes the stored business information to obtain processed environmental information, processed passenger flow information, and processed operating status information of the regulating device;

[0017] The edge computing processing unit processes the stored business information, including: supplementing missing business information based on mean filling, replacing abnormal business information based on weighted average, and directly deleting duplicate business information.

[0018] In some embodiments of the present invention, the environmental information includes one or more of the following indicators: temperature, humidity, brightness, noise, PM 2.5 、PM 10 and CO2;

[0019] Passenger flow information includes one or more of the following indicators: passenger flow density and passenger flow thermal image; wherein passenger flow density includes: passenger flow density entering and leaving the station and passenger flow density in different areas within the station;

[0020] The regulating equipment includes one or more of the following equipment: entry and exit gates, station air conditioners, station lighting equipment, guide screens and station broadcasts, and the operating status information of the regulating equipment includes: equipment operating values ​​and working status.

[0021] In some embodiments of the present invention, the application unit generates a device adjustment instruction based on the environment prediction result, the passenger flow prediction result and the processed operation status information of the adjustment device, including:

[0022] Based on the predicted results of temperature, humidity and passenger flow density in different areas of the station and the operating value of the station air conditioner, an adjustment instruction for the operating value of the station air conditioner is generated; the predicted values ​​of temperature, humidity and passenger flow density in different areas of the station are negatively correlated with the operating value of the station air conditioner after adjustment;

[0023] Based on PM 2.5 、PM 10 The prediction results of CO2 and the operating values ​​of the station ventilation equipment are used to generate adjustment instructions for the operating values ​​of the station ventilation equipment; PM 2.5 、PM 10 The predicted value of CO2 is positively correlated with the operating value after the station ventilation equipment;

[0024] Based on the brightness prediction results and the brightness values ​​of the station lighting equipment and the guide screen, an adjustment instruction for the brightness values ​​of the station lighting equipment and the guide screen is generated; the brightness prediction value is negatively correlated with the adjusted brightness value of the station lighting equipment and the adjusted brightness value of the guide screen;

[0025] Based on the prediction results of noise and passenger flow density in different areas of the station and the volume of the station broadcast, an adjustment instruction for the volume of the station broadcast is generated; the predicted value of noise, the predicted value of passenger flow density in different areas of the station and the adjusted volume of the station broadcast are positively correlated;

[0026] Based on the predicted results of the passenger flow density entering and exiting the station and the number of opening gates of the station, an adjustment instruction for the number of opening gates of the station is generated; the predicted value of the passenger flow density entering and exiting the station is positively correlated with the number of opening gates of the station after adjustment;

[0027] The application unit pre-stores the normal operating range of the equipment operating values ​​of each regulating equipment in the railway station, and generates an equipment adjustment instruction for the equipment if the operating value of the regulating equipment exceeds the normal operating range;

[0028] In the case of generating equipment adjustment instructions based on the prediction results of multiple indicators, weights are assigned to the prediction results of each indicator according to the real-time needs of the railway station and the total prediction result is obtained. The equipment adjustment instructions of the equipment are generated by comparing the total prediction result with the prediction threshold.

[0029] Another aspect of the present invention provides a railway station equipment control system, which includes a processor and a memory, wherein the memory stores computer instructions, and the processor is used to execute the computer instructions stored in the memory. When the computer instructions are executed by the processor, the system implements the steps of the method described in any of the above embodiments.

[0030] Another aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the method described in any of the above embodiments when the program is executed by a processor.

[0031] Another aspect of the present invention provides a railway station equipment control device, the device comprising:

[0032] The sensing unit includes an environment monitoring unit, a passenger flow monitoring unit and an equipment monitoring unit, which are used to collect environmental information, passenger flow information and operating status information of the regulating equipment at the railway station;

[0033] The communication unit includes a 5G communication network, which is used to collect business information and transmit it to the processing unit; wherein the 5G communication network includes: a 5G communication module, a 5G customer front-end device, a 5G access network and a 5G core network; the 5G communication module is mounted on the perception unit;

[0034] Processing units, including edge computing processing units, are used to store and process business information and predict environmental information and passenger flow information of railway stations;

[0035] An application unit generates an equipment adjustment instruction based on the environmental prediction result, the passenger flow prediction result and the processed operation status information of the adjustment equipment, and sends the equipment adjustment instruction to a control unit of a railway station;

[0036] The control unit is used to control the railway station regulation equipment to execute equipment regulation instructions and feed back the execution results to the application unit.

[0037] The railway station regulating equipment control method and system provided by the present invention can realize real-time feedback of operating environment monitoring services such as "environment-passenger flow-equipment" at the local station through fast and reliable 5G Internet of Things perception and transmission means, combined with real-time and intelligent local edge computing processing technology, greatly improving the response speed and efficiency of station operating services, reducing the network transmission load of business data, and meeting the basic needs of the business in terms of real-time, rapidity, convenience and security.

[0038] Additional advantages, purposes, and features of the present invention will be described in part in the following description, and will become apparent to those skilled in the art after studying the following, or may be learned from the practice of the present invention. The purposes and other advantages of the present invention may be achieved and obtained by the structures specifically indicated in the specification and the accompanying drawings.

[0039] Those skilled in the art will appreciate that the objectives and advantages that can be achieved with the present invention are not limited to the above specific description, and the above and other objectives that can be achieved by the present invention will be more clearly understood from the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The drawings described herein are used to provide a further understanding of the present invention, constitute a part of the present application, and do not constitute a limitation of the present invention. In the drawings:

[0041] Figure 1 The figure is a flow chart of a method for controlling railway station regulating equipment in one embodiment of the present invention.

[0042] Figure 2 It is a schematic diagram of the specific process of the railway station regulating equipment control method in one embodiment of the present invention.

[0043] Figure 3 Schematic diagram of the architecture of a railway station equipment control device in one embodiment of the present invention. DETAILED DESCRIPTION

[0044] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the embodiments and the accompanying drawings. Here, the illustrative embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0045] It should also be noted that, in order to avoid obscuring the present invention due to unnecessary details, only structures and / or processing steps closely related to the solutions according to the present invention are shown in the accompanying drawings, while other details that are not closely related to the present invention are omitted.

[0046] It should be emphasized that the term “include / comprises” when used herein refers to the presence of features, elements, steps or components, but does not exclude the presence or addition of one or more other features, elements, steps or components.

[0047] It should also be noted that, unless otherwise specified, the term “connection” herein may refer not only to a direct connection but also to an indirect connection involving an intermediate.

[0048] Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. In the accompanying drawings, the same reference numerals represent the same or similar components, or the same or similar steps.

[0049] For services such as station environment monitoring, passenger flow monitoring and regulating equipment monitoring, wired communication is still used to transmit business data. There are problems such as long data transmission cycle, large computing load of cloud platform, high deployment cost, large construction volume, and difficult operation and maintenance. In addition, in the existing technology, these business data are directly stored in each station, and the cloud platform does not process them in any way. Therefore, the regulating equipment is manually adjusted by station staff, which not only has a lag but also consumes manpower.

[0050] Mobile Edge Computing (MEC) is a technology that aims to migrate cloud platforms from the mobile core network to the edge of the mobile access network to achieve flexible use of computing and storage resources. Edge computing provides cloud services and IT environment services to application developers and service providers at the edge of the network; the goal is to provide computing, storage and network bandwidth close to data input or users.

[0051] Based on this, an embodiment of the present invention provides a method for controlling regulating equipment in a railway station, which uses 5G communication and mobile edge computing to realize the deployment of corresponding operational business information and services of the station's "environment-passenger flow-equipment" locally in the station, breaking the centralized deployment mode of the cloud platform center for railway operational business. It can realize the real-time and secure transmission of "environment-passenger flow-equipment" monitoring data and control instructions, meet the needs of local autonomy, real-time service, and rapid response of station business, and reduce data transmission costs and the load pressure of the cloud platform.

[0052] Figure 1 FIG. 1 is a flow chart of a method for controlling a railway station regulating device according to an embodiment of the present invention. Figure 1 The method shown may specifically include steps S110 to S140.

[0053] Step S110: Utilize the 5G communication network to obtain environmental information of different areas of the railway station from the environmental monitoring unit, obtain passenger flow image information of different areas of the railway station from the passenger flow monitoring unit to obtain passenger flow information based on the passenger flow image information, obtain the operating status information of the railway station regulating equipment from the equipment monitoring unit, and transmit the business information to the edge computing processing unit; wherein the business information includes: the obtained environmental information, passenger flow information and operating status information of the regulating equipment.

[0054] In some embodiments of the present invention, the environmental information includes one or more of the following indicators: temperature, humidity, brightness, noise, PM 2.5 、PM 10 and CO2;

[0055] Passenger flow information includes one or more of the following indicators: passenger flow density and passenger flow thermal image; wherein passenger flow density includes: passenger flow density entering and leaving the station and passenger flow density in different areas within the station;

[0056] The regulating equipment includes one or more of the following equipment: entry and exit gates, station air conditioners, station lighting equipment, guide screens and station broadcasts, and the operating status information of the regulating equipment includes: equipment operating values ​​and working status.

[0057] More specifically, the environment monitoring unit obtains the environment information of different areas in the railway station through the environment monitoring sensors; the passenger flow monitoring unit obtains the passenger flow image information of different areas through the passenger flow monitoring equipment in the railway station, and analyzes the passenger flow image information based on the crowd counting algorithm, so as to obtain the passenger flow information of different areas; the regulating equipment monitoring unit can obtain the current operating value of the station regulating equipment and whether it is operating in a normal state.

[0058] The environmental monitoring unit is an environmental monitoring sensor, including: temperature sensor, humidity sensor, brightness sensor, noise sensor, PM 2.5 Sensors, PM 10 Sensors and CO2 sensors, etc. Environmental sensors can regularly collect temperature, humidity, brightness, noise, PM 2.5 、、PM 10 and CO2 and other environmental information. Multiple environmental monitoring sensors of the same type can be deployed in the same area of ​​the station, and all types of environmental monitoring sensors should be deployed in all areas of the station.

[0059] The passenger flow monitoring unit is a passenger flow monitoring device, including: infrared cameras, gun cameras, spherical cameras, hemispherical cameras, network high-definition cameras and other types of monitoring cameras. Based on the monitoring images and crowd counting algorithms obtained by the passenger flow monitoring equipment, the passenger flow density in different areas of the station (including the passenger flow density in and out of the station and the passenger flow density in different areas of the station) and thermal maps and other image information can be obtained. Among them, the passenger flow thermal image can be obtained from the infrared camera equipment of the station.

[0060] The regulating equipment monitoring unit is deployed inside the regulating equipment, and the regulating equipment includes entry and exit gates, station air conditioners, ventilation equipment, station lighting equipment, guide screens, security scanners and station broadcasts, etc.

[0061] As an example, the device operation value in the device operation status information refers to the current operation value of the regulating device, such as the degree of the air conditioner in the current station and the volume of the station broadcast.

[0062] As an example, whether the station regulating device is in normal operation can be represented by 0-1, 0 means the regulating device is in abnormal state, 1 means the device is in normal state. The working state and the device operation value can be obtained by the device monitoring unit at the same time.

[0063] The use of a crowd counting algorithm to analyze passenger flow image information mentioned in the present invention is only an example, and the present invention is not limited thereto. Other algorithms may also be used to analyze passenger flow image information, such as a station passenger number detection model based on the Faster-RCNN algorithm.

[0064] The environmental information, passenger flow information, and equipment operation status information of the regulating equipment mentioned in the present invention are only examples, but the present invention is not limited thereto, and other monitoring indicators may also be used.

[0065] In some embodiments of the present invention, using a 5G communication network, environmental information of different areas of a railway station is obtained from an environmental monitoring unit, passenger flow image information of different areas of the railway station is obtained from a passenger flow monitoring unit to obtain passenger flow information based on the passenger flow image information, and operating status information of a railway station adjustment device is obtained from an equipment monitoring unit, and business information is transmitted to an edge computing processing unit, including:

[0066] The 5G communication module is used to obtain environmental information, passenger flow information and equipment operation status information from the environmental monitoring unit, passenger flow monitoring unit and equipment monitoring unit respectively, and the collected environmental information, passenger flow information and equipment operation status information are used as business information, and the business information is transmitted to the edge computing processing unit through the 5G customer front-end equipment and the 5G access network;

[0067] The edge computing processing unit is deployed at the edge of the 5G access network; the edge computing processing unit is connected to the 5G access network and the 5G core network respectively through optical cables.

[0068] The 5G communication network includes: 5G communication module, 5G customer premise equipment (CPE), 5G access network and 5G core network;

[0069] The 5G communication module and CPE are connected through wireless communication, the CPE and 5G access network are connected through wireless communication or cables, and the 5G access network and 5G core network are connected through optical cables.

[0070] Furthermore, the 5G access network acts as a "window" that can access data to the 5G network, and the 5G core network acts as a "management hub" that can manage and sort data.

[0071] More specifically, the 5G communication module collects environmental information, passenger flow information, and equipment operating status information, gathers this information on the CPE through wireless communication, and sends this business information to the edge computing processing unit through optical cable transmission after passing through the 5G access network. Among them, environmental monitoring sensors, passenger flow monitoring equipment, and adjustment equipment are all equipped with 5G communication modules (i.e., 5G communication modules).

[0072] Step S120: The edge computing processing unit processes the business information to obtain processed environmental information, processed passenger flow information and processed operating status information of the regulating equipment, and predicts the environment and passenger flow of the railway station based on the processed environmental information, processed passenger flow information and a pre-stored recurrent neural network algorithm, and sends the processed business information, the obtained environmental prediction results and the passenger flow prediction results to the application unit.

[0073] More specifically, the cloud platform's application for monitoring "environment-passenger flow-equipment" business information is moved down to the edge computing processing unit, where the environment information, passenger flow information, and equipment operation status information are stored, and the stored business information is processed. The station environment is quickly predicted using the processed environment information and the pre-stored recurrent neural network algorithm, and the station passenger flow is quickly predicted using the processed passenger flow information and the pre-stored recurrent neural network algorithm. The prediction results of the environment, the prediction results of the passenger flow, the processed environment information, the processed passenger flow information, and the processed equipment operation status information are sent to the application unit. Among them, the edge computing processing unit is deployed in the local edge computing server of the railway station.

[0074] Furthermore, the pre-stored recurrent neural network algorithm is pushed from the cloud center to the edge computing processing unit and stored in the local edge computing server. The recurrent neural network algorithm is used to predict the station environment and passenger flow information. The prediction time interval can be one hour, one day or two days, etc., and the time interval can be set by the station staff.

[0075] In some embodiments of the present invention, the edge computing processing unit obtains processed environmental information, processed passenger flow information, and processed operating status information of the regulating device by processing the business information, including:

[0076] The edge computing processing unit stores the business information, and the edge computing processing unit processes the stored business information to obtain processed environmental information, processed passenger flow information, and processed operating status information of the regulating device;

[0077] The edge computing processing unit processes the stored business information, including: supplementing missing business information based on mean filling, replacing abnormal business information based on weighted average, and directly deleting duplicate business information.

[0078] Furthermore, data processing usually includes data cleaning and data filtering. The processed business information not only reduces the occupation of server resources, but also increases the accuracy of prediction results and improves the operating efficiency of edge computing. In the case of missing business information, the missing data information is usually supplemented by deleting missing values ​​or using mean filling method; in the case of outliers in business information (that is, individual mutations in samples with slow changes), it is usually processed by deleting or replacing outliers, and the weighted average method can be used to replace outliers; in the case of repeated redundancy in business information, it is usually processed by directly deleting redundant information or weighted average method.

[0079] As an example, if business information is missing, the average value of the information near the missing value can be selected as the missing information to supplement the missing position; if the business information is abnormal, the weighted average value of the information near the abnormal value can be selected as normal information to replace the abnormal value; if the business information is repeated, the repeated data information can be directly deleted.

[0080] The processing methods for business information missing, business information abnormality and business information redundancy mentioned in the present invention are only examples, and the present invention is not limited thereto, and other methods can also be used to process the business information.

[0081] Step S130: The application unit generates an equipment adjustment instruction based on the environmental prediction result, the passenger flow prediction result and the processed operating status information of the adjustment equipment, and sends the equipment adjustment instruction to the control unit of the railway station.

[0082] More specifically, the application unit can visualize the processed environmental information, passenger flow information and equipment operation status information, and convert the environmental prediction results and passenger flow prediction results into a time-development trend curve. Based on the prediction results of the environment and passenger flow and the current equipment operation status, the adjustment instructions for the operating equipment are generated, and the equipment adjustment instructions are sent to railway station equipment such as air conditioners, entry and exit gates, guide screens, lighting and broadcasting, so that the control unit controls the corresponding railway station equipment to execute the instructions.

[0083] The application unit is deployed in the local edge computing server of the railway station. The control unit is used to receive the equipment adjustment instructions issued by the application unit and control the corresponding equipment to execute the instructions. In addition, the control unit is deployed in station adjustment equipment such as air conditioning, lighting, guide screens, broadcasting, and entry and exit gates.

[0084] The application unit can visually display the processed business information, environmental prediction results and passenger flow prediction results, and generate equipment adjustment instructions.

[0085] In some embodiments of the present invention, the application unit generates a device adjustment instruction based on the environment prediction result, the passenger flow prediction result and the processed operation status information of the adjustment device, including:

[0086] Based on the predicted results of temperature, humidity and passenger flow density in different areas of the station and the operating value of the station air conditioner, an adjustment instruction for the operating value of the station air conditioner is generated; the predicted values ​​of temperature, humidity and passenger flow density in different areas of the station are negatively correlated with the operating value of the station air conditioner after adjustment;

[0087] Based on PM 2.5 、PM 10 The prediction results of CO2 and the operating values ​​of the station ventilation equipment are used to generate adjustment instructions for the operating values ​​of the station ventilation equipment; PM 2.5 、PM 10 The predicted value of CO2 is positively correlated with the operating value after the station ventilation equipment;

[0088] Based on the brightness prediction results and the brightness values ​​of the station lighting equipment and the guide screen, an adjustment instruction for the brightness values ​​of the station lighting equipment and the guide screen is generated; the brightness prediction value is negatively correlated with the adjusted brightness value of the station lighting equipment and the adjusted brightness value of the guide screen;

[0089] Based on the prediction results of noise and passenger flow density in different areas of the station and the volume of the station broadcast, an adjustment instruction for the volume of the station broadcast is generated; the predicted value of noise, the predicted value of passenger flow density in different areas of the station and the adjusted volume of the station broadcast are positively correlated;

[0090] Based on the predicted results of the passenger flow density entering and exiting the station and the number of opening gates entering and exiting the station, an adjustment instruction for the number of opening gates entering and exiting the station is generated; the predicted value of the passenger flow density entering and exiting the station is positively correlated with the number of opening gates after adjustment;

[0091] The application unit pre-stores the normal operating range of the equipment operating values ​​of each regulating equipment in the railway station, and generates an equipment adjustment instruction for the equipment if the operating value of the regulating equipment exceeds the normal operating range;

[0092] In the case of generating equipment adjustment instructions based on the prediction results of multiple indicators, weights are assigned to the prediction results of each indicator according to the real-time needs of the railway station and the total prediction result is obtained. The equipment adjustment instructions of the equipment are generated by comparing the total prediction result with the prediction threshold.

[0093] Furthermore, if it is known from the prediction results that the temperature in the station will rise, the humidity will increase, and the passenger flow density in the inner area of ​​the station will increase within the predetermined time, then an equipment adjustment instruction for the station air conditioner to reduce the temperature and humidity is generated;

[0094] If the forecast results show that PM 2.5 、PM 10 The concentration of CO2 will increase, and the ventilation equipment will generate equipment adjustment instructions to strengthen ventilation;

[0095] If it is known from the prediction results that the brightness in the station will increase within the predetermined time (for example, when it changes from night to day), then an equipment adjustment instruction is generated to reduce the brightness value of the station lighting equipment and the guide screen; the brightness is related to natural laws such as day and night and the four seasons, and the guide screen has energy saving as its main goal;

[0096] If it is known from the prediction results that the noise will increase and the passenger flow density in different areas of the station will increase within the predetermined time, an equipment adjustment instruction to increase the volume of the station broadcast is generated;

[0097] If it is known from the prediction results that the passenger flow density in and out of the station will increase within the scheduled time, an equipment adjustment instruction is generated to increase the number of in and out gates to be opened.

[0098] Equipment adjustment instructions include: adjusting the air-conditioning temperature, ventilation equipment, lighting switches in different areas of the control station, lighting brightness, guide screen brightness, volume of broadcasts in different areas and the number of entry and exit gates working within a predetermined time. The equipment can be controlled by directly generating instructions for adjusted operating values ​​(for example, directly generating instructions: the air-conditioning temperature drops to 25°C after one hour) or instructions for equipment adjustment values ​​(for example, generating instructions for adjustment values: lowering the air-conditioning temperature by 5°C after one hour).

[0099] As an example, the application unit stores the normal operating range of each device (for example, the normal operating range of the air conditioner is 20-30°C). If the operating value of the adjusted device exceeds the normal operating range (for example, the current air conditioner temperature is 18°C), it is regarded as an abnormal state and marked as "0". If the device is in an abnormal state, the application unit generates a device adjustment instruction based on the current operating value (18°C) and the target operating value (assuming it is set to 25°C), and adjusts the device within a predetermined time (for example, raising the air conditioner temperature to 25°C within 10 minutes).

[0100] As an example, the application unit stores the normal range of environmental information and passenger flow information (for example, the room temperature needs to be maintained at 25°C). Assuming that it is predicted that the ambient temperature will rise to 28°C in one hour and the current air-conditioning temperature is 26°C, a device adjustment instruction of "the air-conditioning temperature will drop to 24°C after one hour" can be generated based on a recurrent neural network algorithm.

[0101] As an example, for the case where a device adjustment instruction is generated based on the prediction results of multiple indicators (such as based on PM 2.5 、PM 10 The prediction results of CO2 and the operating values ​​of the station ventilation equipment are used to generate adjustment instructions for the operating values ​​of the station ventilation equipment. The total prediction result (for example, PM 2.5 The value is 10, the weight is 0.5; PM 10 The value of is 6, the weight is 0.3; the value of CO2 is 1, the weight is 0.2; the total prediction result is 7), and by comparing the total prediction result with the prediction threshold (assuming it is set to 5), an equipment adjustment instruction for strengthening the ventilation equipment is generated.

[0102] Furthermore, when generating equipment adjustment instructions for station air conditioning and station broadcasting, the passenger flow density in different areas of the station may not be considered, that is, the weight of the passenger flow density in different areas of the station is 0, as shown below:

[0103] Based on the predicted results of temperature and humidity and the operating values ​​of the station air conditioner, an adjustment instruction for the operating value of the station air conditioner is generated; the predicted values ​​of temperature and humidity are negatively correlated with the operating values ​​of the station air conditioner after adjustment;

[0104] Based on the noise prediction result and the volume of the station broadcast, an adjustment instruction for the volume of the station broadcast is generated; the noise prediction value is positively correlated with the adjusted volume of the station broadcast.

[0105] Specifically, the ventilation equipment may include: a fresh air system, an air purifier, etc. Similarly, the ventilation function of the air conditioner can replace the ventilation equipment, and the opening and closing control of the station windows can also be used as a ventilation device to adjust the air quality of the station.

[0106] As an example, when generating equipment adjustment instructions for station air conditioners, the temperature, humidity, PM 2.5 、PM 10 and the prediction result of CO2 and the operating value of the station air conditioner, generating an adjustment instruction for the operating value of the station air conditioner; or

[0107] Based on temperature, humidity, PM 2.5 、PM 10 The prediction results of CO2 and passenger flow density in different areas inside the station and the operating values ​​of the station air conditioner are used to generate adjustment instructions for the operating values ​​of the station air conditioner.

[0108] As an example, the security scanner can realize background linkage control with the entrance and exit gates: when the number of entrance and exit gates opened increases, the number of security scanners opened increases; when the number of entrance and exit gates opened decreases, the number of security scanners opened decreases. Or based on the predicted results of the passenger flow density of inbound and outbound stations and the number of security scanners opened, an adjustment instruction for the number of security scanners opened is generated, and the predicted value of the passenger flow density of inbound and outbound stations is positively correlated with the number of security scanners opened after adjustment.

[0109] Step S140: The control unit controls the railway station adjustment equipment to execute the equipment adjustment instruction.

[0110] In some embodiments of the present invention, after step S140, step S150 is further included: the device monitoring unit feeds back the execution result of the device adjustment instruction by the adjustment device to the application unit, and updates the operation status information of the adjustment device in the device monitoring unit.

[0111] More specifically, after the regulating device monitoring unit detects that the regulating device has completed the device regulating instruction issued by the application unit, it feeds back the instruction execution result to the application unit in real time and updates the device operation value and its working status.

[0112] The control unit can send the execution result of the control regulating device executing the device adjustment instruction (such as "execution successful" or "execution failed") to the application unit; and the equipment monitoring unit can send the execution result of the regulating device after executing the device adjustment instruction (for example, the air conditioning temperature is reduced to 25°C) to the application unit.

[0113] In some embodiments of the present invention, step S160 is also included: the cloud platform regularly obtains updated recurrent neural network algorithms from the Internet through the 5G core network, and pushes the obtained algorithms to the edge computing processing unit; wherein the Internet and the 5G core network are connected via wired communication; the cloud platform is respectively connected to the edge computing processing unit and the 5G core network via wired communication.

[0114] More specifically, the cloud platform pushes the data training models and intelligent algorithms obtained from the Internet to the station edge computing processing unit, which stores the above models and algorithms, enabling the station to complete rapid data processing of "environment-passenger flow-equipment" business information at the edge, and predict the development trends of environmental information and passenger flow information.

[0115] The data training model and intelligent algorithm pushed above may be a recurrent neural network model and algorithm, or may be an algorithm of other categories.

[0116] As an example, predicting station environmental information includes: using historical data collected by environmental sensors within 2 days (sampling frequency is 5 minutes / time) as a sample data set, and using an improved neural network model algorithm, such as a combined model of a long short-term memory neural network (Long Short-Term Memory, LSTM) and a gradient boosting algorithm (Light GradientBoosting Machine, LightGBM), to predict the development trend of environmental data over time.

[0117] The prediction of station passenger flow information includes: taking the actual passenger flow of the station throughout the whole year last year (the frequency of collecting passenger flow is 30 minutes / time) as a sample data set, and using neural network model algorithms, such as recurrent neural network (RNN), gated recurrent unit neural network (GRU) or LSTM algorithm, to predict the development trend of the number of passengers entering the station over time.

[0118] As an example, supplementing missing business information includes: if the proportion of samples with missing values ​​in the overall sample is relatively small, then directly delete the samples with missing values; mean filling method refers to selecting several groups of samples near the missing value and calculating the average value, and filling the missing sample with the average value. Correcting abnormal business information includes: if the sample data volume is large and there are few abnormal values, then directly delete the abnormal value; if there are many abnormal values ​​in the sample, then replace the abnormal value by the average value or median of the data samples near the abnormal value. Deleting duplicate business information includes: because the sensor collects environmental information frequently, usually at intervals of a few minutes, the collected environmental information does not change much within a certain time range, resulting in a large amount of duplicate data. For a large amount of duplicate data, any data sample can be selected and other duplicate data can be directly filtered out; the weighted average method is a method of calculating the average value by weighted averaging a set of redundant data.

[0119] In a specific embodiment, Figure 2The following is a schematic diagram of the specific process of the railway station regulation equipment control method. Figure 2 As shown, the specific process includes the following:

[0120] (1) Obtaining environmental information of the railway station from the environmental monitoring unit, obtaining passenger flow information of the railway station from the passenger flow monitoring unit, and obtaining equipment operation status information of the railway station from the equipment monitoring unit.

[0121] (2) The 5G customer front-end equipment collects the above-mentioned environmental information, passenger flow information and equipment operation status information as business information, and transmits the business information to the edge computing processing unit through the 5G access network.

[0122] (3) The edge computing processing unit sends the processed equipment operation status information and the obtained prediction results to the application unit.

[0123] (4) The application unit generates an equipment adjustment instruction and sends it to the control unit, and the control unit controls the station adjustment device to execute the equipment adjustment instruction.

[0124] In addition, the process also includes: the cloud platform and the Internet are connected through the 5G core network, and algorithms and models are regularly pushed to the edge computing processing unit. The 5G core network is connected to the 5G access network and the edge computing processing unit respectively.

[0125] The above technical solution of the railway station regulating equipment control method proposed by the present invention has the following advantages:

[0126] 1. 5G wireless communication technology has the advantages of high speed, low latency, wide connection, high reliability, and support for high-speed mobility. It has broad prospects for application in the construction of smart station informationization. It can not only meet the basic needs of business in terms of real-time, rapidity, convenience and security, but also complete the 5G transmission of the station with the help of the existing operator network. At the same time, compared with the current wired communication of the station, wireless communication also provides many conveniences in information transmission and equipment addition and removal.

[0127] 2. Deploy edge computing services locally at the station and sink the cloud platform's operation monitoring business applications to the edge side, so as to realize reliable, stable, and high-speed transmission of operation environment monitoring business information such as "environment-passenger flow-equipment" of smart stations and real-time, fast, and intelligent local edge processing, which is conducive to improving the level of intelligent station management.

[0128] 3. 5G has the characteristics of low power consumption, low latency, security and reliability. Combined with the characteristics of distributed, low latency, low cost and high efficiency of edge computing, it has greatly solved the bottleneck problems of deployment and implementation of railway station operation monitoring equipment and data transmission. It can support the deployment of corresponding "environment-passenger flow-equipment" operation business and services at the local station, meet the needs of local autonomy and real-time services of station business, and reduce the load pressure and data transmission cost of the cloud platform.

[0129] The present invention also provides a railway station equipment control system, which includes a computer device, the computer device includes a processor and a memory, the memory stores computer instructions, the processor is used to execute the computer instructions stored in the memory, and when the computer instructions are executed by the processor, the system implements the steps of the method described above.

[0130] The embodiment of the present invention also provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the steps of the aforementioned edge computing server deployment method are implemented. The computer-readable storage medium can be a tangible storage medium, such as a random access memory (RAM), a memory, a read-only memory (ROM), an electrically programmable ROM, an electrically erasable programmable ROM, a register, a floppy disk, a hard disk, a removable storage disk, a CD-ROM, or any other form of storage medium known in the technical field.

[0131] Corresponding to the above method, the present invention also provides a railway station equipment control device, the structure diagram of the device is as follows Figure 3 As shown, the device comprises:

[0132] The sensing unit includes an environment monitoring unit, a passenger flow monitoring unit and an equipment monitoring unit, which are used to collect environmental information, passenger flow information and operating status information of the regulating equipment at the railway station;

[0133] The communication unit includes a 5G communication network, which is used to collect business information and transmit it to the processing unit; wherein the 5G communication network includes: a 5G communication module, a 5G customer front-end device, a 5G access network and a 5G core network; the 5G communication module is mounted on the perception unit;

[0134] Processing units, including edge computing processing units, are used to store and process business information and predict environmental information and passenger flow information of railway stations;

[0135] An application unit generates an equipment adjustment instruction based on the environmental prediction result, the passenger flow prediction result and the processed operation status information of the adjustment equipment, and sends the equipment adjustment instruction to a control unit of a railway station;

[0136] The control unit is used to control the railway station regulation equipment to execute equipment regulation instructions and feed back the execution results to the application unit.

[0137] It should be understood by those skilled in the art that the exemplary components, systems and methods described in conjunction with the embodiments disclosed herein can be implemented in hardware, software or a combination of the two. Whether it is performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention. When implemented in hardware, it can be, for example, an electronic circuit, an application specific integrated circuit (ASIC), appropriate firmware, a plug-in, a function card, etc. When implemented in software, the elements of the present invention are programs or code segments used to perform the required tasks. The program or code segment can be stored in a machine-readable medium, or transmitted on a transmission medium or a communication link via a data signal carried in a carrier.

[0138] It should be clear that the present invention is not limited to the specific configuration and processing described above and shown in the figures. For the sake of simplicity, a detailed description of the known method is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present invention is not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications and additions, or change the order between the steps after understanding the spirit of the present invention.

[0139] In the present invention, features described and / or illustrated for one embodiment may be used in the same or similar manner in one or more other embodiments, and / or combined with features of other embodiments or replace features of other embodiments.

[0140] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the embodiments of the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A railway station regulating equipment control method, characterized in that: The method comprises the following steps: By using the 5G communication network, environmental information of different areas of the railway station is obtained from the environmental monitoring unit, passenger flow image information of different areas of the railway station is obtained from the passenger flow monitoring unit to obtain passenger flow information based on the passenger flow image information, and operation status information of different types of regulating equipment of the railway station is obtained from the equipment monitoring unit, and the business information is transmitted to the edge computing processing unit; wherein the business information includes: the obtained environmental information, passenger flow information and operation status information of different types of regulating equipment; The edge computing processing unit processes the business information to obtain processed environmental information, processed passenger flow information, and processed operating status information of the regulating device, predicts the environment of the railway station based on the processed environmental information and a pre-stored recurrent neural network algorithm, predicts the passenger flow of the railway station based on the processed passenger flow information and a pre-stored recurrent neural network algorithm, and sends the processed business information, the obtained environmental prediction results, and the passenger flow prediction results to the application unit; The application unit generates a device adjustment instruction based on the environmental prediction result, the passenger flow prediction result and the processed operation status information of different types of adjustment equipment, and sends the device adjustment instruction to the control unit of the railway station; The control unit controls a corresponding type of regulating device to execute the device regulating instruction based on the device regulating instruction; The passenger flow information includes passenger flow density; wherein the passenger flow density includes: passenger flow density entering and leaving the station and passenger flow density in different areas within the station; The different types of regulating equipment include the following equipment: station entry and exit gates, station air conditioners, station ventilation equipment, station lighting equipment, guide screens, station broadcasts and security inspection devices, and the operating status information of the regulating equipment includes: equipment operating values ​​and working status; The application unit generates a device adjustment instruction based on the environment prediction result, the passenger flow prediction result and the processed operation status information of the adjustment device, including: Generate an adjustment instruction for the operating value of the station air conditioner based on the predicted value of the multidimensional environmental index in the environmental information that is negatively correlated with the operating value of the station air conditioner after adjustment and the predicted results of the passenger flow density in different areas inside the station and the operating value of the station air conditioner, or based on the predicted value of the multidimensional environmental index in the environmental information that is negatively correlated with the operating value of the station air conditioner after adjustment and the operating value of the station air conditioner; Based on the predicted value of the multidimensional environmental index in the environmental information that is positively correlated with the adjusted operating value of the station ventilation equipment and the operating value of the station ventilation equipment, generating an adjustment instruction for the operating value of the station ventilation equipment; Based on the predicted value of the environmental index in the environmental information that is negatively correlated with the brightness value of the station lighting equipment and the guide screen after adjustment and the brightness value of the station lighting equipment and the guide screen, an adjustment instruction for the brightness value of the station lighting equipment and the guide screen is generated; Based on the predicted values ​​of the environmental indicators in the environmental information that are positively correlated with the volume of the station broadcast after adjustment, the predicted values ​​of the passenger flow density in different areas of the station, and the volume of the station broadcast, an adjustment instruction for the volume of the station broadcast is generated; Based on the predicted value of the passenger flow density entering and exiting the station and the number of entry and exit gates opened, an adjustment instruction for the number of entry and exit gates opened is generated, and based on the number of entry and exit gates opened or based on the predicted value of the passenger flow density entering and exiting the station and the number of security scanners opened, an adjustment instruction for the number of security scanners opened is generated; the predicted value of the passenger flow density entering and exiting the station is positively correlated with the number of entry and exit gates opened after adjustment.

2. The method according to claim 1, characterized in that: The method further includes: the device monitoring unit feeds back the execution result of the device adjustment instruction by the adjustment device to the application unit, and updates the operation status information of the adjustment device of the device monitoring unit.

3. The method according to claim 1, characterized in that The method utilizes the 5G communication network to obtain environmental information of different areas of the railway station from the environmental monitoring unit, obtains passenger flow image information of different areas of the railway station from the passenger flow monitoring unit to obtain passenger flow information based on the passenger flow image information, obtains operating status information of the railway station adjustment equipment from the equipment monitoring unit, and transmits the business information to the edge computing processing unit, including: The 5G communication module is used to obtain environmental information, passenger flow information and equipment operation status information from the environmental monitoring unit, the passenger flow monitoring unit and the equipment monitoring unit respectively, and the collected environmental information, passenger flow information and equipment operation status information are used as business information, and the business information is transmitted to the edge computing processing unit through the 5G customer front-end device and the 5G access network; The edge computing processing unit is connected to the 5G access network and 5G core network respectively through optical cables.

4. The method according to claim 1, characterized in that The method also includes: the cloud platform regularly obtains updated recurrent neural network algorithms from the Internet through the 5G core network, and pushes the obtained algorithms to the edge computing processing unit, thereby pre-storing the recurrent neural network algorithms; wherein the Internet and the 5G core network are connected by wired communication; the cloud platform is respectively connected to the edge computing processing unit and the 5G core network by wired communication.

5. The method according to claim 1, characterized in that The edge computing processing unit processes the business information to obtain processed environmental information, processed passenger flow information, and processed operating status information of the regulating device, including: The edge computing processing unit stores the business information, and the edge computing processing unit processes the stored business information to obtain processed environmental information, processed passenger flow information, and processed operating status information of the regulating device; The edge computing processing unit processes the stored business information, including: supplementing missing business information based on mean filling, replacing abnormal business information based on weighted average, and directly deleting duplicate business information.

6. The method according to claim 1, characterized in that The environmental information includes one or more of the following indicators: temperature, humidity, brightness, noise, PM 2.5 、PM 10 and CO2.

7. The method according to claim 6, characterized in that Environmental indicators that are negatively correlated with the station air-conditioning adjusted operating values ​​include temperature and humidity; Environmental indicators that are positively correlated with the adjusted operating values ​​of station ventilation equipment include PM 2.5 、PM 10 and CO2; environmental indicators that are negatively correlated with the adjusted brightness value of the station lighting equipment and the brightness value of the guide screen after adjustment include brightness; Environmental indicators that are positively correlated with the adjusted volume of station broadcasts include noise; The method further comprises: the application unit pre-stores the normal operating range of the equipment operating value of each regulating equipment in the railway station, and if the operating value of the regulating equipment exceeds the normal operating range, generates an equipment adjustment instruction for the equipment; In the case of generating equipment adjustment instructions based on the prediction results of multiple indicators, weights are assigned to the prediction results of each indicator according to the real-time needs of the railway station and the total prediction result is obtained. The equipment adjustment instructions of the equipment are generated by comparing the total prediction result with the prediction threshold.

8. A railway station equipment control system, comprising a processor and a memory, characterized in that: The memory stores computer instructions, and the processor is used to execute the computer instructions stored in the memory. When the computer instructions are executed by the processor, the system implements the steps of the method as claimed in any one of claims 1 to 7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A railway station equipment control device, characterized in that: To implement the method according to any one of claims 1 to 7, the device comprises: The sensing unit includes an environment monitoring unit, a passenger flow monitoring unit and an equipment monitoring unit, which are used to collect environmental information, passenger flow information and operating status information of the regulating equipment at the railway station; A communication unit, including a 5G communication network, for collecting business information and transmitting it to a processing unit; wherein the 5G communication network includes: a 5G communication module, a 5G customer premise equipment, a 5G access network and a 5G core network; the 5G communication module is mounted on the perception unit; A processing unit, including an edge computing processing unit, for storing and processing the business information and predicting environmental information and passenger flow information of the railway station; An application unit generates an equipment adjustment instruction based on the environmental prediction result, the passenger flow prediction result and the processed operation status information of the adjustment equipment, and sends the equipment adjustment instruction to a control unit of the railway station; The control unit is used to control the railway station adjustment equipment to execute the equipment adjustment instructions and feed back the execution results to the application unit.

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