Intelligent energy-saving method and device for air conditioner in subway station

Abstract

The embodiment of the invention discloses an intelligent energy-saving method and device for an air conditioner in a subway station. According to the technical scheme, the initial air conditioner control parameters of the target area in the passenger flow idle period are set based on the historical average passenger flow volume, and the air conditioner temperature and the air conditioner air speed of the target area are controlled according to the initial air conditioner control parameters; the passenger flow variation of the target area is predicted based on the in-station monitoring video in the passenger flow idle period, and the predicted passenger flow of the target area is determined according to the real-time passenger flow and the passenger flow variation; and according to the passenger flow difference value, configuring an air-conditioning temperature adjustment amount and an air-conditioning wind speed adjustment amount, and adjusting the air-conditioning temperature and the air-conditioning wind speed of the target area according to the air-conditioning temperature adjustment amount and the air-conditioning wind speed adjustment amount. Air conditioner control can meet the real-time passenger flow requirement, precise control over the air conditioner in the station is achieved, energy consumption in the idle period is reduced, and the operation cost in the station is reduced.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of rail transit technology, and in particular to an intelligent energy-saving method and device for air conditioning in a subway station. Background Art

[0002] At present, in the daily operation of subways, due to the large space and large flow of people in subway stations, there is a great demand for air conditioning. In order to improve the riding experience of passengers and provide a comfortable riding environment, air conditioning is usually provided in the station during the operation period of the subway.

[0003] However, the passenger flow in subway stations varies during different operating hours. During peak passenger flow periods, the demand for air conditioning in the station is relatively large; during periods with less passenger flow, the demand for air conditioning supply in some areas of the station is relatively small. If the highest standard of air conditioning is provided during all operating hours, it will inevitably cause energy waste and increase the operating costs of the subway station. Summary of the invention

[0004] The embodiment of the present application provides an intelligent energy-saving method and device for air conditioning in a subway station. By dynamically adjusting the air-conditioning temperature and air-conditioning wind speed during idle periods in combination with changes in historical average passenger flow and real-time passenger flow, the air-conditioning control can be made to meet real-time passenger flow needs, thereby achieving precise control of the air conditioning in the station, saving energy consumption during idle periods, reducing operating costs in the station, and solving the technical problem of air-conditioning energy waste in subway stations.

[0005] In a first aspect, an embodiment of the present application provides an intelligent energy-saving method for air conditioning in a subway station, comprising:

[0006] Obtain historical surveillance videos of different time periods in the subway station, analyze historical passenger flow data of a target area at different time periods based on the historical surveillance videos, determine a passenger flow idle period of the target area according to the historical passenger flow data, and determine a historical average passenger flow of the target area during the passenger flow idle period according to the historical passenger flow data;

[0007] Setting initial air-conditioning control parameters of the target area during the idle passenger flow period based on the historical average passenger flow, and controlling the air-conditioning temperature and air-conditioning wind speed of the target area according to the initial air-conditioning control parameters at the initial moment of the idle passenger flow period;

[0008] During the idle passenger flow period, real-time inbound passenger flow, arrival passenger flow and real-time passenger flow in the target area are collected based on the in-station surveillance video, and the passenger flow change in the target area is predicted based on the correlation between the inbound passenger flow, arrival passenger flow and the in-station path of the target area. The predicted passenger flow of the target area is determined based on the real-time passenger flow and the passenger flow change. When the passenger flow difference between the predicted passenger flow and the historical average passenger flow reaches a set threshold, the air-conditioning temperature adjustment amount and the air-conditioning wind speed adjustment amount are configured according to the passenger flow difference, and the air-conditioning temperature and air-conditioning wind speed of the target area are adjusted according to the air-conditioning temperature adjustment amount and the air-conditioning wind speed adjustment amount.

[0009] Furthermore, the analyzing the historical passenger flow data of the target area at different time periods based on the historical surveillance video includes:

[0010] Based on the historical surveillance video, target detection is performed on the target area, the number of targets detected in different time periods is counted, and the number of targets is used as the historical passenger flow data of the corresponding time period.

[0011] Further, determining the idle passenger flow period of the target area according to the historical passenger flow data includes:

[0012] Determine a time period in which the historical passenger flow data is lower than a set threshold as an idle sub-period, wherein the length of the idle sub-period is fixed;

[0013] When the number of the continuously detected idle sub-periods reaches a set value, the continuously detected idle sub-periods are determined as passenger flow idle periods of the target area.

[0014] Furthermore, before the initial moment of the passenger flow idle period, the method further includes:

[0015] It is detected that the current time is less than a set time from the initial time of the passenger flow idle period, and a smooth transition adjustment is performed to the initial air-conditioning control parameters based on the current real-time air-conditioning control parameters of the target area.

[0016] Further, the predicting of the passenger flow change of the target area based on the correlation between the incoming passenger flow, the arriving passenger flow and the in-station path of the target area includes:

[0017] Calculate a first passenger flow increment of the target area during a target period based on the correlation between the incoming passenger flow and the in-station path of the target area;

[0018] Calculate a second passenger flow increment of the target area during a target period based on the correlation between the passenger flow arriving at the station and the path within the station of the target area;

[0019] The sum of the first passenger flow increment and the second passenger flow increment is taken as the passenger flow change of the target area.

[0020] Further, the adjusting the air conditioning temperature and the air conditioning wind speed of the target area according to the air conditioning temperature adjustment amount and the air conditioning wind speed adjustment amount includes:

[0021] During the set adjustment period, the air-conditioning temperature and air-conditioning wind speed of the target area are adjusted according to the set step size until the adjustment value of the air-conditioning temperature of the target area reaches the air-conditioning temperature adjustment amount, and the adjustment value of the air-conditioning wind speed of the target area reaches the air-conditioning wind speed adjustment amount.

[0022] Further, after adjusting the air conditioning temperature and the air conditioning wind speed of the target area according to the air conditioning temperature adjustment amount and the air conditioning wind speed adjustment amount, the method further includes:

[0023] The real-time passenger flow is detected to reach the set passenger flow threshold value after a set number of consecutive adjustment cycles, and it is determined that the current target area jumps out of the passenger flow idle period, and the set conventional passenger flow air conditioning adjustment logic is called to perform air conditioning control of the current target area.

[0024] In a second aspect, an embodiment of the present application provides an intelligent energy-saving device for air conditioning in a subway station, comprising:

[0025] An idle period determination module is used to obtain historical surveillance videos of different periods in the subway station, analyze historical passenger flow data of the target area at different periods based on the historical surveillance videos, determine the passenger flow idle period of the target area according to the historical passenger flow data, and determine the historical average passenger flow of the target area during the passenger flow idle period according to the historical passenger flow data;

[0026] An initial adjustment module, configured to set initial air conditioning control parameters of the target area during the idle passenger flow period based on the historical average passenger flow, and control the air conditioning temperature and air conditioning wind speed of the target area according to the initial air conditioning control parameters at the initial moment of the idle passenger flow period;

[0027] A real-time adjustment module is used to collect real-time incoming passenger flow, arriving passenger flow and real-time passenger flow in the target area based on the station monitoring video during the idle passenger flow period, predict the passenger flow change in the target area based on the correlation between the incoming passenger flow, arriving passenger flow and the station path of the target area, determine the predicted passenger flow of the target area according to the real-time passenger flow and the passenger flow change, and when the passenger flow difference between the predicted passenger flow and the historical average passenger flow reaches a set threshold, configure the air-conditioning temperature adjustment amount and the air-conditioning wind speed adjustment amount according to the passenger flow difference, and adjust the air-conditioning temperature and air-conditioning wind speed of the target area according to the air-conditioning temperature adjustment amount and the air-conditioning wind speed adjustment amount.

[0028] In a third aspect, an embodiment of the present application provides an electronic device, including:

[0029] memory and one or more processors;

[0030] The memory is used to store one or more programs;

[0031] When the one or more programs are executed by the one or more processors, the one or more processors implement the intelligent energy-saving method for air conditioning in a subway station as described in the first aspect.

[0032] In a fourth aspect, an embodiment of the present application provides a storage medium comprising computer executable instructions, which, when executed by a computer processor, are used to execute the intelligent energy-saving method for air conditioning in a subway station as described in the first aspect.

[0033] The embodiment of the present application obtains historical surveillance videos of different time periods in the subway station, analyzes historical passenger flow data of the target area at different time periods based on the historical surveillance videos, determines the idle passenger flow period of the target area according to the historical passenger flow data, and determines the historical average passenger flow of the target area during the idle passenger flow period according to the historical passenger flow data; sets initial air-conditioning control parameters of the target area during the idle passenger flow period based on the historical average passenger flow, and controls the air-conditioning temperature and air-conditioning wind speed of the target area according to the initial air-conditioning control parameters at the initial moment of the idle passenger flow period; collects real-time inbound passenger flow, arrival passenger flow and real-time passenger flow of the target area based on the in-station surveillance video during the idle passenger flow period, predicts the passenger flow change of the target area based on the correlation between the inbound passenger flow, arrival passenger flow and the in-station path of the target area, determines the predicted passenger flow of the target area according to the real-time passenger flow and the passenger flow change, and configures the air-conditioning temperature adjustment amount and the air-conditioning wind speed adjustment amount according to the passenger flow difference when the passenger flow difference between the predicted passenger flow and the historical average passenger flow reaches a set threshold, and adjusts the air-conditioning temperature and air-conditioning wind speed of the target area according to the air-conditioning temperature adjustment amount and the air-conditioning wind speed adjustment amount. By adopting the above-mentioned technical means, the air-conditioning temperature and air-conditioning wind speed during idle periods are dynamically adjusted by combining the historical average passenger flow and the changes in real-time passenger flow. This can make the air-conditioning control meet the real-time passenger flow demand, realize precise control of the air-conditioning in the station, save energy consumption during idle periods, and reduce the operating costs in the station. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 This is a flow chart of an intelligent energy-saving method for air conditioning in a subway station provided in Example 1 of the present application;

[0035] Figure 2 It is an interactive schematic diagram of the air conditioning intelligent energy-saving system in the subway station in the first embodiment of the present application;

[0036] Figure 3 This is a flow chart for determining the idle passenger flow period in the first embodiment of the present application;

[0037] Figure 4 is a flow chart for determining the passenger flow change amount in the first embodiment of the present application;

[0038] Figure 5 This is a schematic diagram of the structure of an intelligent energy-saving device for air conditioning in a subway station provided in Example 2 of the present application;

[0039] Figure 6 It is a structural schematic diagram of an electronic device provided in Example 3 of the present application. DETAILED DESCRIPTION

[0040] In order to make the purpose, technical scheme and advantages of the present application clearer, the specific embodiments of the present application are further described in detail below in conjunction with the accompanying drawings. It is understood that the specific embodiments described herein are only used to explain the present application, rather than to limit the present application. It should also be noted that, for the convenience of description, only the part related to the present application but not all the contents are shown in the accompanying drawings. Before discussing the exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flow charts. Although the flow chart describes each operation (or step) as a sequential process, many of the operations therein can be implemented in parallel, concurrently or simultaneously. In addition, the order of each operation can be rearranged. The process can be terminated when its operation is completed, but it can also have additional steps not included in the accompanying drawings. The process can correspond to a method, a function, a procedure, a subroutine, a subprogram, etc.

[0041] Embodiment 1:

[0042] The intelligent energy-saving method for air conditioning in subway stations of this application aims to collect historical surveillance videos of various areas in the subway station (such as platforms, passages, waiting areas, etc.) at different time periods. Through video analysis technology (such as computer vision, image recognition, etc.), historical passenger flow data for each time period is counted. The collected passenger flow data is sorted, the passenger flow for each time period (such as every hour or every half hour) is calculated, and the peak passenger flow period and idle period are identified. Based on the historical passenger flow data, the idle passenger flow period of each target area is determined. For each idle period, an initial air-conditioning temperature and wind speed control parameters are set according to the historical average passenger flow of the period. These parameters are designed to ensure basic comfort while avoiding excessive cooling or heating.

[0043] Then, during the idle passenger flow period, the real-time passenger flow data of the incoming passenger flow, the arriving passenger flow and the target area are collected in real time through the station monitoring video. At the same time, the data analysis model (such as time series analysis, machine learning algorithm, etc.) is used to combine the incoming passenger flow, the arriving passenger flow and the target area path correlation to predict the future passenger flow change in the target area. The real-time passenger flow is combined with the predicted change to obtain the predicted passenger flow in the target area. The predicted passenger flow is compared with the historical average passenger flow. When the difference between the two reaches the preset threshold, the adjustment mechanism of the air conditioning parameters is triggered. According to the size and direction of the passenger flow difference (increase or decrease), the adjustment amount of the air conditioning temperature and wind speed is calculated, and the air conditioning settings of the target area are automatically adjusted to meet the real-time passenger flow needs.

[0044] In this way, by dynamically adjusting the air conditioning parameters, unnecessary cooling or heating can be avoided during periods of low passenger flow, significantly reducing energy consumption, reducing the operating costs of subway stations, and ensuring that the air conditioning parameters are adjusted in time when the passenger flow changes to maintain the basic comfort of passengers and avoid overcooling or overheating. At the same time, big data analysis and intelligent control technology are used to realize the automation and intelligent management of the air conditioning system in the subway station, improve operational efficiency and management level. Flexible response to changes in passenger flow in different periods and different areas, accurate control, and avoid "one-size-fits-all" air conditioning management methods. And by reducing energy consumption, it helps to reduce carbon emissions and promote the green, low-carbon and sustainable development of the subway system.

[0045] Figure 1 A flow chart of an air conditioning smart energy-saving method in a subway station provided in Example 1 of the present application is given. The air conditioning smart energy-saving method in a subway station provided in this embodiment can be executed by an air conditioning smart energy-saving device in the subway station. The air conditioning smart energy-saving device in the subway station can be implemented by software and / or hardware. The air conditioning smart energy-saving device in the subway station can be composed of two or more physical entities, or it can be composed of one physical entity. Generally speaking, the air conditioning smart energy-saving device in the subway station can be a control device such as a subway air conditioning background system.

[0046] The following description takes the subway air conditioning background system as the main body of the air conditioning smart energy saving method in the subway station as an example. Figure 1 The smart energy-saving methods for air conditioning in this subway station include:

[0047] S110. Obtain historical surveillance videos of different time periods in the subway station, analyze historical passenger flow data of the target area at different time periods based on the historical surveillance videos, determine the idle passenger flow period of the target area according to the historical passenger flow data, and determine the historical average passenger flow of the target area during the idle passenger flow period according to the historical passenger flow data.

[0048] Reference Figure 2,The background system 11 realizes air conditioning control by interacting with each air conditioner 12 in the station. At the same time, the ,station monitoring video is collected by interacting with the station camera 13 and the ,station monitoring system 14 to collect historical monitoring video, and then dynamically adjust the ,air conditioning temperature and air conditioning wind speed of each air conditioner 12 in the station during the ,idle period according to the changes of the historical average passenger flow and the real-time passenger flow.

[0049] Among them, the passenger flow data is analyzed by obtaining historical surveillance videos to determine the idle passenger flow period and the historical average passenger flow. First, the background system obtains the surveillance video data of the past period of time (such as one year or longer) by accessing the monitoring system of the subway station. These data should cover all key areas in the subway station, such as platforms, passages, transfer areas, etc. Since the amount of video data may be very large, it is necessary to screen and classify the videos according to the time period to be analyzed (such as different time periods of the day, such as morning, noon, evening, late night or hourly segments, etc.).

[0050] Then, computer vision and image processing technologies are used to analyze the selected surveillance videos. These technologies include face recognition, human body detection, and tracking to count the number of people in the video. By marking and tracking individuals in the video frames, for each target area and each time period, the number of people entering and leaving the area, as well as the number of people staying in the area, is counted. The passenger flow data obtained is then organized into a table or database format for subsequent analysis and processing.

[0051] Conduct in-depth analysis of the collated historical passenger flow data to identify the passenger flow change trends in each target area at different time periods. According to the level of passenger flow, the time period is divided into peak time period and idle time period. Idle time period is defined as a time period when the passenger flow is significantly lower than the average level. If the passenger flow is lower than a certain threshold K, the time period is determined to be idle time period. Identify the idle time period of passenger flow in each target area and record the specific time range of these time periods.

[0052] For each idle period in each target area, calculate the average passenger flow of all historical dates in that period. The average passenger flow is obtained by adding up all passenger flows in the idle period and then dividing by the number of days in the idle period. The calculated historical average passenger flow is recorded as a basis for subsequent adjustment of air conditioning control parameters.

[0053] Optionally, historical passenger flow data of the target area at different time periods is analyzed based on historical surveillance videos, including:

[0054] Perform target detection in the target area based on historical surveillance videos, count the number of targets detected in different time periods, and use the number of targets as the historical passenger flow data for the corresponding time period.

[0055] By pre-training and reasoning the target detection model, passenger flow counting can be performed based on video data. Prior to this, historical surveillance video data of the target area is collected. This data covers different time periods, weather conditions, and traffic volume to ensure the generalization ability of the model. Each frame or key frame in the video is annotated to mark the target to be detected (such as pedestrians). Select a deep learning model suitable for the target detection task, such as YOLO, SSD, Faster R-CNN, etc. These models have strong feature extraction and target localization capabilities. The model is trained using the annotated data. During the training process, the model learns how to identify the target in the video and predict its location and category. The training includes multiple iterations, and each cycle adjusts the parameters of the model to optimize the detection performance. Then, the performance of the model is evaluated using an independent test set, including indicators such as accuracy, recall, and F1 score. According to the evaluation results, the model structure, hyperparameters, or training strategies are adjusted to improve the detection accuracy and efficiency of the model.

[0056] Afterwards, when performing target detection on the target area based on the historical surveillance video, the historical surveillance video file of the target area is loaded and decomposed into individual frames. Each frame is preprocessed, such as resizing and normalization, to meet the requirements of the model input. The preprocessed frames are used for target detection using the trained model. The model outputs the bounding box, category, and confidence of each detected target. Low-confidence detection results are filtered out based on the confidence threshold to improve the accuracy of the detection. The detection results of all frames in the same period are aggregated to count the total number of targets detected in the period (e.g., by accumulating the number of targets in each frame and removing duplicate targets).

[0057] The video data is divided into different time periods according to the time granularity to be analyzed (such as every hour, every half hour, etc.). For each time period, the target total obtained by aggregation in the previous step is used as the historical passenger flow data for that time period. By setting a passenger flow threshold, the time period below the threshold is considered to be an idle time period.

[0058] Optionally, refer to Figure 3 , determine the idle passenger flow period in the target area based on historical passenger flow data, including:

[0059] S1101, determining a period in which the historical passenger flow data is lower than a set threshold as an idle sub-period, and the length of the idle sub-period is fixed;

[0060] S1102: When the number of the continuously detected idle sub-periods reaches a set value, the continuously detected idle sub-periods are determined as passenger flow idle periods in the target area.

[0061] Based on the passenger flow threshold set above, the threshold is determined comprehensively based on historical passenger flow data, business needs, site capacity and other factors. This threshold represents the minimum passenger flow that the target area should reach in the "non-idle" state. Then analyze the historical passenger flow data, divide each day (or the set analysis period) into multiple time periods (such as every hour, every half hour, etc.), and calculate the average passenger flow or cumulative passenger flow in each time period. For each time period, compare the actual measured passenger flow with the set threshold.

[0062] If the passenger flow in a certain time period is lower than the set threshold, the time period is regarded as an idle sub-period, which means that the passenger flow in this period is relatively small. The length of the idle sub-period is fixed and determined by the granularity of the time period division. For example, if a day is divided into 24 hours and each hour is a time period, the length of the idle sub-period is 1 hour. If the analysis granularity is finer (such as every half hour), the length of the idle sub-period is shortened accordingly. After determining all the idle sub-periods, it is necessary to further analyze whether these idle sub-periods appear continuously and whether the number of consecutive occurrences reaches a certain set value.

[0063] If the number of consecutively detected idle sub-periods reaches the set threshold (for example, 2, 3 or more consecutive hours), these consecutive idle sub-periods are merged into a longer passenger flow idle period. This setting value is also determined based on business needs, site characteristics, operation mode and other factors, aiming to more accurately reflect the actual passenger flow conditions in the target area during a specific time period. In summary, by setting passenger flow thresholds, analyzing historical passenger flow data, identifying idle sub-periods and determining passenger flow idle periods, it can provide strong data support for the air conditioning operation management of the target area, promote the rational allocation and efficient use of resources, and then accurately accumulate the historical average passenger flow of each passenger flow idle period.

[0064] S120: setting initial air-conditioning control parameters of the target area during the idle passenger flow period based on the historical average passenger flow, and controlling the air-conditioning temperature and air-conditioning wind speed of the target area according to the initial air-conditioning control parameters at the initial moment of the idle passenger flow period.

[0065] Furthermore, based on the historical average passenger flow, the initial air-conditioning control parameters in the idle passenger flow period can be set, mainly including the air-conditioning temperature and the air-conditioning wind speed. It is understandable that even in the idle passenger flow period, a certain level of comfort needs to be maintained to avoid causing discomfort to passengers who occasionally enter. At the same time, when the passenger flow is small, the air-conditioning parameters can be appropriately adjusted to save energy. For example, the air-conditioning temperature and wind speed can be lowered to reduce energy consumption. In addition, the initial air-conditioning control parameters can be comprehensively configured by considering the influence of factors such as the area, height, orientation, and thermal insulation performance of the target area. For example, by setting the mapping relationship between different historical average passenger flows and the initial air-conditioning control parameters, the corresponding initial air-conditioning control parameters can be obtained by querying the preset mapping relationship according to the value of the historical average passenger flow.

[0066] Then, at the initial moment of the idle passenger flow period, the air conditioning temperature and air conditioning wind speed of the target area are controlled according to the set initial air conditioning control parameters. Through the above steps, the initial air conditioning control parameters of the target area during the idle passenger flow period can be set based on the historical average passenger flow to achieve a balance between energy efficiency and passenger comfort and save energy consumption.

[0067] Optionally, before the initial moment of the passenger flow idle period, it also includes:

[0068] It is detected that the current time is less than the set time from the initial time of the passenger flow idle period, and a smooth transition adjustment is made to the initial air-conditioning control parameters based on the real-time air-conditioning control parameters of the current target area.

[0069] Before the initial moment of the idle period, in order to ensure the smooth transition of the air conditioning system and avoid discomfort to passengers caused by sudden changes in temperature and wind speed, a smooth transition adjustment strategy can be adopted. First, a smooth transition duration is set, which represents the period from the current moment to the initial moment of the idle period, and is used to gradually adjust the air conditioning control parameters. This duration can be set according to the response speed of the air conditioning system, the thermal inertia of the indoor environment, and the comfort perception of the passengers.

[0070] When the system detects that the current time is less than the set smooth transition time from the initial time of the passenger flow idle period, the smooth transition adjustment mechanism will be triggered. At this time, the system will obtain the real-time air conditioning control parameters (including air conditioning temperature and air conditioning wind speed) of the current target area. Based on the difference between the real-time air conditioning control parameters and the initial air conditioning control parameters, the temperature and wind speed that need to be adjusted in each time step (such as every minute, every second) are calculated. This adjustment amount should be gradually reduced to ensure that the air conditioning control parameters can smoothly transition to the initial value at the end of the smooth transition time.

[0071] Based on the calculated adjustment amount, the system begins to gradually adjust the air conditioning control parameters. This adjustment process is continuous, and the adjustment speed is moderate to avoid giving passengers a noticeable sense of temperature change. At the same time, the system continuously monitors indoor environmental parameters (such as temperature, humidity) and passenger comfort feedback (if any) to make fine adjustments when necessary. When the smooth transition duration ends, the air conditioning control parameters smoothly transition to the initial values. At this point, the system will continue to operate according to the initial air conditioning control parameters until the next adjustment cycle or the passenger flow status changes. By implementing the above smooth transition adjustment strategy, it can be ensured that the control parameters of the air conditioning system can smoothly transition to the initial values ​​at the beginning of the passenger flow idle period, thereby avoiding discomfort to passengers and improving energy efficiency.

[0072] S130. During the idle passenger flow period, collect the real-time incoming passenger flow, arriving passenger flow and real-time passenger flow in the target area based on the station monitoring video, predict the passenger flow change in the target area based on the correlation between the incoming passenger flow, arriving passenger flow and the station path of the target area, determine the predicted passenger flow of the target area based on the real-time passenger flow and the passenger flow change, and when the passenger flow difference between the predicted passenger flow and the historical average passenger flow reaches a set threshold, configure the air-conditioning temperature adjustment amount and the air-conditioning wind speed adjustment amount according to the passenger flow difference, and adjust the air-conditioning temperature and air-conditioning wind speed of the target area according to the air-conditioning temperature adjustment amount and the air-conditioning wind speed adjustment amount.

[0073] Furthermore, during periods of idle passenger flow, in order to more accurately control the air-conditioning temperature and wind speed in the target area to adapt to the real-time changes in passenger flow, the in-station monitoring video and data analysis technology can be combined to predict and adjust the air-conditioning parameters.

[0074] Among them, the passenger flow entering the subway station is collected in real time through the surveillance video in the station. The passenger flow arriving at each platform is also recorded by using the surveillance video. The statistics of passenger flow refer to the passenger flow statistics method based on historical surveillance video mentioned above, which will not be elaborated here.

[0075] Then, based on historical data and passenger behavior patterns, the path correlation between the incoming passenger flow, the arriving passenger flow and the target area is analyzed. For example, by counting the flow paths and frequencies of passengers from the station entrance to the target area in different time periods. Using the above correlation information, combined with real-time incoming passenger flow and arriving passenger flow data, the change in passenger flow in the target area in the future can be predicted. For example, by establishing mathematical models (such as time series analysis, machine learning models, etc.) to predict the change in passenger flow.

[0076] More specifically, by collecting the real-time passenger flow data of the inbound passenger flow, the arrival passenger flow and the target area over a period of time in the past (such as weeks, months or years). These data should include information such as timestamp, passenger flow, entrance / platform identification, target area identification, etc. Collect passenger behavior data in the station through surveillance video, such as walking path, stay time, etc. After removing duplicate records and erroneous data, integrate data from different sources (such as inbound passenger flow, arrival passenger flow, passenger behavior data) into a unified data set. Convert the data into a format suitable for analysis, such as time series data.

[0077] Then, the surveillance video analysis is used to identify the flow path of passengers from the entrance / platform to the target area. The frequency of use of each path in different time periods (such as peak hours, off-peak hours, and low-peak hours) is counted.

[0078] For each entrance / platform, calculate the path relevance from it to the target area. The relevance formula is:

[0079]

[0080] Then select the key factors that affect the passenger flow in the target area as the model input features, such as real-time inbound passenger flow, real-time arrival passenger flow and correlation data. Select a suitable mathematical model according to the characteristics of the data and the prediction requirements. The model can be a time series analysis (such as ARI MA, seasonal decomposition, etc.), a machine learning model (such as random forest, gradient boosting tree, neural network, etc.). Use the above historical data to train the model and adjust the model parameters to optimize the prediction performance. Evaluate the model performance, such as using methods such as cross-validation to test the generalization ability of the model.

[0081] Afterwards, the inbound and arrival passenger flow data are collected in real time and input into the trained model. Since the model is trained based on the correlation between the inbound and arrival passenger flow and the station paths in the target area, the passenger flow changes in the target area in the future can be predicted based on the real-time inbound and arrival passenger flow data.

[0082] Then, the predicted passenger flow in the target area is obtained by adding the real-time passenger flow in the target area to the predicted passenger flow change and subtracting the set passenger flow attenuation between the current time and the predicted period. The difference between the predicted passenger flow and the historical average passenger flow is calculated. This difference reflects the degree of deviation of the current passenger flow from the historical average level. If the passenger flow difference reaches or exceeds the set threshold, it means that there is a significant difference between the current passenger flow and the historical average level, and the air conditioning parameters need to be adjusted to adapt to this change.

[0083] According to the size and direction of the passenger flow difference (a positive difference indicates an increase in passenger flow, and a negative difference indicates a decrease in passenger flow), configure the corresponding air conditioning temperature adjustment and air conditioning wind speed adjustment. Generally speaking, when the passenger flow increases, the temperature should be appropriately lowered and the wind speed should be increased to improve comfort; when the passenger flow decreases, the temperature can be increased and the wind speed can be reduced accordingly to save energy. The configured air conditioning temperature adjustment and air conditioning wind speed adjustment are sent to the air conditioning system for execution to achieve real-time adjustment of the air conditioning parameters in the target area. During the adjustment process, the real-time passenger flow and air conditioning system operating status of the target area are continuously monitored to ensure that the adjustment effect meets expectations.

[0084] Through the above process, intelligent adjustment of the air-conditioning parameters in the target area can be achieved to better adapt to the real-time changing passenger flow demand and improve the comfort of passengers and the operational efficiency of the subway station.

[0085] Optionally, refer to Figure 4 , based on the correlation between the incoming passenger flow, the arriving passenger flow and the in-station path of the target area, the passenger flow change in the target area is predicted, including:

[0086] S1301, calculating a first passenger flow increment in a target area during a target period based on the correlation between the incoming passenger flow and the in-station path of the target area;

[0087] S1302, calculating a second passenger flow increment in the target area during the target period based on the correlation between the passenger flow arriving at the station and the path within the target area;

[0088] S1303: Taking the sum of the first passenger flow increment and the second passenger flow increment as the passenger flow change of the target area.

[0089] It can be understood that the in-station path correlation is calculated based on historical passenger flow information, indicating the impact of inbound passenger flow and outbound passenger flow on the passenger flow of the target area during the forecast period. Therefore, based on the inbound passenger flow and the in-station path correlation of the target area, the number of inbound passengers arriving at the target area during the forecast period can be calculated, which is defined as the first passenger flow increment; based on the outbound passenger flow and the in-station path correlation of the target area, the number of outbound passengers arriving at the target area during the forecast period can be calculated, which is defined as the second passenger flow increment. The sum of the two is the passenger flow change in the target area.

[0090] Optionally, adjusting the air conditioning temperature and the air conditioning wind speed of the target area according to the air conditioning temperature adjustment amount and the air conditioning wind speed adjustment amount includes:

[0091] During the set adjustment period, the air-conditioning temperature and air-conditioning wind speed of the target area are adjusted according to the set step size until the air-conditioning temperature adjustment value of the target area reaches the air-conditioning temperature adjustment amount, and the air-conditioning wind speed adjustment value of the target area reaches the air-conditioning wind speed adjustment amount.

[0092] In order to adjust the air conditioning temperature and wind speed of the target area according to the air conditioning temperature adjustment amount and the air conditioning wind speed adjustment amount, a control process is designed so that the process can gradually adjust the temperature and wind speed with a set step size within a set adjustment period until the predetermined adjustment amount is reached respectively.

[0093] Among them, by initializing parameters, the current air-conditioning temperature (current_temp) and wind speed (current_speed) of the target area are set; the target adjustment amount is set, including the temperature adjustment amount (temp_adjustment) and wind speed adjustment amount (speed_adjustment); the adjustment period (adjustment_durat i on), step length (step_durat i on), and the temperature step length (temp_step) and wind speed step length (speed_step) of each adjustment are set. Then, according to the adjustment amount and step length, the number of adjustments required (rounded up) is calculated to ensure that at least the adjustment amount is reached.

[0094] During the set adjustment period, the system cycles with the set step length. In each cycle, it checks whether the target adjustment amount has been reached or exceeded. If not, the temperature and wind speed are adjusted according to the step length. If reached or exceeded, further adjustments are stopped (or the temperature / wind speed can be set to the exact target value). When the adjustment period ends or all adjustments are completed, the final temperature and wind speed values ​​are recorded to complete the real-time adjustment of the air conditioning temperature and air conditioning wind speed.

[0095] Optionally, after adjusting the air conditioning temperature and the air conditioning wind speed of the target area according to the air conditioning temperature adjustment amount and the air conditioning wind speed adjustment amount, the method further includes:

[0096] After a set number of consecutive adjustment cycles, it is detected that the real-time passenger flow reaches the set passenger flow threshold, and the current target area is determined to jump out of the passenger flow idle period, and the set conventional passenger flow air conditioning adjustment logic is called to control the air conditioning of the current target area.

[0097] After adjusting the air conditioning temperature and wind speed of the target area according to the air conditioning temperature adjustment amount and the air conditioning wind speed adjustment amount, if the system detects that the real-time passenger flow reaches or exceeds the set passenger flow threshold within a set number of adjustment cycles, it is considered that the current target area has jumped out of the passenger flow idle period. At this time, the set regular passenger flow air conditioning adjustment logic should be called to perform air conditioning control.

[0098] Among them, the background system initializes parameters, including the number of adjustment cycles, the duration of each adjustment cycle, the passenger flow threshold, the real-time passenger flow monitoring function, etc. Then, the temperature and wind speed adjustment is performed, and the air conditioning temperature and wind speed are adjusted according to the previous logic. At the end of each adjustment cycle, the real-time passenger flow monitoring function is called to obtain the current passenger flow data. If the real-time passenger flow reaches or exceeds the set passenger flow threshold within a set number of adjustment cycles, the next step is executed. Otherwise, continue to monitor the passenger flow of the next adjustment cycle. Then, the conventional passenger flow air conditioning adjustment logic is called. Once it is determined that the target area has jumped out of the passenger flow idle period, the preset conventional passenger flow air conditioning adjustment logic is called to control the air conditioning, so as to improve the stability and reliability of air conditioning control, and provide comfortable air conditioning control effects in a timely manner under conventional passenger flow conditions.

[0099] In the above, by acquiring historical surveillance videos of different time periods in the subway station, analyzing historical passenger flow data of the target area at different time periods based on the historical surveillance videos, determining the idle passenger flow period of the target area based on the historical passenger flow data, and determining the historical average passenger flow of the target area during the idle passenger flow period based on the historical passenger flow data; setting the initial air-conditioning control parameters of the target area during the idle passenger flow period based on the historical average passenger flow, and controlling the air-conditioning temperature and air-conditioning wind speed of the target area according to the initial air-conditioning control parameters at the initial moment of the idle passenger flow period; collecting the real-time inbound passenger flow, the arrival passenger flow and the real-time passenger flow of the target area based on the in-station surveillance video during the idle passenger flow period, predicting the passenger flow change of the target area based on the correlation between the inbound passenger flow, the arrival passenger flow and the in-station path of the target area, determining the predicted passenger flow of the target area based on the real-time passenger flow and the passenger flow change, and when the passenger flow difference between the predicted passenger flow and the historical average passenger flow reaches a set threshold, configuring the air-conditioning temperature adjustment amount and the air-conditioning wind speed adjustment amount according to the passenger flow difference, and adjusting the air-conditioning temperature and air-conditioning wind speed of the target area according to the air-conditioning temperature adjustment amount and the air-conditioning wind speed adjustment amount. By adopting the above-mentioned technical means, the air-conditioning temperature and air-conditioning wind speed during idle periods are dynamically adjusted by combining the historical average passenger flow and the changes in real-time passenger flow. This can make the air-conditioning control meet the real-time passenger flow demand, realize precise control of the air-conditioning in the station, save energy consumption during idle periods, and reduce the operating costs in the station.

[0100] Embodiment 2:

[0101] Based on the above embodiments, Figure 5 This is a schematic diagram of the structure of an intelligent energy-saving device for air conditioning in a subway station provided in Example 2 of the present application. Figure 5 The air conditioning intelligent energy-saving device in the subway station provided in this embodiment specifically includes: an idle period determination module 21, an initial adjustment module 22 and a real-time adjustment module 23.

[0102] The idle period determination module 21 is used to obtain historical surveillance videos of different periods in the subway station, analyze historical passenger flow data of the target area at different periods based on the historical surveillance videos, determine the passenger flow idle period of the target area according to the historical passenger flow data, and determine the historical average passenger flow of the target area during the passenger flow idle period according to the historical passenger flow data;

[0103] The initial adjustment module 22 is used to set the initial air conditioning control parameters of the target area in the idle passenger flow period based on the historical average passenger flow, and control the air conditioning temperature and air conditioning wind speed of the target area according to the initial air conditioning control parameters at the initial moment of the idle passenger flow period;

[0104] The real-time adjustment module 23 is used to collect real-time inbound passenger flow, arrival passenger flow and real-time passenger flow of the target area based on the in-station monitoring video during the idle passenger flow period, predict the passenger flow change of the target area based on the correlation between the inbound passenger flow, arrival passenger flow and the in-station path of the target area, determine the predicted passenger flow of the target area according to the real-time passenger flow and the passenger flow change, and when the passenger flow difference between the predicted passenger flow and the historical average passenger flow reaches a set threshold, configure the air-conditioning temperature adjustment amount and the air-conditioning wind speed adjustment amount according to the passenger flow difference, and adjust the air-conditioning temperature and air-conditioning wind speed of the target area according to the air-conditioning temperature adjustment amount and the air-conditioning wind speed adjustment amount.

[0105] Specifically, the analyzing the historical passenger flow data of the target area at different time periods based on the historical surveillance video includes:

[0106] Based on the historical surveillance video, target detection is performed on the target area, the number of targets detected in different time periods is counted, and the number of targets is used as the historical passenger flow data of the corresponding time period.

[0107] Specifically, determining the idle passenger flow period of the target area according to the historical passenger flow data includes:

[0108] Determine a time period in which the historical passenger flow data is lower than a set threshold as an idle sub-period, wherein the length of the idle sub-period is fixed;

[0109] When the number of the continuously detected idle sub-periods reaches a set value, the continuously detected idle sub-periods are determined as passenger flow idle periods of the target area.

[0110] Specifically, before the initial moment of the passenger flow idle period, the method further includes:

[0111] It is detected that the current time is less than a set time from the initial time of the passenger flow idle period, and a smooth transition adjustment is performed to the initial air-conditioning control parameters based on the current real-time air-conditioning control parameters of the target area.

[0112] Specifically, the predicting the passenger flow change amount of the target area based on the correlation between the incoming passenger flow, the arriving passenger flow and the in-station path of the target area includes:

[0113] Calculate a first passenger flow increment of the target area during a target period based on the correlation between the incoming passenger flow and the in-station path of the target area;

[0114] Calculate a second passenger flow increment of the target area during a target period based on the correlation between the passenger flow arriving at the station and the path within the station of the target area;

[0115] The sum of the first passenger flow increment and the second passenger flow increment is taken as the passenger flow change of the target area.

[0116] Specifically, adjusting the air conditioning temperature and the air conditioning wind speed of the target area according to the air conditioning temperature adjustment amount and the air conditioning wind speed adjustment amount includes:

[0117] During the set adjustment period, the air-conditioning temperature and air-conditioning wind speed of the target area are adjusted according to the set step size until the adjustment value of the air-conditioning temperature of the target area reaches the air-conditioning temperature adjustment amount, and the adjustment value of the air-conditioning wind speed of the target area reaches the air-conditioning wind speed adjustment amount.

[0118] Specifically, after adjusting the air conditioning temperature and the air conditioning wind speed of the target area according to the air conditioning temperature adjustment amount and the air conditioning wind speed adjustment amount, the method further includes:

[0119] The real-time passenger flow is detected to reach the set passenger flow threshold value after a set number of consecutive adjustment cycles, and it is determined that the current target area jumps out of the passenger flow idle period, and the set conventional passenger flow air conditioning adjustment logic is called to perform air conditioning control of the current target area.

[0120] In the above, by acquiring historical surveillance videos of different time periods in the subway station, analyzing historical passenger flow data of the target area at different time periods based on the historical surveillance videos, determining the idle passenger flow period of the target area based on the historical passenger flow data, and determining the historical average passenger flow of the target area during the idle passenger flow period based on the historical passenger flow data; setting the initial air-conditioning control parameters of the target area during the idle passenger flow period based on the historical average passenger flow, and controlling the air-conditioning temperature and air-conditioning wind speed of the target area according to the initial air-conditioning control parameters at the initial moment of the idle passenger flow period; collecting the real-time inbound passenger flow, the arrival passenger flow and the real-time passenger flow of the target area based on the in-station surveillance video during the idle passenger flow period, predicting the passenger flow change of the target area based on the correlation between the inbound passenger flow, the arrival passenger flow and the in-station path of the target area, determining the predicted passenger flow of the target area based on the real-time passenger flow and the passenger flow change, and when the passenger flow difference between the predicted passenger flow and the historical average passenger flow reaches a set threshold, configuring the air-conditioning temperature adjustment amount and the air-conditioning wind speed adjustment amount according to the passenger flow difference, and adjusting the air-conditioning temperature and air-conditioning wind speed of the target area according to the air-conditioning temperature adjustment amount and the air-conditioning wind speed adjustment amount. By adopting the above-mentioned technical means, the air-conditioning temperature and air-conditioning wind speed during idle periods are dynamically adjusted by combining the historical average passenger flow and the changes in real-time passenger flow. This can make the air-conditioning control meet the real-time passenger flow demand, realize precise control of the air-conditioning in the station, save energy consumption during idle periods, and reduce the operating costs in the station.

[0121] The intelligent energy-saving device for air conditioning in a subway station provided in Example 2 of the present application can be used to execute the intelligent energy-saving method for air conditioning in a subway station provided in Example 1 above, and has corresponding functions and beneficial effects.

[0122] Embodiment three:

[0123] Embodiment 3 of the present application provides an electronic device, referring to Figure 6 The electronic device includes: a processor 31, a memory 32, a communication module 33, an input device 34 and an output device 35. The number of processors in the electronic device can be one or more, and the number of memories in the electronic device can be one or more. The processor, memory, communication module, input device and output device of the electronic device can be connected via a bus or other means.

[0124] As a computer-readable storage medium, the memory can be used to store software programs, computer executable programs and modules, such as the program instructions / modules corresponding to the air conditioning smart energy-saving method in the subway station described in any embodiment of the present application (for example, the idle period determination module, the initial adjustment module and the real-time adjustment module in the air conditioning smart energy-saving device in the subway station). The memory may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the device, etc. In addition, the memory may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some instances, the memory may further include a memory remotely arranged relative to the processor, and these remote memories may be connected to the device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network and a combination thereof.

[0125] The communication module is used for data transmission.

[0126] The processor executes various functional applications and data processing of the device by running software programs, instructions and modules stored in the memory, thereby realizing the above-mentioned intelligent energy-saving method for air conditioning in subway stations.

[0127] The input device can be used to receive input digital or character information and generate key signal input related to user settings and function control of the device. The output device can include display devices such as display screens.

[0128] The electronic device provided above can be used to execute the intelligent energy-saving method for air conditioning in a subway station provided in the above-mentioned embodiment 1, and has corresponding functions and beneficial effects.

[0129] Embodiment 4:

[0130] The embodiment of the present application also provides a storage medium containing computer executable instructions, which, when executed by a computer processor, are used to execute an intelligent energy-saving method for air conditioning in a subway station. The intelligent energy-saving method for air conditioning in the subway station comprises: obtaining historical surveillance videos of different time periods in the subway station, analyzing historical passenger flow data of a target area in different time periods based on the historical surveillance videos, determining a passenger flow idle period of the target area based on the historical passenger flow data, and determining a historical average passenger flow of the target area during the passenger flow idle period based on the historical passenger flow data; setting initial air conditioning control parameters for the target area during the passenger flow idle period based on the historical average passenger flow, and setting the initial air conditioning control parameters for the target area during the passenger flow idle period At the start moment, the air-conditioning temperature and the air-conditioning wind speed of the target area are controlled according to the initial air-conditioning control parameters; during the idle passenger flow period, the real-time inbound passenger flow, the arrival passenger flow and the real-time passenger flow of the target area are collected based on the in-station monitoring video, the passenger flow change of the target area is predicted based on the correlation between the inbound passenger flow, the arrival passenger flow and the in-station path of the target area, the predicted passenger flow of the target area is determined according to the real-time passenger flow and the passenger flow change, and when the passenger flow difference between the predicted passenger flow and the historical average passenger flow reaches a set threshold, the air-conditioning temperature adjustment amount and the air-conditioning wind speed adjustment amount are configured according to the passenger flow difference, and the air-conditioning temperature and the air-conditioning wind speed of the target area are adjusted according to the air-conditioning temperature adjustment amount and the air-conditioning wind speed adjustment amount.

[0131] Storage medium - any of various types of memory devices or storage devices. The term "storage medium" is intended to include: installation media, such as CD-ROM, floppy disk or tape device; computer system memory or random access memory, such as DRAM, DDR RAM, SRAM, EDO RAM, Rambus RAM, etc.; non-volatile memory, such as flash memory, magnetic media (such as hard disk or optical storage); registers or other similar types of memory elements, etc. Storage media may also include other types of memory or combinations thereof. In addition, the storage medium may be located in the first computer system in which the program is executed, or may be located in a different second computer system, which is connected to the first computer system via a network (such as the Internet). The second computer system can provide program instructions to the first computer for execution. The term "storage medium" may include two or more storage media residing in different locations (for example, in different computer systems connected by a network). The storage medium may store program instructions (for example, embodied as a computer program) that can be executed by one or more processors.

[0132] Of course, the storage medium containing computer executable instructions provided in the embodiment of the present application, whose computer executable instructions are not limited to the intelligent energy-saving method for air conditioning in the subway station as described above, can also execute related operations in the intelligent energy-saving method for air conditioning in the subway station provided in any embodiment of the present application.

[0133] The intelligent energy-saving device, storage medium and electronic device for air conditioning in the subway station provided in the above embodiments can execute the intelligent energy-saving method for air conditioning in the subway station provided in any embodiment of the present application. For technical details not described in detail in the above embodiments, please refer to the intelligent energy-saving method for air conditioning in the subway station provided in any embodiment of the present application.

[0134] The above are only preferred embodiments of the present application and the technical principles used. The present application is not limited to the specific embodiments described herein, and various obvious changes, readjustments and substitutions that can be made by those skilled in the art will not deviate from the scope of protection of the present application. Therefore, although the present application is described in more detail through the above embodiments, the present application is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present application, and the scope of the present application is determined by the scope of the claims.

Claims

1. An intelligent energy-saving method for air conditioning in a subway station, characterized in that: include: Obtain historical surveillance videos of different time periods in the subway station, analyze historical passenger flow data of a target area at different time periods based on the historical surveillance videos, determine a passenger flow idle period of the target area according to the historical passenger flow data, and determine a historical average passenger flow of the target area during the passenger flow idle period according to the historical passenger flow data; Setting initial air-conditioning control parameters of the target area during the idle passenger flow period based on the historical average passenger flow, and controlling the air-conditioning temperature and air-conditioning wind speed of the target area according to the initial air-conditioning control parameters at the initial moment of the idle passenger flow period; During the idle passenger flow period, real-time inbound passenger flow, arrival passenger flow and real-time passenger flow in the target area are collected based on the in-station surveillance video, and the passenger flow change in the target area is predicted based on the correlation between the inbound passenger flow, arrival passenger flow and the in-station path of the target area. The predicted passenger flow of the target area is determined based on the real-time passenger flow and the passenger flow change. When the passenger flow difference between the predicted passenger flow and the historical average passenger flow reaches a set threshold, the air-conditioning temperature adjustment amount and the air-conditioning wind speed adjustment amount are configured according to the passenger flow difference, and the air-conditioning temperature and air-conditioning wind speed of the target area are adjusted according to the air-conditioning temperature adjustment amount and the air-conditioning wind speed adjustment amount.

2. The intelligent energy-saving method for air conditioning in a subway station according to claim 1, characterized in that: The analyzing the historical passenger flow data of the target area at different time periods based on the historical surveillance video includes: Based on the historical surveillance video, target detection is performed on the target area, the number of targets detected in different time periods is counted, and the number of targets is used as the historical passenger flow data of the corresponding time period.

3. The intelligent energy-saving method for air conditioning in a subway station according to claim 1, characterized in that: The step of determining the idle passenger flow period of the target area according to the historical passenger flow data includes: Determine a time period in which the historical passenger flow data is lower than a set threshold as an idle sub-period, wherein the length of the idle sub-period is fixed; When the number of the continuously detected idle sub-periods reaches a set value, the continuously detected idle sub-periods are determined as passenger flow idle periods of the target area.

4. The intelligent energy-saving method for air conditioning in a subway station according to claim 1, characterized in that: Before the initial moment of the passenger flow idle period, the method further includes: It is detected that the current time is less than a set time from the initial time of the passenger flow idle period, and a smooth transition adjustment is performed to the initial air-conditioning control parameters based on the current real-time air-conditioning control parameters of the target area.

5. The intelligent energy-saving method for air conditioning in a subway station according to claim 1, characterized in that: The predicting of the passenger flow change of the target area based on the correlation between the incoming passenger flow, the arriving passenger flow and the in-station path of the target area includes: Calculate a first passenger flow increment of the target area during a target period based on the correlation between the incoming passenger flow and the in-station path of the target area; Calculate a second passenger flow increment of the target area during a target period based on the correlation between the passenger flow arriving at the station and the path within the station of the target area; The sum of the first passenger flow increment and the second passenger flow increment is taken as the passenger flow change of the target area.

6. The intelligent energy-saving method for air conditioning in a subway station according to claim 1, characterized in that: The step of adjusting the air conditioning temperature and the air conditioning wind speed of the target area according to the air conditioning temperature adjustment amount and the air conditioning wind speed adjustment amount includes: During the set adjustment period, the air-conditioning temperature and air-conditioning wind speed of the target area are adjusted according to the set step size until the adjustment value of the air-conditioning temperature of the target area reaches the air-conditioning temperature adjustment amount, and the adjustment value of the air-conditioning wind speed of the target area reaches the air-conditioning wind speed adjustment amount.

7. The intelligent energy-saving method for air conditioning in a subway station according to claim 1, characterized in that: After adjusting the air conditioning temperature and the air conditioning wind speed of the target area according to the air conditioning temperature adjustment amount and the air conditioning wind speed adjustment amount, the method further includes: The real-time passenger flow is detected to reach the set passenger flow threshold value after a set number of consecutive adjustment cycles, and it is determined that the current target area jumps out of the passenger flow idle period, and the set conventional passenger flow air conditioning adjustment logic is called to perform air conditioning control of the current target area.

8. An intelligent energy-saving device for air conditioning in a subway station, characterized in that: include: An idle period determination module is used to obtain historical surveillance videos of different periods in the subway station, analyze historical passenger flow data of the target area at different periods based on the historical surveillance videos, determine the passenger flow idle period of the target area according to the historical passenger flow data, and determine the historical average passenger flow of the target area during the passenger flow idle period according to the historical passenger flow data; An initial adjustment module, configured to set initial air conditioning control parameters of the target area during the idle passenger flow period based on the historical average passenger flow, and control the air conditioning temperature and air conditioning wind speed of the target area according to the initial air conditioning control parameters at the initial moment of the idle passenger flow period; A real-time adjustment module is used to collect real-time inbound passenger flow, arrival passenger flow and real-time passenger flow of the target area based on the station monitoring video during the idle passenger flow period, predict the passenger flow change of the target area based on the correlation between the inbound passenger flow, arrival passenger flow and the station path of the target area, determine the predicted passenger flow of the target area according to the real-time passenger flow and the passenger flow change, and when the passenger flow difference between the predicted passenger flow and the historical average passenger flow reaches a set threshold, configure the air-conditioning temperature adjustment amount and the air-conditioning wind speed adjustment amount according to the passenger flow difference, and adjust the air-conditioning temperature and air-conditioning wind speed of the target area according to the air-conditioning temperature adjustment amount and the air-conditioning wind speed adjustment amount.

9. An electronic device, characterized in that: include: memory and one or more processors; The memory is used to store one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the intelligent energy-saving method for air conditioning in a subway station as described in any one of claims 1-7.

10. A storage medium containing computer executable instructions, characterized in that: The computer executable instructions, when executed by a computer processor, are used to execute the intelligent energy-saving method for air conditioning in a subway station as described in any one of claims 1-7.

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