Electronic station advertisement playing method, device and equipment and storage medium

Abstract

The invention discloses an electronic station advertisement playing method, device and equipment and a storage medium. The method comprises the steps of obtaining passenger getting-on and getting-off information data, advertisement playing request data, bus getting-on arrival and departure data and bus operation data; determining an advertisement priority list according to the advertisement playing request data; calculating the user granularity in the time period according to the passenger getting-on and getting-off information data and the bus getting-on arrival and departure data; according to the bus operation data, obtaining the average number of passengers at each station on the same bus line; obtaining a station priority coefficient according to the average passenger number of each station in combination with a preset line priority coefficient; determining the advertisement playing time of each site according to the user granularity and the site priority coefficient; and putting advertisements according to the sequence of the advertisement priority list within the advertisement playing time. According to the method, the advertisement putting sequence can be arranged according to the actual bus operation condition and the passenger number, and efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the field of multimedia technology, and in particular to an electronic station advertisement playing method, device, electronic equipment and storage medium. Background Art

[0002] The development and popularization of public transportation is of great significance to avoiding "urban diseases", but with limited public transportation resources, public transportation resources often cannot meet people's growing needs. To this end, innovation and reform are necessary to develop a variety of public transportation systems, including ground public transportation, rail transportation, water transportation, etc., while improving the service level of public transportation.

[0003] As the main component of the ground public transportation system, buses are of great significance to people's daily travel. In order to improve people's satisfaction with public transportation, designing and using bus stop advertising systems on buses is a promising option.

[0004] Traditional bus advertising often requires advertisers to choose the time and method of delivery themselves, but people's subjective judgment often fails to achieve good advertising effects. At the same time, the time from a bus stop to its departure is limited, and the ad often ends before people begin to pay attention to the content of the ad. This further reduces people's selective acceptance of bus advertising, resulting in low advertising efficiency. Summary of the invention

[0005] The present invention provides an electronic platform advertisement playing method, device, electronic equipment and storage medium, so as to improve people's selective acceptance of public transportation advertisements and improve the efficiency of advertisement delivery.

[0006] In a first aspect, in order to solve the above technical problems, the present invention provides an electronic station advertisement playing method, comprising:

[0007] Obtain passenger boarding and alighting information data, advertisement play request data, bus boarding and departure data, and bus operation data;

[0008] Determine an advertisement priority list according to the advertisement play request data;

[0009] Calculate the user granularity within the time period according to the passenger boarding and alighting information data and the bus boarding and departure data; wherein the time period represents the time period included in the passenger boarding and alighting information data;

[0010] According to the bus operation data, the average number of passengers at each stop on the same bus line is obtained;

[0011] According to the average number of passengers at each station, combined with a preset line priority coefficient, a station priority coefficient is obtained;

[0012] Determining the advertisement playing time of each site according to the user granularity and the site priority coefficient;

[0013] During the advertisement playing time, advertisements are delivered according to the order of the advertisement priority list.

[0014] In an optional implementation, the passenger boarding and alighting information data includes the passenger boarding time, the passenger alighting time and the boarding station;

[0015] The advertisement play request data includes the number of advertisement delivery times, the number of advertisement delivery days, the request time, and the advertisement delivery method;

[0016] The bus boarding and departure data includes the static waiting time for the bus to enter the platform;

[0017] The bus operation data includes bus operation routes and bus operation speeds.

[0018] In an optional implementation, determining an advertisement priority list according to the advertisement play request data includes:

[0019] Calculating the advertisement priority using a preset advertisement priority model according to the advertisement play request data;

[0020] Sort all the ads to be delivered by priority;

[0021] The advertisement data is divided into standby advertisements and played advertisements from an initial state; wherein the standby advertisements are at the first position in the advertisement priority list, and the played advertisements are at the last position in the advertisement priority list;

[0022] When the standby advertisement exists, the standby advertisement with the highest advertisement priority is played as the played advertisement, and the standby advertisement is transferred from the standby to the end of the play queue;

[0023] When the standby advertisements do not exist, all the played advertisements are changed into standby advertisements.

[0024] In an optional implementation, the user granularity within the time period is calculated based on the passenger boarding and alighting information data and the bus boarding and departure data, including:

[0025] Calculate the current time of the passenger at the current station based on the passenger boarding and alighting information data;

[0026] According to the bus boarding and departure data, the number of passengers staying in the bus station is counted in time segments according to the time granularity;

[0027] Calculate the average length of time that passengers stay at the station based on the number of passengers who stay at the station;

[0028] According to the average stay time, input it into the average stay time algorithm to obtain the length of this stay;

[0029] The probability of staying at the site is obtained by the following formula:

[0030]

[0031] Where P is the probability of a passenger staying at the platform; t is the current time; a 1 、a 2 Indicates the starting and ending time of the passenger boarding the bus and leaving the platform; b 1 , b 2 is the preset weight coefficient; c 1 、c 2 is the magnitude of the passenger stay time interval, and are the probabilities that interval t belongs to a1 to a2;

[0032] The time for passengers to get on and off the bus is segmented and counted according to the stay time probability and the time length to obtain the user granularity of the video playback.

[0033] In an optional implementation, the station priority coefficient is obtained according to the average number of passengers at each station and a preset line priority coefficient, including:

[0034] Get the number of stops of the bus line at the station;

[0035] According to the average number of passengers and the number of stops, a platform coefficient is obtained through a preset coefficient allocation model;

[0036] The platform coefficient is multiplied by the line priority coefficient to obtain the site priority coefficient.

[0037] In an optional implementation, determining the advertisement playing time of each site according to the user granularity and the site priority coefficient includes:

[0038] The advertisement playing time is calculated by the following formula:

[0039] d = (24-t)·P(t)·m, where d is the advertisement playing time, m is the station priority coefficient, t is the current time, and P(t) is the probability of the passenger staying on the platform at time t.

[0040] In an optional implementation, after delivering the advertisements according to the order of the advertisement priority list during the advertisement playing time, the method further includes:

[0041] When the remaining advertisement playing time is less than the highest priority unplayed advertisement, an advertisement whose advertisement request duration is less than the remaining advertisement playing time is selected from the unplayed advertisement list for playing.

[0042] In a second aspect, the present invention provides an electronic station advertisement playing device, comprising:

[0043] A data acquisition module is used to obtain passenger boarding and alighting information data, advertisement play request data, bus boarding and departure data, and bus operation data;

[0044] An advertisement priority module, used to determine an advertisement priority list according to the advertisement play request data;

[0045] A user granularity module calculates the user granularity within the time period based on the passenger boarding and alighting information data and the bus boarding and departure data;

[0046] An operation analysis module, used for obtaining the average number of passengers at each station on the same bus line according to the bus operation data;

[0047] A station priority module, used to obtain a station priority coefficient according to the average number of passengers at each station and a preset line priority coefficient;

[0048] A time module, used to determine the advertisement playing time of each site according to the user granularity and the site priority coefficient;

[0049] The advertisement delivery module is used to deliver advertisements according to the order of the advertisement priority list during the advertisement playing time.

[0050] In a third aspect, the present invention further provides an electronic device, comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor implements any one of the above-mentioned electronic station advertisement playing methods when executing the computer program.

[0051] In a fourth aspect, the present invention further provides a computer-readable storage medium, the computer-readable storage medium comprising a stored computer program, wherein when the computer program is executed, the device where the computer-readable storage medium is located is controlled to execute any one of the above-mentioned electronic station advertisement playing methods.

[0052] Compared with the prior art, the present invention has the following beneficial effects:

[0053] The present invention discloses an electronic platform advertisement playing method, the method comprising obtaining passenger boarding and alighting information data, advertisement playing request data, bus boarding and departure data, and bus operation data; determining an advertisement priority list according to the advertisement playing request data; calculating the user granularity in the time period according to the passenger boarding and alighting information data and the bus boarding and departure data; obtaining the average number of passengers at each station on the same bus line according to the bus operation data; obtaining the station priority coefficient according to the average number of passengers at each station combined with a preset line priority coefficient; determining the advertisement playing time of each station according to the user granularity and the station priority coefficient; and placing advertisements according to the order of the advertisement priority list during the advertisement playing time. Through the electronic platform advertisement playing method based on the real-time operation information of the bus, the target audience can be more accurately located, and the advertisement can be displayed to the passengers at the most appropriate time and place, thereby improving the attractiveness and influence of the advertisement, improving people's selective acceptance of bus advertisements, and improving the efficiency of advertisement placement. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 It is a flowchart of an electronic station advertisement playing method provided by the first embodiment of the present invention;

[0055] Figure 2 It is a schematic diagram of the structure of an electronic station advertisement playing device provided by the second embodiment of the present invention. DETAILED DESCRIPTION

[0056] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0057] The development and popularization of public transportation is of great significance to avoiding "urban diseases", but with limited public transportation resources, public transportation resources often cannot meet people's growing needs. To this end, it is necessary to innovate and reform, develop a variety of public transportation systems, including ground public transportation, rail transportation, water transportation, etc., and improve the service level of public transportation. As the main component of the ground public transportation system, buses are of great significance to people's daily travel. In order to improve people's satisfaction with public transportation, designing and using bus stop advertising systems on buses is a promising option.

[0058] Traditional bus advertising often requires advertisers to choose the time and method of delivery themselves, but people's subjective judgment often fails to achieve good advertising effects. At the same time, the time from a bus stop to its departure is limited, and the ad often ends before people begin to pay attention to the content of the ad. This further reduces people's selective acceptance of bus advertising, resulting in low advertising efficiency.

[0059] In an embodiment of the present invention, a method, device, electronic device and storage medium for playing advertisements on an electronic platform are disclosed to improve people's selective acceptance of public transportation advertisements and improve the efficiency of advertisement delivery.

[0060] Reference Figure 1 The first embodiment of the present invention provides an electronic station advertisement playing method, comprising the following steps:

[0061] S11, obtaining passenger boarding and alighting information data, advertisement play request data, bus boarding and departure data, and bus operation data;

[0062] S12, determining an advertisement priority list according to the advertisement play request data;

[0063] S13, calculating the user granularity within the time period according to the passenger boarding and alighting information data and the bus boarding and departure data; wherein the time period represents the time period included in the passenger boarding and alighting information data;

[0064] S14, obtaining the average number of passengers at each stop on the same bus line according to the bus operation data;

[0065] S15, obtaining a station priority coefficient according to the average number of passengers at each station and a preset line priority coefficient;

[0066] S16, determining the advertisement playing time of each site according to the user granularity and the site priority coefficient;

[0067] S17: within the advertisement playing time, placing advertisements according to the order of the advertisement priority list.

[0068] In step S11, the passenger boarding and alighting information data, advertisement broadcasting request data, bus boarding and departure data, and bus operation data are obtained. The passenger boarding and alighting information data includes the passenger boarding time, the passenger alighting time, and the boarding station; the advertisement broadcasting request data includes the number of advertisement delivery times, the number of days for advertisement delivery, the request time, and the advertisement delivery method; the bus boarding and departure data includes the static waiting time for the bus to enter the platform; and the bus operation data includes the bus operation route and the bus operation speed.

[0069] It is worth noting that the bus route refers to the route of the bus, including the stations passed, route length, etc. Route information can help the system determine the coverage and target audience of the advertisement. For example, if a route passes through a commercial or residential area, the advertising content can be adjusted accordingly to better attract passengers in these areas; the bus running speed refers to the speed of the bus on each section of the road. By monitoring the speed of the bus, the time it takes for the vehicle to arrive at each station can be estimated, and the broadcast time of the advertisement can be adjusted. For example, when there is traffic congestion, the bus will slow down, which means that the waiting time for passengers on the platform will become longer, so the broadcast time of the advertisement can be increased.

[0070] In one implementation, the bus operation data may be obtained from big data, or may be obtained through third-party navigation software.

[0071] In step S12, determining an advertisement priority list according to the advertisement play request data includes:

[0072] Calculating the advertisement priority using a preset advertisement priority model according to the advertisement play request data;

[0073] Sort all the ads to be delivered by priority;

[0074] The advertisement data is divided into standby advertisements and played advertisements from an initial state; wherein the standby advertisements are at the first position in the advertisement priority list, and the played advertisements are at the last position in the advertisement priority list;

[0075] When the standby advertisement exists, the standby advertisement with the highest advertisement priority is played as the played advertisement, and the standby advertisement is transferred from the standby to the end of the play queue;

[0076] When the standby advertisements do not exist, all the played advertisements are changed into standby advertisements.

[0077] In one implementation, the advertisement priority model may be calculated in the following manner:

[0078] Using the weighted average model, reference factors can be considered in multiple dimensions, such as the terms of the advertising contract. Ads that are ranked higher have higher priority; time factors. Different time periods are suitable for displaying different types of product or service ads. For example, weekday mornings are more suitable for displaying ads for breakfast food or commuting tools; the interactivity of the ads. Ads with higher interactivity, such as those with QR codes, AR / VR experiences, etc., will be given higher priority based on their expected engagement.

[0079] Exemplarily, the ready-to-play ads are defined as ads that have not been played yet but are ready to be played at any time. The played ads are defined as ads that have been played and will not be played again.

[0080] Assume that there is an advertisement list: Ad1 has a priority of 1 and is a standby advertisement; Ad2 has a priority of 2 and is a standby advertisement; Ad3 has a priority of 3 and is a playing advertisement; Ad4 has a priority of 4 and is a playing advertisement; Ad5 has a priority of 5 and is a standby advertisement; Ad6 has a priority of 6 and is a playing advertisement; and Ad7 has a priority of 7 and is a standby advertisement.

[0081] Select all the standby ads and sort them by priority (the smaller the value, the higher the priority), and get the standby ad list: Ad1 has priority 1 and is a standby ad; Ad2 has priority 2 and is a standby ad; Ad5 has priority 5 and is a standby ad; Ad7 has priority 7 and is a standby ad. This means that Ad1 is played first, followed by Ad2. In this way, the system can ensure that the ads are played efficiently and orderly, and can also dynamically adjust the ad playback strategy according to priority and status.

[0082] In step S13, the user granularity in the time period is calculated based on the passenger boarding and alighting information data and the bus boarding and departure data, including:

[0083] Calculate the current time of the passenger at the current station based on the passenger boarding and alighting information data;

[0084] According to the bus boarding and departure data, the number of passengers staying in the bus station is counted in time segments according to the time granularity;

[0085] Calculate the average length of time that passengers stay at the station based on the number of passengers who stay at the station;

[0086] According to the average stay time, input it into the average stay time algorithm to obtain the length of this stay;

[0087] The probability of staying at the site is obtained by the following formula:

[0088]

[0089] Where P is the probability of a passenger staying at the platform; t is the current time; a 1 、a 2 Indicates the starting and ending time of the passenger boarding the bus and leaving the platform; b 1 , b 2 is the preset weight coefficient; c 1 、c 2is the magnitude of the passenger stay time interval, and are the probabilities that interval t belongs to a1 to a2;

[0090] The time for passengers to get on and off the bus is segmented and counted according to the stay time probability and the time length to obtain the user granularity of the video playback.

[0091] It is worth noting that the time period refers to the time period included in the passenger boarding and alighting information data, and the user granularity refers to grouping by time period (morning peak, evening peak, non-peak) to obtain the distribution characteristics of the number of passengers at different times. For example, it is found that most passengers take the bus to the city center between 7 and 8 in the morning and return between 5 and 6 in the afternoon. Based on the above analysis, the travel characteristics of passengers during this period can be defined, such as "morning peak office workers", and further subdivided into passenger groups of different age groups and professional backgrounds. Based on this user granular information, bus companies can adjust routes and schedules to ensure sufficient capacity during peak hours, and advertisers can place relevant advertisements based on the travel habits of these groups, such as pushing coffee or breakfast advertisements during work hours. In this way, refined management of passenger behavior can be achieved, and more personalized services can be provided accordingly.

[0092] In one embodiment, a time period is selected, for example, the morning peak time period is 7:00-9:00. For each station, the number of passengers who board the bus in time period 6 is counted and normalized to obtain N i ;

[0093] The user granularity can be represented as a vector, where each element represents the number of passengers at a station during the time period. Assuming there are m stations, it can be represented as [N 1 , N 2 , ...N m ]; Use the same method to count the different time periods throughout the day, such as morning peak, evening peak, and non-peak.

[0094] Preferably, the passenger boarding and alighting information data includes the records of passengers boarding and alighting at a certain time point. Such data are usually derived from bus card swiping records, mobile payment records, or even face recognition systems. Bus boarding and departure data include the arrival and departure times of the bus at each station. Such data can be obtained through vehicle-mounted GPS devices, station sensors, and other means.

[0095] In one embodiment, the platform equipment collects passenger boarding and alighting signals through infrared sensors, and records the passenger's boarding time T1 and alighting time T2, where the current time is the boarding time T1.

[0096] In step S14, the average number of passengers at each station on the same bus line is obtained based on the bus operation data.

[0097] In one implementation, the names and numbers of bus stops and the boarding and alighting times of passengers at the stops are obtained from the big data; after data cleaning by removing invalid records and processing missing values, all relevant data are integrated together to form a complete data set containing passenger boarding and alighting information. Then, one day is selected to calculate the average number of passengers at each stop.

[0098] In step S15, based on the average number of passengers at each station and the preset line priority coefficient, a station priority coefficient is obtained, including:

[0099] Get the number of stops of the bus line at the station;

[0100] According to the average number of passengers and the number of stops, a platform coefficient is obtained through a preset coefficient allocation model;

[0101] The platform coefficient is multiplied by the line priority coefficient to obtain the site priority coefficient.

[0102] It is worth noting that in step S15, for the coefficient allocation model, more algorithms can be used to formulate more accurate coefficients. For example, the AIDA model: although it is mainly used to describe consumer purchasing behavior in marketing and advertising, it can also indirectly affect the setting of advertising priorities. It emphasizes the process from attracting attention (Attention), arousing interest (Interest), stimulating desire (Desire) to finally prompting action (Action). Advertising priority can be adjusted based on these stages. Or the KANO model: although it is mainly used for prioritizing product requirements, it can also be used in the advertising field to distinguish the impact of different advertisements on user satisfaction. It can divide advertising into basic needs (such as advertising should not disturb users' normal use of applications), expected needs (such as advertising should be related to user interests), attractive needs (such as innovative advertising forms), etc. An effective advertising priority model should be able to comprehensively consider multiple dimensions such as the expected effect of advertising, user experience, and advertiser needs to ensure that advertising can effectively reach the target audience without negatively affecting the user experience.

[0103] It is worth noting that this method is not only applicable to buses, but can also be extended to other public transportation vehicles (such as subways, taxis, etc.) and even non-transportation advertising scenarios. This is mainly because it can comprehensively consider multiple factors, such as time, location, passenger behavior, etc., and has strong adaptability and flexibility.

[0104] In one embodiment, it is assumed that there are two coefficients C p and C s, represent the weights of the average number of passengers and the number of stops, respectively. These coefficients can be adjusted according to actual conditions to reflect the importance of different factors. The number of stops is defined as the total number of times a bus stops at the station in a day.

[0105] Next, the station priority coefficient S can be calculated by the following formula:

[0106] S=C p ×(average number of passengers)+C s ×(Number of stops)

[0107] In order to make the data uniform, the calculated station coefficients need to be normalized to ensure that the coefficients of all stations are within a reasonable range. This can be achieved by dividing by the maximum value or using other normalization methods.

[0108] In step S16, the advertisement playing time of each site is determined according to the user granularity and the site priority coefficient, including:

[0109] The advertisement playing time is calculated by the following formula:

[0110] d=(24-t)·P(t)·m

[0111] Where d is the advertisement playing time, m is the station priority coefficient, t is the current time, and P(t) is the probability of the passenger staying at the platform at time t.

[0112] It is worth noting that based on passenger behavior data, user granularity is defined, that is, a way to distinguish different passenger groups, including information such as passengers' travel time, frequency of travel, and boarding and alighting stations. A priority coefficient is assigned to each station based on factors such as the importance of the station and the flow of people. This coefficient can be calculated based on historical data, real-time data, or a combination of both. Based on user granularity and station priority coefficients, the broadcast time of advertisements at each station is determined. In this way, not only can the advertising content be more in line with the needs of the target audience, but also the effectiveness and influence of the advertisement can be maximized.

[0113] In one implementation, passenger boarding and alighting information can be collected from bus card swiping records, mobile payment records, GPS location data, etc. For user groups that mainly travel during peak hours in the morning and evening and tend to pay attention to health and lifestyle advertisements, bus companies can play more advertisements about healthy lifestyles, especially during peak hours in the morning and evening; and for user groups that mainly travel during non-peak hours during the day and are interested in technology products, bus companies can play some technology product advertisements, especially during non-peak hours during the day.

[0114] In step S17, during the advertisement playing time, advertisements are delivered according to the order of the advertisement priority list.

[0115] In order to facilitate the understanding of the present invention, some preferred embodiments of the present invention are further described below.

[0116] In an optional implementation, after delivering the advertisements according to the order of the advertisement priority list, the method further includes:

[0117] When the remaining ad playback time is less than the highest priority unplayed ad, in the unplayed ad list, select the ad whose ad request duration is less than the remaining ad playback time to play. For example, if the remaining ad playback time is 25 seconds, the highest priority ad playback time is 30 seconds, and the second priority ad playback time is 15 seconds, the second priority ad is selected to play.

[0118] It should be noted that the additional embodiment can make full use of the advertisement playing time, ensuring that as many unplayed advertisements as possible are played within a limited time, while giving priority to advertisements with higher priority for playing. This method not only improves the efficiency of advertisement playing, but also better meets the needs of advertisers.

[0119] In summary, the present invention obtains passenger boarding and alighting information data, advertisement broadcasting request data, bus boarding and departure data, and bus operation data through big data, and can be combined with analyzing passenger behavior in bus operation data to more accurately identify the target audience, and customize the advertisement content accordingly to improve the relevance and attractiveness of the advertisement. Based on user granularity and site priority coefficients, the best time for advertisement broadcasting can be better grasped, thereby increasing the interaction between passengers and advertisements. The method of optimizing the advertising delivery strategy based on bus operation data has many advantages. It can not only improve advertising effects and optimize resource allocation, but also improve user experience, and has high cost-effectiveness and technological advancement. These advantages make this method have broad prospects in practical applications.

[0120] Reference Figure 2 The second embodiment of the present invention provides an electronic station advertisement playing device, comprising:

[0121] A data acquisition module is used to obtain passenger boarding and alighting information data, advertisement play request data, bus boarding and departure data, and bus operation data;

[0122] An advertisement priority module, used to determine an advertisement priority list according to the advertisement play request data;

[0123] A user granularity module calculates the user granularity within the time period based on the passenger boarding and alighting information data and the bus boarding and departure data;

[0124] An operation analysis module, used for obtaining the average number of passengers at each station on the same bus line according to the bus operation data;

[0125] A station priority module, used to obtain a station priority coefficient according to the average number of passengers at each station and a preset line priority coefficient;

[0126] A time module, used to determine the advertisement playing time of each site according to the user granularity and the site priority coefficient;

[0127] The advertisement delivery module is used to deliver advertisements according to the order of the advertisement priority list during the advertisement playing time.

[0128] Preferably, the data acquisition module is also used for:

[0129] Obtain passenger boarding and alighting information data, advertisement play request data, bus boarding and departure data, and bus operation data; wherein the advertisement play request data includes the number of advertisement delivery times, the number of days for advertisement delivery, the request time, and the advertisement delivery method; the bus boarding and departure data includes the static waiting time for the bus to enter the platform; the bus operation data includes the bus operation route and the bus operation speed.

[0130] Preferably, the advertisement priority module is used to:

[0131] Determine an advertisement priority list according to the advertisement play request data; calculate the advertisement priority through a preset advertisement priority model according to the advertisement play request data; sort all advertisements to be delivered according to their priorities; divide the advertisement data from an initial state into standby advertisements and play advertisements; wherein the standby advertisements are at the first position in the advertisement priority list, and the play advertisements are at the last position in the advertisement priority list; when the standby advertisements exist, the standby advertisements with the highest advertisement priority are played as the play advertisements, and the standby advertisements are transferred from the standby position to the last position in the play queue; when the standby advertisements do not exist, all the play advertisements are changed to standby advertisements.

[0132] Preferably, the user granularity module is used to:

[0133] Calculate the current time of the passenger at the current station based on the passenger boarding and alighting information data;

[0134] According to the bus boarding and departure data, the number of passengers staying in the bus station is counted in time segments according to the time granularity;

[0135] Calculate the average length of time that passengers stay at the station based on the number of passengers who stay at the station;

[0136] According to the average stay time, input it into the average stay time algorithm to obtain the length of this stay;

[0137] The probability of staying at the site is obtained by the following formula:

[0138]

[0139] Where P is the probability of a passenger staying at the platform; t is the current time; a 1 、a 2 Indicates the starting and ending time of the passenger boarding the bus and leaving the platform; b 1 、b 2 is the preset weight coefficient; c 1 、c 2 is the magnitude of the passenger stay time interval, and are the probabilities that interval t belongs to a1 to a2;

[0140] The time for passengers to get on and off the bus is segmented and counted according to the stay time probability and the time length to obtain the user granularity of the video playback.

[0141] Preferably, the operation analysis module is used to

[0142] Obtain the number of stops of the bus line at the station; obtain the platform coefficient according to the average number of passengers and the number of stops through a preset coefficient allocation model; multiply the platform coefficient by the line priority coefficient to obtain the station priority coefficient.

[0143] Preferably, the site priority module is used to:

[0144] The advertisement playing time is calculated by the following formula:

[0145] d=(24-t)·P(t)·m

[0146] Where d is the advertisement playing time, m is the station priority coefficient, t is the current time, and P(t) is the probability of the passenger staying at the platform at time t.

[0147] Preferably, the device further comprises:

[0148] The second advertisement delivery module is configured to select, from the unplayed advertisement list, an advertisement whose advertisement request duration is less than the remaining advertisement playing time for playing when the remaining advertisement playing time is less than the highest priority unplayed advertisement.

[0149] It should be noted that the electronic station advertisement playing device provided in the embodiment of the present invention is used to execute all the process steps of the electronic station advertisement playing method in the above embodiment, and the working principles and beneficial effects of the two correspond one to one, so they will not be described in detail.

[0150] The embodiment of the present invention further provides an electronic device. The electronic device includes: a processor, a memory, and a computer program stored in the memory and executable on the processor, such as a data acquisition program. When the processor executes the computer program, the steps in the above-mentioned electronic station advertisement playing method embodiments are implemented, such as Figure 1 Alternatively, when the processor executes the computer program, the functions of the modules / units in the above-mentioned device embodiments are realized, such as the data acquisition module.

[0151] Exemplarily, the computer program may be divided into one or more modules / units, which are stored in the memory and executed by the processor to implement the present invention. The one or more modules / units may be a series of computer program instruction segments capable of implementing specific functions, which are used to describe the execution process of the computer program in the electronic device.

[0152] The electronic device may be a computing device such as a desktop computer, a notebook, a PDA, and a smart tablet. The electronic device may include, but is not limited to, a processor and a memory. Those skilled in the art will appreciate that the above components are merely examples of electronic devices and do not constitute a limitation on the electronic device. The electronic device may include more or fewer components than the above components, or may combine certain components, or different components. For example, the electronic device may also include input and output devices, network access devices, buses, etc.

[0153] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the electronic device, and uses various interfaces and lines to connect various parts of the entire electronic device.

[0154] The memory can be used to store the computer program and / or module, and the processor realizes various functions of the electronic device by running or executing the computer program and / or module stored in the memory, and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area can store data created according to the use of the mobile phone (such as audio data, a phone book, etc.), etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0155] Wherein, if the module / unit integrated in the electronic device is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Wherein, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0156] It should be noted that the device embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. In addition, in the accompanying drawings of the device embodiments provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, which may be specifically implemented as one or more communication buses or signal lines. A person of ordinary skill in the art may understand and implement it without paying any creative effort.

[0157] The specific embodiments described above further illustrate the purpose, technical solutions and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. It is particularly pointed out that for those skilled in the art, any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for playing advertisements on an electronic platform, characterized in that: include: Obtain passenger boarding and alighting information data, advertisement play request data, bus boarding and departure data, and bus operation data; Determine an advertisement priority list according to the advertisement play request data; Calculate the user granularity within the time period according to the passenger boarding and alighting information data and the bus boarding and departure data; wherein the time period represents the time period included in the passenger boarding and alighting information data; According to the bus operation data, the average number of passengers at each stop on the same bus line is obtained; According to the average number of passengers at each station, combined with a preset line priority coefficient, a station priority coefficient is obtained; Determining the advertisement playing time of each site according to the user granularity and the site priority coefficient; During the advertisement playing time, advertisements are delivered according to the order of the advertisement priority list.

2. The electronic station advertisement broadcasting method according to claim 1, characterized in that: The passenger boarding and alighting information data includes the passenger boarding time, the passenger alighting time and the boarding station; The advertisement play request data includes the number of advertisement delivery times, the number of advertisement delivery days, the request time, and the advertisement delivery method; The bus boarding and departure data includes the static waiting time for the bus to enter the platform; The bus operation data includes bus operation routes and bus operation speeds.

3. The electronic station advertisement broadcasting method according to claim 1, characterized in that: Determining an advertisement priority list according to the advertisement play request data includes: Calculating the advertisement priority using a preset advertisement priority model according to the advertisement play request data; Sort all the ads to be delivered by priority; The advertisement data is divided into standby advertisements and played advertisements from an initial state; wherein the standby advertisements are at the first position in the advertisement priority list, and the played advertisements are at the last position in the advertisement priority list; When the standby advertisement exists, the standby advertisement with the highest advertisement priority is played as the played advertisement, and the standby advertisement is transferred from the standby to the end of the play queue; When the standby advertisements do not exist, all the played advertisements are changed into standby advertisements.

4. The electronic station advertisement broadcasting method according to claim 1, characterized in that: The user granularity within the time period is calculated based on the passenger boarding and alighting information data and the bus boarding and departure data, including: Calculate the current time of the passenger at the current station based on the passenger boarding and alighting information data; According to the bus boarding and departure data, the number of passengers staying in the bus station is counted in time segments according to the time granularity; Calculate the average length of time that passengers stay at the station based on the number of passengers who stay at the station; According to the average stay time, input it into the average stay time algorithm to obtain the length of this stay; The probability of staying at the site is obtained by the following formula: Among them, P is the probability of the passenger's stay time at the platform; t is the current time; a1 and a2 represent the starting time and ending time of the passenger from getting on the bus to leaving the platform; b1 and b2 are the preset weight coefficients; c1 and c2 are the magnitude of the passenger's stay time interval, which are the probabilities that interval t belongs to a1 to a2 respectively; The time for passengers to get on and off the bus is segmented and counted according to the stay time probability and the time length to obtain the user granularity of the video playback.

5. The electronic station advertisement broadcasting method according to claim 1, characterized in that: According to the average number of passengers at each station, combined with the preset line priority coefficient, the station priority coefficient is obtained, including: Get the number of stops of the bus line at the station; According to the average number of passengers and the number of stops, a platform coefficient is obtained through a preset coefficient allocation model; The platform coefficient is multiplied by the line priority coefficient to obtain the site priority coefficient.

6. The electronic station advertisement broadcasting method according to claim 4, characterized in that: Determining the advertisement playing time of each site according to the user granularity and the site priority coefficient includes: The advertisement playing time is calculated by the following formula: d=(24-t)·P(t)·m Where d is the advertisement playing time, m is the station priority coefficient, t is the current time, and P(t) is the probability of the passenger staying at the platform at time t.

7. The electronic station advertisement broadcasting method according to claim 1, characterized in that: After delivering the advertisements according to the order of the advertisement priority list during the advertisement playing time, the method further includes: When the remaining advertisement playing time is less than the highest priority unplayed advertisement, an advertisement whose advertisement request duration is less than the remaining advertisement playing time is selected from the unplayed advertisement list for playing.

8. An electronic platform advertising playback device, characterized in that: include: A data acquisition module is used to obtain passenger boarding and alighting information data, advertisement play request data, bus boarding and departure data, and bus operation data; An advertisement priority module, used to determine an advertisement priority list according to the advertisement play request data; A user granularity module calculates the user granularity within the time period based on the passenger boarding and alighting information data and the bus boarding and departure data; An operation analysis module, used for obtaining the average number of passengers at each station on the same bus line according to the bus operation data; A station priority module, used to obtain a station priority coefficient according to the average number of passengers at each station and a preset line priority coefficient; A time module, used to determine the advertisement playing time of each site according to the user granularity and the site priority coefficient; The advertisement delivery module is used to deliver advertisements according to the order of the advertisement priority list during the advertisement playing time.

9. An electronic device, characterized in that: The method comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, an electronic station advertisement playing method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored computer program, wherein when the computer program is executed, the device where the computer-readable storage medium is located is controlled to execute the electronic station advertisement playing method according to any one of claims 1 to 7.

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