Airport lighting control method and device, computer equipment and storage medium

Abstract

The embodiment of the invention belongs to the field of lighting control, and relates to an airport lighting control method, which comprises the following steps: acquiring historical lighting control data of a target airport; establishing an illumination control prediction model according to the historical illumination control data; monitoring the passenger flow volume and the illumination intensity of the target airport, and inputting the passenger flow volume and the illumination intensity into the illumination control prediction model; and according to a prediction result output by the illumination control prediction model, determining a target illumination scheme corresponding to the target airport in each preset illumination scheme. According to the method, intelligent management of airport illumination is realized by acquiring historical data and the prediction model, energy consumption waste caused by a fixed mode is reduced, and meanwhile, a basic framework for dynamic adjustment is provided, so that the illumination system is more efficient.

Description

Technical Field

[0001] The present application relates to the field of lighting control, and in particular to an airport lighting control method, device, computer equipment and storage medium. Background Art

[0002] As an important transportation hub in modern society, airports have received extensive attention for their operational efficiency and energy consumption. The lighting system is an indispensable part of airport operations, which not only provides necessary lighting for passengers and staff, but also affects the safety and efficiency of airport operations.

[0003] Generally speaking, the lighting system of an airport adopts a fixed lighting solution, that is, maintaining a constant lighting mode and lighting intensity throughout the day. However, this solution will keep the energy consumption of the lighting system at a high level, resulting in energy waste.

[0004] At present, in order to control energy consumption and avoid wasting energy, most airports use manual adjustment to control lighting. For example, at night or during periods with less traffic, some lighting equipment is manually turned off to reduce energy consumption. However, this method requires manual intervention, resulting in high labor and time costs, and is often inefficient. Summary of the invention

[0005] The purpose of the embodiments of the present application is to provide an airport lighting control method, device, computer equipment and storage medium to solve the technical problem of low efficiency of airport lighting control.

[0006] In order to solve the above technical problems, the embodiment of the present application provides an airport lighting control method, which adopts the following technical solutions:

[0007] A method for controlling airport lighting comprises the following steps:

[0008] Obtain historical lighting control data for target airports;

[0009] Establishing a lighting control prediction model based on the historical lighting control data;

[0010] Monitoring the passenger flow and light intensity of the target airport, and inputting the passenger flow and light intensity into the lighting control prediction model;

[0011] According to the prediction result output by the lighting control prediction model, a target lighting scheme corresponding to the target airport is determined from various preset lighting schemes.

[0012] Furthermore, the step of establishing a lighting control prediction model based on the historical lighting control data specifically includes:

[0013] Preprocessing and feature extraction are performed on the historical lighting control data to obtain a feature data set;

[0014] Performing data segmentation on the feature data set to obtain a training set and a test set;

[0015] Establishing an initial model according to a preset machine learning algorithm, and training the initial model according to the training set to obtain a trained first model;

[0016] The first model is tested according to the test set to obtain a tested second model as the lighting control prediction model.

[0017] Furthermore, after the step of determining the target lighting scheme corresponding to the target airport in each preset lighting scheme according to the prediction result output by the lighting control prediction model, the method further includes:

[0018] When the first variable corresponding to the passenger flow is greater than a preset passenger flow change threshold and / or the second variable corresponding to the light intensity is greater than a preset light intensity change threshold, the target lighting scheme is updated according to the first variable, the second variable and a preset scheme adjustment rule.

[0019] Furthermore, after the step of determining the target lighting scheme corresponding to the target airport in each preset lighting scheme according to the prediction result output by the lighting control prediction model, the method further includes:

[0020] Record in real time the number of times each lamp of the target airport is turned on and off;

[0021] The target lighting solution is optimized according to the switching times.

[0022] Furthermore, after the step of determining the target lighting scheme corresponding to the target airport in each preset lighting scheme according to the prediction result output by the lighting control prediction model, the method further includes:

[0023] Establishing an energy consumption database corresponding to the target airport, collecting lighting energy consumption data of the target airport and storing it in the energy consumption database;

[0024] The lighting energy consumption data is analyzed to generate a lighting energy consumption report corresponding to the target airport.

[0025] Furthermore, after the step of determining the target lighting scheme corresponding to the target airport in each preset lighting scheme according to the prediction result output by the lighting control prediction model, the method further includes:

[0026] At every preset time period, detecting the lighting equipment status of the target airport;

[0027] When there is an abnormality in the state of the lighting device, a preset abnormality alarm message is sent to the administrator user terminal.

[0028] Furthermore, after the step of determining the target lighting scheme corresponding to the target airport in each preset lighting scheme according to the prediction result output by the lighting control prediction model, the method further includes:

[0029] Displaying the passenger flow, the light intensity and the target lighting scheme in real time in a preset management interface;

[0030] When an adjustment instruction carrying adjustment information is received, the target lighting scheme is adjusted according to the adjustment information.

[0031] In order to solve the above technical problems, the embodiment of the present application further provides an airport lighting control device, which adopts the following technical solution:

[0032] An airport lighting control device, comprising:

[0033] An acquisition module, used to acquire historical lighting control data of a target airport;

[0034] An establishment module is used to establish a lighting control prediction model based on the historical lighting control data;

[0035] A monitoring module, used for monitoring the passenger flow and light intensity of the target airport, and inputting the passenger flow and light intensity into the lighting control prediction model;

[0036] A determination module is used to determine the target lighting scheme corresponding to the target airport from various preset lighting schemes based on the prediction results output by the lighting control prediction model.

[0037] In order to solve the above technical problems, the embodiment of the present application further provides a computer device, which adopts the following technical solution:

[0038] A computer device comprises a memory and a processor, wherein the memory stores computer-readable instructions, and the processor implements the steps of the above-mentioned airport lighting control method when executing the computer-readable instructions.

[0039] In order to solve the above technical problems, the embodiment of the present application further provides a computer-readable storage medium, which adopts the following technical solution:

[0040] A computer-readable storage medium stores computer-readable instructions, which, when executed by a processor, implement the steps of the above-mentioned airport lighting control method.

[0041] Compared with the prior art, the embodiments of the present application have the following beneficial effects:

[0042] The airport lighting control method disclosed in the present application obtains the historical lighting control data of the target airport; then establishes a lighting control prediction model based on the historical lighting control data; then monitors the passenger flow and light intensity of the target airport, and inputs the passenger flow and light intensity into the lighting control prediction model; thereby determining the target lighting scheme corresponding to the target airport in each preset lighting scheme based on the prediction results output by the lighting control prediction model. The present application realizes the intelligent management of airport lighting by obtaining historical data and prediction models, reduces energy waste caused by fixed modes, and provides a basic framework for dynamic adjustment to make the lighting system more efficient. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the scheme in the present application, a brief introduction is given below to the drawings required for use in the description of the embodiments of the present application. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0044] Figure 1 is an exemplary system architecture diagram to which the present application may be applied;

[0045] Figure 2 is a flow chart of an embodiment of an airport lighting control method according to the present application;

[0046] Figure 3 is a schematic structural diagram of an embodiment of an airport lighting control device according to the present application;

[0047] Figure 4 It is a structural diagram of an embodiment of a computer device according to the present application. DETAILED DESCRIPTION

[0048] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by technicians in the technical field of the present application; the terms used in the specification of the application herein are only for the purpose of describing specific embodiments and are not intended to limit the present application; the terms "including" and "having" and any variations thereof in the specification and claims of the present application and the above-mentioned drawings are intended to cover non-exclusive inclusions. The terms "first", "second", etc. in the specification and claims of the present application or the above-mentioned drawings are used to distinguish different objects, not to describe a specific order.

[0049] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0050] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings.

[0051] like Figure 1 As shown, the system architecture 100 may include terminal devices 101, 102, 103, a network 104 and a server 105. The network 104 is used to provide a medium for communication links between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links or optical fiber cables, etc.

[0052] Users can use terminal devices 101, 102, 103 to interact with server 105 through network 104 to receive or send messages, etc. Various communication client applications can be installed on terminal devices 101, 102, 103, such as web browser applications, shopping applications, search applications, instant messaging tools, email clients, social platform software, etc.

[0053] Terminal devices 101, 102, 103 can be various electronic devices with display screens and supporting web browsing, including but not limited to smart phones, tablet computers, e-book readers, MP3 (Moving Picture Experts Group Audio Layer III) players, MP4 (Moving Picture Experts Group Audio Layer IV) players, laptop computers, desktop computers, etc.

[0054] The server 105 may be a server that provides various services, such as a background server that provides support for web pages displayed on the terminal devices 101 , 102 , and 103 .

[0055] It should be noted that the airport lighting control method provided in the embodiment of the present application is generally executed by a server / terminal device, and accordingly, the airport lighting control device is generally arranged in the server / terminal device.

[0056] It should be understood that Figure 1The number of terminal devices, networks and servers in the embodiment is only for illustration. Any number of terminal devices, networks and servers may be provided according to implementation requirements.

[0057] Continue to refer Figure 2 , shows a flow chart of an embodiment of an airport lighting control method according to the present application. The airport lighting control method comprises the following steps:

[0058] Step S201, obtaining historical lighting control data of the target airport.

[0059] In this embodiment, the airport lighting control method is executed on the electronic device (eg Figure 1 The server / terminal device shown in the figure can send or receive data through a wired connection or a wireless connection. It should be noted that the above wireless connection methods may include but are not limited to 3G / 4G / 5G connection, WiFi connection, Bluetooth connection, WiMAX connection, Zigbee connection, UWB (ultra wideband) connection, and other wireless connection methods currently known or to be developed in the future.

[0060] In this embodiment, the historical lighting control data of the target airport is usually derived from past operation records, including the time when lamps are turned on and off, the set value of regional brightness, passenger flow statistics, light intensity monitoring data, and energy consumption records. The acquisition of these data requires relying on the airport's existing lighting management system and collecting them through linkage with passenger flow monitoring and environmental sensors. Specifically, it is assumed that the historical data of the target airport reflects that the passenger flow peak from 18:00 to 22:00 in winter is accompanied by high brightness requirements, while in the same period in spring, due to sufficient natural light, historical data shows that the brightness setting is lower. After these data are imported into the system, the correlation between passenger flow, time and light intensity can be extracted through specific algorithms.

[0061] Step S202: establishing a lighting control prediction model based on the historical lighting control data.

[0062] In this embodiment, after the data is cleaned, it will be trained using machine learning algorithms such as support vector machines (SVM) and random forests. Combined with the feature extraction steps in the briefing book, multidimensional features such as time and passenger flow are extracted and divided into training sets and test sets. The accuracy of the prediction results is ensured by continuously optimizing the parameters of the model. For example, the prediction model can output a suggestion: when the passenger flow is 1,800 people per hour and the natural light intensity is less than 10 lux, the optimal lighting solution is to set the terminal hall to 70% brightness.

[0063] Step S203, monitoring the passenger flow and light intensity of the target airport, and inputting the passenger flow and light intensity into the lighting control prediction model.

[0064] In this embodiment, the passenger flow and light intensity of the airport are monitored in real time, input into the prediction model and the lighting scheme is adjusted dynamically. Specifically, sensors are deployed in different areas of the airport, including infrared passenger flow counters and light intensity sensors. Each sensor uploads data to the central control system at a fixed time. For example, when the infrared sensor detects that the passenger flow in the terminal hall has increased from 1,500 to 2,500, the light sensor shows that the natural light intensity has dropped to 8 lux, and the system will automatically identify that the current area requires higher artificial lighting compensation. The prediction model outputs a recommended lighting scheme and optimizes and adjusts it according to the real-time data of passenger flow and light intensity changes. Assume that the original lighting scheme of the terminal hall is set to 50% brightness, but due to the arrival of the passenger flow peak, the system switches to 70% brightness mode, while reducing the lighting intensity of low-usage areas (such as the edge area of ​​the terminal building), so as to achieve energy consumption balance while meeting demand.

[0065] Step S204: determining a target lighting scheme corresponding to the target airport from various preset lighting schemes according to the prediction result output by the lighting control prediction model.

[0066] In this embodiment, the system selects the most suitable text solution from the preset solution library based on the suggested text output by the prediction model. For example, the terminal hall uses 80% of the lighting brightness, and the boarding gate area is reduced to 60%, instead of using a uniform high brightness mode.

[0067] This application achieves intelligent management of airport lighting by acquiring historical data and predictive models, reducing energy waste caused by fixed modes, and providing a basic framework for dynamic adjustment to make the lighting system more efficient.

[0068] In some optional implementations of this embodiment, the step of establishing a lighting control prediction model based on the historical lighting control data specifically includes:

[0069] Preprocessing and feature extraction are performed on the historical lighting control data to obtain a feature data set;

[0070] Performing data segmentation on the feature data set to obtain a training set and a test set;

[0071] Establishing an initial model according to a preset machine learning algorithm, and training the initial model according to the training set to obtain a trained first model;

[0072] The first model is tested according to the test set to obtain a tested second model as the lighting control prediction model.

[0073] In this embodiment, the historical data may contain redundant information (such as data noise, missing values, etc.). The system removes outliers through data cleaning, and extracts features such as time, passenger flow, light intensity, brightness setting, etc. to generate a feature data set. For example, the extracted features include "18:00-22:00", "light intensity <10 lux", and "brightness is set to 80%". The system divides the feature data set into a training set and a test set, for example, in a ratio of 8:2. The initial model is then trained using a support vector machine (SVM) to output the first version of the prediction model. The system verifies the first version of the model with a test set, adjusts parameters to improve prediction accuracy, and generates a final model. For example, the final model can predict that "the optimal brightness of the terminal hall is 75%" based on passenger flow and light intensity.

[0074] This application improves prediction accuracy through model training and optimization, ensuring that the system can adapt to complex airport environments and provide accurate lighting demand predictions.

[0075] In some optional implementations of this embodiment, after the step of determining the target lighting scheme corresponding to the target airport from various preset lighting schemes according to the prediction results output by the lighting control prediction model, the method further includes:

[0076] When the first variable corresponding to the passenger flow is greater than a preset passenger flow change threshold and / or the second variable corresponding to the light intensity is greater than a preset light intensity change threshold, the target lighting scheme is updated according to the first variable, the second variable and a preset scheme adjustment rule.

[0077] In this embodiment, the system presets the change thresholds of two key variables, such as "passenger flow increases by more than 2,000 people" and "light intensity decreases by more than 50%". When the passenger flow in a certain area increases sharply from 3,000 to 5,000 people, and the light intensity decreases to 5 lux, the system determines that the change threshold conditions are met and immediately triggers the solution update. The system increases the brightness of key areas according to the rules. For example, the brightness of the lamps in the terminal hall is adjusted from 60% to 90%, while the edge areas remain the same, thereby avoiding the increase in energy consumption caused by the global brightness increase.

[0078] This application improves the system's response capability to emergencies by setting passenger flow change thresholds and light intensity change thresholds, optimizes the solution adjustment process, ensures the flexibility and accuracy of lighting, and takes into account energy consumption control.

[0079] In some optional implementations of this embodiment, after the step of determining the target lighting scheme corresponding to the target airport from various preset lighting schemes according to the prediction results output by the lighting control prediction model, the method further includes:

[0080] Record in real time the number of times each lamp of the target airport is turned on and off;

[0081] The target lighting solution is optimized according to the switching times.

[0082] In this embodiment, the system can assign a unique ID to each lamp and record its daily on-off times through the background. For example, the lamp ID001 in the boarding gate area is on and off 15 times in one day, with a total of 3,000 times. According to the recorded data, when the on-off times of a lamp reaches 80% of its design life, the system will give priority to adjusting other lamps to balance the use. For example, replace the lamps with high frequency of use with spare lamps to extend the overall life of the equipment.

[0083] This application reduces equipment loss, lowers maintenance costs, and extends the life of lamps through recording and optimization, while avoiding insufficient regional lighting due to damage.

[0084] In some optional implementations of this embodiment, after the step of determining the target lighting scheme corresponding to the target airport from various preset lighting schemes according to the prediction results output by the lighting control prediction model, the method further includes:

[0085] Establishing an energy consumption database corresponding to the target airport, collecting lighting energy consumption data of the target airport and storing it in the energy consumption database;

[0086] The lighting energy consumption data is analyzed to generate a lighting energy consumption report corresponding to the target airport.

[0087] In this embodiment, the system collects energy consumption data of various areas of the airport in real time and stores it in the database. For example, the monthly energy consumption of the terminal hall is 3000kWh, of which 70% is during peak hours. Then, a report is generated through energy consumption data analysis. For example, the analysis found that the energy consumption of the boarding gate area is still high during the late night when there is low passenger flow, and it is recommended to reduce the brightness setting during this period.

[0088] This application achieves refined management of energy consumption by collecting energy consumption data, analyzing it and generating reports, providing a scientific basis for green operations at the airport.

[0089] In some optional implementations of this embodiment, after the step of determining the target lighting scheme corresponding to the target airport from various preset lighting schemes according to the prediction results output by the lighting control prediction model, the method further includes:

[0090] At every preset time period, detecting the lighting equipment status of the target airport;

[0091] When there is an abnormality in the state of the lighting device, a preset abnormality alarm message is sent to the administrator user terminal.

[0092] In this embodiment, the system can detect the current and voltage status of the lamp every hour to identify whether the equipment has abnormalities such as short circuit or damage; when it detects that the power of a lamp in the terminal hall has dropped abnormally, the system sends an alarm message to the administrator that "Lamp ID001 is faulty, please check in time."

[0093] This application improves the intelligence level of equipment management and reduces the impact of faults on airport operations by regularly detecting equipment status and sending alarm information.

[0094] In some optional implementations of this embodiment, after the step of determining the target lighting scheme corresponding to the target airport from various preset lighting schemes according to the prediction results output by the lighting control prediction model, the method further includes:

[0095] Displaying the passenger flow, the light intensity and the target lighting scheme in real time in a preset management interface;

[0096] When an adjustment instruction carrying adjustment information is received, the target lighting scheme is adjusted according to the adjustment information.

[0097] In this embodiment, data can be displayed in real time, and the management interface displays the passenger flow, light intensity, and lighting scheme of each area of ​​the airport. For example, the passenger flow of the terminal hall is 2,000 people, the light intensity is 8 lux, and the current brightness is 70%. Manual intervention and adjustment can also be made. The administrator can enter adjustment instructions, such as increasing the brightness of the boarding gate to 80%, and the system will respond immediately and update the scheme.

[0098] This application improves the flexibility of human-computer interaction by displaying data in real time and adjusting through manual intervention, allows manual intervention on the basis of automatic control, and enhances the adaptability of the system.

[0099] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Among them, artificial intelligence (AI) is the theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.

[0100] AI basic technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing technology, operation / interaction systems, mechatronics, etc. AI software technologies mainly include computer vision technology, robotics technology, biometrics technology, speech processing technology, natural language processing technology, and machine learning / deep learning.

[0101] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through computer-readable instructions, and the computer-readable instructions can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, the aforementioned storage medium can be a non-volatile storage medium such as a disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).

[0102] It should be understood that, although the steps in the flowchart of the accompanying drawings are displayed in sequence as indicated by the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a part of the sub-steps or stages of other steps.

[0103] Further references Figure 3 , as a response to the above Figure 2 The present application provides an embodiment of an airport lighting control device, and the device embodiment is Figure 2 Corresponding to the method embodiment shown, the device can be specifically applied to various electronic devices.

[0104] like Figure 3 As shown, the airport lighting control device 300 described in this embodiment includes: an acquisition module 301, an establishment module 302, a monitoring module 303 and a determination module 304. Among them:

[0105] An acquisition module 301 is used to acquire historical lighting control data of a target airport;

[0106] Establishing module 302, for establishing a lighting control prediction model according to the historical lighting control data;

[0107] A monitoring module 303, used to monitor the passenger flow and light intensity of the target airport, and input the passenger flow and light intensity into the lighting control prediction model;

[0108] The determination module 304 is used to determine the target lighting scheme corresponding to the target airport from various preset lighting schemes based on the prediction results output by the lighting control prediction model.

[0109] The airport lighting control device provided in this application realizes intelligent management of airport lighting by acquiring historical data and predictive models, reduces energy waste caused by fixed modes, and provides a basic framework for dynamic adjustment to make the lighting system more efficient.

[0110] In some optional implementations of this embodiment, the establishing module 302 is further used to:

[0111] Preprocessing and feature extraction are performed on the historical lighting control data to obtain a feature data set;

[0112] Performing data segmentation on the feature data set to obtain a training set and a test set;

[0113] Establishing an initial model according to a preset machine learning algorithm, and training the initial model according to the training set to obtain a trained first model;

[0114] The first model is tested according to the test set to obtain a tested second model as the lighting control prediction model.

[0115] The airport lighting control device provided in this application improves prediction accuracy through model training and optimization, ensuring that the system can adapt to complex airport environments and provide accurate lighting demand predictions.

[0116] In some optional implementations of this embodiment, the determination module 304 is further configured to:

[0117] When the first variable corresponding to the passenger flow is greater than a preset passenger flow change threshold and / or the second variable corresponding to the light intensity is greater than a preset light intensity change threshold, the target lighting scheme is updated according to the first variable, the second variable and a preset scheme adjustment rule.

[0118] The airport lighting control device provided in this application improves the system's response capability to emergencies by setting passenger flow change thresholds and light intensity change thresholds, optimizes the solution adjustment process, ensures the flexibility and accuracy of lighting, and takes into account energy consumption control.

[0119] In some optional implementations of this embodiment, the determination module 304 is further configured to:

[0120] Record in real time the number of times each lamp of the target airport is turned on and off;

[0121] The target lighting solution is optimized according to the switching times.

[0122] The airport lighting control device provided in this application reduces equipment loss, reduces maintenance costs, and extends the service life of lamps through recording and optimization, while avoiding insufficient regional lighting due to damage.

[0123] In some optional implementations of this embodiment, the determination module 304 is further configured to:

[0124] Establishing an energy consumption database corresponding to the target airport, collecting lighting energy consumption data of the target airport and storing it in the energy consumption database;

[0125] The lighting energy consumption data is analyzed to generate a lighting energy consumption report corresponding to the target airport.

[0126] The airport lighting control device provided in this application realizes refined management of energy consumption by collecting energy consumption data, analyzing it and generating reports, providing a scientific basis for green operations of the airport.

[0127] In some optional implementations of this embodiment, the determination module 304 is further configured to:

[0128] At every preset time period, detecting the lighting equipment status of the target airport;

[0129] When there is an abnormality in the state of the lighting device, a preset abnormality alarm message is sent to the administrator user terminal.

[0130] The airport lighting control device provided in the present application improves the intelligent level of equipment management and reduces the impact of faults on airport operations by regularly detecting equipment status and sending alarm information.

[0131] In some optional implementations of this embodiment, the determination module 304 is further configured to:

[0132] Displaying the passenger flow, the light intensity and the target lighting scheme in real time in a preset management interface;

[0133] When an adjustment instruction carrying adjustment information is received, the target lighting scheme is adjusted according to the adjustment information.

[0134] The airport lighting control device provided in the present application improves the flexibility of human-computer interaction by displaying data in real time and adjusting through manual intervention, allows manual intervention on the basis of automatic control, and enhances the adaptability of the system.

[0135] To solve the above technical problems, the present application also provides a computer device. Figure 4 , Figure 4 This is a basic structural block diagram of the computer device in this embodiment.

[0136] The computer device 4 includes a memory 41, a processor 42, and a network interface 43 that are interconnected through a system bus. It should be noted that the figure only shows a computer device 4 with components 41-43, but it should be understood that it is not required to implement all the components shown, and more or fewer components can be implemented instead. Among them, those skilled in the art can understand that the computer device here is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to microprocessors, application specific integrated circuits (Application Specific Integrated Circuit, ASIC), programmable gate arrays (Field-Programmable Gate Array, FPGA), digital processors (Digital Signal Processor, DSP), embedded devices, etc.

[0137] The computer device may be a computing device such as a desktop computer, a notebook, a PDA, a cloud server, etc. The computer device may interact with a user through a keyboard, a mouse, a remote controller, a touch pad, or a voice control device.

[0138] The memory 41 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, hard disk, multimedia card, card-type memory (for example, SD or DX memory, etc.), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 41 can be an internal storage unit of the computer device 4, such as a hard disk or memory of the computer device 4. In other embodiments, the memory 41 can also be an external storage device of the computer device 4, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (FlashCard), etc. equipped on the computer device 4. Of course, the memory 41 can also include both the internal storage unit of the computer device 4 and its external storage device. In this embodiment, the memory 41 is generally used to store the operating system and various application software installed on the computer device 4, such as computer-readable instructions of the airport lighting control method, etc. In addition, the memory 41 can also be used to temporarily store various types of data that have been output or are to be output.

[0139] The processor 42 may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chips in some embodiments. The processor 42 is generally used to control the overall operation of the computer device 4. In this embodiment, the processor 42 is used to run computer-readable instructions stored in the memory 41 or process data, such as computer-readable instructions for running the airport lighting control method.

[0140] The network interface 43 may include a wireless network interface or a wired network interface. The network interface 43 is generally used to establish a communication connection between the computer device 4 and other electronic devices.

[0141] The computer equipment provided in this application realizes intelligent management of airport lighting by acquiring historical data and predictive models, reduces energy waste caused by fixed modes, and provides a basic framework for dynamic adjustment to make the lighting system more efficient.

[0142] The present application also provides another embodiment, namely, providing a computer-readable storage medium, wherein the computer-readable storage medium stores computer-readable instructions, and the computer-readable instructions can be executed by at least one processor to enable the at least one processor to perform the steps of the above-mentioned airport lighting control method.

[0143] The computer-readable storage medium provided in this application realizes intelligent management of airport lighting by acquiring historical data and predictive models, reduces energy waste caused by fixed modes, and provides a basic framework for dynamic adjustment to make the lighting system more efficient.

[0144] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in each embodiment of the present application.

[0145] Obviously, the embodiments described above are only some embodiments of the present application, rather than all embodiments. The preferred embodiments of the present application are given in the accompanying drawings, but they do not limit the patent scope of the present application. The present application can be implemented in many different forms. On the contrary, the purpose of providing these embodiments is to make the understanding of the disclosure of the present application more thorough and comprehensive. Although the present application is described in detail with reference to the aforementioned embodiments, for those skilled in the art, it is still possible to modify the technical solutions recorded in the aforementioned specific implementation methods, or to perform equivalent replacement of some of the technical features therein. Any equivalent structure made using the contents of the specification and drawings of this application, directly or indirectly used in other related technical fields, is similarly within the scope of patent protection of this application.

Claims

1. A method for controlling airport lighting, characterized in that: The steps include: Obtain historical lighting control data for target airports; Establishing a lighting control prediction model based on the historical lighting control data; Monitoring the passenger flow and light intensity of the target airport, and inputting the passenger flow and light intensity into the lighting control prediction model; According to the prediction result output by the lighting control prediction model, a target lighting scheme corresponding to the target airport is determined from various preset lighting schemes.

2. The airport lighting control method according to claim 1, characterized in that: The step of establishing a lighting control prediction model according to the historical lighting control data specifically includes: Preprocessing and feature extraction are performed on the historical lighting control data to obtain a feature data set; Performing data segmentation on the feature data set to obtain a training set and a test set; Establishing an initial model according to a preset machine learning algorithm, and training the initial model according to the training set to obtain a trained first model; The first model is tested according to the test set to obtain a tested second model as the lighting control prediction model.

3. The airport lighting control method according to claim 1, characterized in that: After the step of determining the target lighting scheme corresponding to the target airport from various preset lighting schemes according to the prediction results output by the lighting control prediction model, the method further includes: When the first variable corresponding to the passenger flow is greater than a preset passenger flow change threshold and / or the second variable corresponding to the light intensity is greater than a preset light intensity change threshold, the target lighting scheme is updated according to the first variable, the second variable and a preset scheme adjustment rule.

4. The airport lighting control method according to claim 1, characterized in that: After the step of determining the target lighting scheme corresponding to the target airport from various preset lighting schemes according to the prediction results output by the lighting control prediction model, the method further includes: Record in real time the number of times each lamp of the target airport is turned on and off; The target lighting solution is optimized according to the switching times.

5. The airport lighting control method according to claim 1, characterized in that: After the step of determining the target lighting scheme corresponding to the target airport from various preset lighting schemes according to the prediction results output by the lighting control prediction model, the method further includes: Establishing an energy consumption database corresponding to the target airport, collecting lighting energy consumption data of the target airport and storing it in the energy consumption database; The lighting energy consumption data is analyzed to generate a lighting energy consumption report corresponding to the target airport.

6. The airport lighting control method according to claim 1, characterized in that: After the step of determining the target lighting scheme corresponding to the target airport from various preset lighting schemes according to the prediction results output by the lighting control prediction model, the method further includes: At every preset time period, detecting the lighting equipment status of the target airport; When there is an abnormality in the state of the lighting device, a preset abnormality alarm message is sent to the administrator user terminal.

7. The airport lighting control method according to any one of claims 1 to 6, characterized in that: After the step of determining the target lighting scheme corresponding to the target airport from various preset lighting schemes according to the prediction results output by the lighting control prediction model, the method further includes: Displaying the passenger flow, the light intensity and the target lighting scheme in real time in a preset management interface; When an adjustment instruction carrying adjustment information is received, the target lighting scheme is adjusted according to the adjustment information.

8. An airport lighting control device, characterized in that: include: An acquisition module, used to acquire historical lighting control data of a target airport; An establishment module is used to establish a lighting control prediction model based on the historical lighting control data; A monitoring module, used for monitoring the passenger flow and light intensity of the target airport, and inputting the passenger flow and light intensity into the lighting control prediction model; A determination module is used to determine the target lighting scheme corresponding to the target airport from various preset lighting schemes based on the prediction results output by the lighting control prediction model.

9. A computer device, characterized in that: The method comprises a memory and a processor, wherein the memory stores computer-readable instructions, and the processor implements the steps of the airport lighting control method according to any one of claims 1 to 7 when executing the computer-readable instructions.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-readable instructions, and when the computer-readable instructions are executed by a processor, the steps of the airport lighting control method according to any one of claims 1 to 7 are implemented.

Images