Student parent pick-up pass feature image method and system

Abstract

The application provides a student parent pick-up and drop-off traffic feature portrait method, which comprises the following steps: collecting historical data related to the pick-up and drop-off time of parents, the traffic features of motor vehicles and non-motor vehicles used by parents to pick up and drop off students near the school in a specified time period, calculating based on the objective data to obtain quantitative data of the punctuality of the parent pick-up and drop-off, and the law-abidingness and standardization of the traffic tools used for pick-up and drop-off; and calculating the overall characteristics of the parents based on the data to obtain the parent pick-up and drop-off traffic feature portrait result; in the parent pick-up and drop-off traffic feature portrait result, the parents are divided into aggressive type, steady type and intermediate type; the method calculates the parent pick-up and drop-off traffic feature portrait result based on historical data, ensures that the result is accurate and quantifiable, and uses the parent pick-up and drop-off traffic feature portrait result calculated by the method as the data basis for subsequent implementation of traffic management measures in the area where the school is located, thereby ensuring the accuracy of the subsequent traffic management.

Description

Technical Field

[0001] This invention relates to the field of traffic management technology, specifically to a method and system for profiling the characteristics of parents picking up and dropping off students. Background Technology

[0002] Parents' actions in picking up and dropping off students involve multiple stages, including arriving at school, parking, and navigating traffic, significantly impacting traffic management in the school area. In particular, the timing of parents' arrivals and the behavior of their motorized or non-motorized vehicles directly affect traffic flow around the school, easily leading to congestion if management is inadequate. From a traffic management perspective, understanding the traffic behavior characteristics of parents picking up and dropping off students is crucial for developing appropriate countermeasures to effectively alleviate traffic congestion. Different parents exhibit different characteristics during pick-up and drop-off, but current technology lacks a comprehensive method for analyzing and mining these behaviors and characteristics. Most approaches rely on manual judgment by technical personnel, resulting in a lack of precise matching between traffic management measures for the school area and these traffic patterns, thus lacking specificity. Summary of the Invention

[0003] To address the lack of a well-established method in existing technologies for analyzing and mining the behavior and traffic characteristics of parents picking up and dropping off students, this invention provides a method for profiling the traffic characteristics of parents picking up and dropping off students. This method analyzes the characteristics of parents' traffic during this process and generates a profile, providing a data foundation for subsequent targeted traffic management measures. This application also discloses a system for profiling the traffic characteristics of parents picking up and dropping off students.

[0004] The technical solution of this invention is as follows: a method for creating a profile of student parents' pick-up and drop-off traffic, characterized by comprising the following steps:

[0005] S1: Set the data collection time period and collect historical data within the data collection time period;

[0006] The historical data includes: the actual arrival time of parents picking up and dropping off students at school and the school's preset pick-up and drop-off time; the parking status of parents' motor vehicles after arrival, including parking in designated spaces, parking beyond the time limit, and illegal parking; and the parking status of non-motorized vehicles at designated locations and illegal passage on road sections after arrival.

[0007] S2: Based on the actual arrival time of parents picking up and dropping off students at school and the school's preset pick-up and drop-off time, the results of the parents' on-time pick-up and drop-off index are calculated.

[0008] S3: Based on the parking status of parents' vehicles after arriving at the school, including parking in designated spaces, exceeding the time limit, and illegal parking, the results of the standardized parking index for motor vehicles are calculated.

[0009] S4: Based on the historical data of parents' non-motorized vehicles arriving at designated parking spots and illegal passage on road sections, the non-motorized vehicle law-abiding passage index result is calculated;

[0010] S5: Based on the results of the on-time pick-up and drop-off indicators, the standardized parking indicators for motor vehicles, and the law-abiding traffic indicators for non-motor vehicles, the overall characteristics of parents are calculated.

[0011] The method for calculating the overall characteristic profile of the parents is as follows:

[0012]

[0013] Among them, D g For non-parental overall characteristics, A t To ensure parents can pick up and drop off students on time, P s To regulate parking quotas for motor vehicles, T b The non-motorized vehicle compliance index is defined as follows: n is the number of times a motorized vehicle picks up and drops off passengers, m is the number of times a non-motorized vehicle picks up and drops off passengers, and μ1 and μ2 are weighting factors.

[0014] S6: Based on the overall characteristics of the parents, create a profile of each parent's pick-up and drop-off and passage behavior to obtain the parent pick-up and drop-off passage characteristic profile results;

[0015] The process involves creating a profile of each parent's pick-up and drop-off and travel behavior, specifically including the following steps:

[0016] a1: Constructs behavior colors;

[0017] The colors of the behavior include: red, yellow, and green.

[0018] Among them, red represents the aggressive type, indicating a high likelihood of traffic violations;

[0019] Green represents a stable type, indicating that traffic violations are unlikely to occur;

[0020] Yellow represents the intermediate type, falling between the aggressive and the conservative types;

[0021] a2: Construct the correspondence between behavioral colors and the overall characteristics of the parents to obtain the parent pick-up and drop-off access feature profile results corresponding to the parents:

[0022]

[0023] Among them, C r The results of the traffic profile analysis for parents picking up and dropping off their children, D g Results representing the overall characteristics of parents.

[0024] Its further features are:

[0025] It also includes the following steps:

[0026] S7: Based on the results of the parent pick-up and drop-off traffic feature profile, construct an overall behavioral feature profile of the student's parents;

[0027] The method for constructing a comprehensive behavioral profile of students' parents includes the following steps:

[0028] b1: Statistically analyze the parent pick-up and drop-off characteristics of all parents and count the percentage of parents whose behavior is marked in red out of the total number of parents. This percentage is called the "aggressive type ratio".

[0029] b2: Set the radical proportion from historical data as the baseline data;

[0030] b3: After the specified start time, continuously acquire the aggressive ratio, and record it as: data to be confirmed.

[0031] b4: Compare each of the data to be confirmed with the baseline data;

[0032] A preset aggressive alarm threshold N is set. When N consecutive data points to be confirmed exceed the baseline data, the overall behavioral profile of the student's parents is set to "to be monitored"; where N is a natural number.

[0033] Otherwise, the overall behavioral profile of the students' parents is set to: Standard.

[0034] Repeat steps b3 to b4.

[0035] S8: Set the cycle period, and execute steps S1 to S7 repeatedly according to the cycle period;

[0036] Before step S8 is implemented, the school traffic management type is also constructed based on the historical data.

[0037] The method for constructing school traffic management types includes the following steps:

[0038] c1: Identify all parents who use motor vehicles and non-motor vehicles to pick up and drop off students, and denot them as: Parents to be observed;

[0039] c2: Calculate the abnormal rate of violation proportion for each parent to be observed during the pick-up and drop-off period. The method for calculating the abnormal rate of violation proportion is as follows:

[0040]

[0041] Where: R l The abnormal rate of violations during pick-up and drop-off times; Q i Let be the number of violations during the i-th pick-up / drop-off; Q be the total number of violations during the i-th pick-up / drop-off period for the entire day; t 接送 For pick-up and drop-off times; t通行 This represents the average time it takes for the road to pass under normal circumstances.

[0042] c3: Compare the violation rate with a preset abnormality threshold. When the violation rate is greater than the abnormality threshold, mark the corresponding parent as an "abnormal parent".

[0043] c4: Count the number of all the aforementioned abnormal parents and calculate the proportion of the abnormal parents in the total number of parents, denoted as: abnormal proportion;

[0044] c5: Compare the abnormality ratio with the preset observation threshold and alarm threshold;

[0045] When the proportion of abnormal cases exceeds the alarm threshold, the school traffic management type is set to: Controlled.

[0046] When the proportion of abnormal cases is greater than or less than the alarm threshold, but greater than the observation threshold, the school traffic management type is set to: observation type.

[0047] Otherwise, the school traffic management type is set to: Normal.

[0048] The calculation method for the parent pick-up and drop-off time indicator is as follows:

[0049]

[0050]

[0051]

[0052] λ1+λ2=1

[0053] Among them, A t A provides a quota for parents to pick up and drop off students on time. 1i To ensure parents drop off their children on time, A 2j For statistics on parents picking up their children on time, n1 represents the number of times students were dropped off, n2 represents the number of times students were picked up, and t represents the number of times students were picked up. 上 For the school's designated school hours, t 1i For the first time a parent drops off their child at school, t 放 The staggered dismissal times for students as stipulated by the school 2i λ1 and λ2 are the time when parents pick up their children from school for the i-th time, and λ1 and λ2 are weighting factors.

[0054] The method for calculating the standard parking quota for motor vehicles is as follows:

[0055]

[0056]

[0057]

[0058]

[0059] α1+α2+α3=1

[0060] Among them, P s To regulate parking quotas for motor vehicles, P 1i For the i-th instance of illegal parking of a motor vehicle, P 2i P represents the parking status of the vehicle during its i-th parking attempt. 3i This represents the number of times a vehicle exceeds the parking time limit during its i-th parking session, where n is the number of times the vehicle is picked up or dropped off, and tc is the number of times the vehicle is parked beyond the permitted parking time. i Let t be the duration of the i-th parking of the motor vehicle. p A time limit for parking spaces is set, with α1, α2, and α3 as weighting factors;

[0061] The calculation method for the non-motorized vehicle compliance index is as follows:

[0062]

[0063]

[0064]

[0065]

[0066] β1+β2+β3=1

[0067] Among them, T b For non-motorized vehicle traffic compliance indicators, T 1i For the fixed-point parking situation during the i-th pick-up and drop-off, T 2i For the case of non-motorized vehicles traveling against the flow of traffic on the road segment during the i-th pick-up and drop-off, T 3i , where m represents the number of times a non-motorized vehicle is picked up or dropped off, and β1, β2, and β3 are weighting factors.

[0068] A student parent pick-up and drop-off traffic feature profiling system, characterized in that it includes: an information acquisition module, a calculation module, a profiling module, and a display module;

[0069] The information acquisition module collects historical data within a preset data collection time period and sends the historical data into the calculation module.

[0070] The historical data includes: the actual arrival time of parents picking up and dropping off students at school and the school's preset pick-up and drop-off time; the parking status of parents' motor vehicles after arrival, including parking in designated spaces, parking beyond the time limit, and illegal parking; and the parking status of non-motorized vehicles at designated locations and illegal passage on road sections after arrival.

[0071] Based on the historical data, the calculation module calculates the results of parents' timely pick-up and drop-off indicators, motor vehicle standardized parking indicators, and non-motor vehicle law-abiding traffic indicators, and then calculates the overall characteristics of parents and sends the results to the profiling module.

[0072] The profiling module obtains the overall characteristics of the parents based on preset behavior colors and the correspondence between behavior colors and the overall characteristics of the parents. Then, it compares the results with preset behavior color categories based on the correspondence to obtain the color profiling results of the parents' pick-up and drop-off and passage behaviors, and sends them to the display module for display.

[0073] Its further features are:

[0074] The information acquisition module is communicatively connected to the school management system, the motor vehicle parking monitoring system, and the non-motor vehicle management system.

[0075] The school management system provides students' school arrival and dismissal times; the motor vehicle parking monitoring system provides information on parents' illegal parking, parking in designated spaces, and parking duration; and the non-motor vehicle management system provides information on non-motor vehicle parking at designated locations and compliance with traffic regulations.

[0076] The calculations performed in the calculation module also include:

[0077] Based on the school management system, all parents who use motor vehicles and non-motor vehicles to pick up and drop off students are counted and recorded as: parents to be observed; based on the motor vehicle parking monitoring system and the non-motor vehicle management system, the number of violations during the pick-up and drop-off period and the total number of violations for each parent to be observed are counted.

[0078] The abnormal violation rate of each parent under observation during the pick-up and drop-off period is calculated: the abnormal violation rate of each parent is compared with a preset abnormal rate threshold. When the abnormal violation rate is greater than the abnormal rate threshold, the corresponding parent is marked as an abnormal parent. The proportion of the abnormal parents in the total number of parents is calculated and denoted as the abnormal proportion. The abnormal proportion is compared with a preset observation threshold and an alarm threshold to determine the school traffic management type.

[0079] The calculations performed in the calculation module also include: statistically analyzing the parent pick-up and drop-off characteristic profiles of all parents, and calculating the percentage of parents whose behavior is marked in red out of the total number of parents, denoted as: aggressive proportion; after a specified start time, continuously acquiring the aggressive proportion, denoted as: data to be confirmed, comparing each data to be confirmed with a preset benchmark data, and when N consecutive data to be confirmed are greater than the benchmark data, setting the overall behavioral characteristic profile of the student's parents as: to be monitored; where N is a preset aggressive alarm threshold;

[0080] The calculation module transmits each piece of data to be confirmed and the corresponding comparison result with the benchmark data to the portrait module;

[0081] The image module displays each piece of data to be confirmed using a specified graphic. For each piece of data to be confirmed that is greater than the baseline data, it marks it with a preset specified color and then transmits the image to the display module for display.

[0082] This invention provides a method for profiling parent traffic characteristics during school drop-off and pick-up. It collects historical data on parents' drop-off and pick-up times, and the traffic characteristics of motor vehicles and non-motor vehicles used by parents near schools within a specified time period. Based on this objective data, it calculates quantitative data on the punctuality of parents' drop-offs and pick-ups, as well as the legality and compliance of the vehicles used. Based on this data, it calculates overall parent characteristics and creates a parent traffic characteristic profile. In this profile, parents are categorized into aggressive, moderate, and intermediate types. This method calculates the parent traffic characteristic profile based on historical data, ensuring the results are accurate and quantifiable. The parent traffic characteristic profile obtained by this method serves as the data basis for subsequent traffic management measures targeting the school area, thereby ensuring the accuracy of subsequent traffic management. Attached Figure Description

[0083] Figure 1 Flowchart of methods for creating profiles of student parents' pick-up and drop-off traffic characteristics;

[0084] Figure 2 Framework diagram of a student parent pick-up and drop-off traffic feature profiling system. Detailed Implementation

[0085] like Figure 1 As shown, the present invention includes a method for creating a profile of student parents' pick-up and drop-off traffic characteristics, which includes the following steps.

[0086] S1: Set the data collection period and collect historical data within the data collection period;

[0087] Historical data includes: the actual arrival time of parents picking up and dropping off students at school and the school's preset pick-up and drop-off times; parking status of parents' motor vehicles after arrival, including parking in designated spaces, parking beyond the time limit, and illegal parking; and parking status of non-motorized vehicles in designated areas and illegal passage on road sections after arrival.

[0088] Because current school management systems scientifically design the times for parents to pick up and drop off students, these times generally have an impact on traffic around the school. If parents pick up and drop off their children on time and strictly abide by traffic rules, there will be virtually no negative impact on the traffic environment around the school. However, in reality, the factors that have a significant negative impact on traffic in the school area are the timing of parents' pick-up and drop-off and the illegal or irregular use of vehicles. Specifically, if parents arrive at the same time to pick up and drop off their children, it can lead to vehicle and pedestrian congestion. If the motor vehicles or non-motor vehicles used by parents are illegally parked or involved in traffic accidents, it will also negatively impact traffic in the school area.

[0089] Therefore, this method collects and calculates historical data on the school's location based on these factors, using the data to depict the traffic characteristics of parents. Simultaneously, it compares and analyzes violations during pick-up and drop-off times with total violations throughout the day to identify parents with abnormal violation rates. This data is then used to calculate the overall school pick-up and drop-off situation, providing a profile analysis of the overall school pick-up and drop-off situation.

[0090] In this embodiment, the data collection period is set to one week, meaning that historical data within one week is collected each time. Tables 1 and 2 below are examples of the arrival times of students A and B's parents picking them up and dropping them off, motor vehicle parking conditions, and non-motorized vehicle traffic compliance conditions within a week.

[0091] Table 1. Examples of Student A's Parent Pick-up and Drop-off and Motor Vehicle Parking Information

[0092]

[0093] Table 2. Examples of Student B's Parent Pick-up and Drop-off and Non-Motorized Vehicle Traffic Compliance.

[0094]

[0095] The pick-up and drop-off times in Tables 1 and 2 are one hour before and after school start and end times.

[0096] The non-motorized vehicle traffic violations in this application refer to the violations committed by non-motorized vehicles within the school area after they arrive there. In this embodiment, the non-motorized vehicle traffic violations include whether they are going against traffic and whether they are driving in the designated lane.

[0097] Meanwhile, the time limit for a motor vehicle's parking is determined by comparing two time periods: the parking duration and the time limit.

[0098] In this embodiment, subsequent calculations are completed based on the data in Tables 1 and 2.

[0099] S2: Based on the actual arrival time of parents picking up and dropping off students at school and the school's preset pick-up and drop-off times, the on-time pick-up and drop-off indicator result is calculated; the calculation method for the on-time pick-up and drop-off indicator result is as follows:

[0100]

[0101]

[0102]

[0103] λ1+λ2=1

[0104] Among them, A t A provides a quota for parents to pick up and drop off students on time. 1i To ensure parents drop off their children on time, A 2j For statistics on parents picking up their children on time, n1 represents the number of times students were dropped off, n2 represents the number of times students were picked up, and t represents the number of times students were picked up. 上 For the school's designated school hours, t 1i For the first time a parent drops off their child at school, t 放 The staggered dismissal times for students as stipulated by the school 2i λ1 and λ2 are the arrival times of parents when picking up their children from school for the i-th time, and are weighting factors that can be set according to the actual situation.

[0105] In existing technology, to ensure student safety, each student is equipped with an RFID card that identifies them personally. Their arrival at and departure from school are recorded by a card reader near the school gate. Parents' vehicles are also assigned access cards for the school parking garage. 上 and t 放 The time designated by the school will be recorded in the school management system. The data of n1 and n2 will be collected by the time clock and stored in the school management system.

[0106] The time t is when the parent first drops the student off at school. 1i The time when parents pick up their children from school for the first time is t. 2iThe data is collected by registering the license plate numbers of non-motorized vehicles belonging to students' parents in the school management system. Based on existing traffic monitoring equipment and motor vehicle parking monitoring systems, the trajectory data corresponding to the license plate numbers can be obtained. According to the specified school area and time (school arrival or dismissal time), the first occurrence of the trajectory data is found, and the vehicle stays near the school for more than a preset threshold (e.g., 1 minute or 5 minutes, set according to the actual situation). If the student's personal identification card also identifies the entry and exit data of the school, it can be regarded as the parent's arrival time t. 1i and t 2i Alternatively, based on the vehicle-mounted video card recognition equipment installed at the school's underground parking system entrance, or the video recognition equipment at the garage entrance, vehicle entry and exit data can be collected. If the student's personal identification card also identifies entry and exit data at the same time, this can be considered as the parent's arrival time t. 1i and t 2i .

[0107] In practice, the specific implementation will depend on the circumstances of each school, and will be based on different systems or devices to obtain t. 1i and t 2i .

[0108] Although both concentrated drop-off and pick-up of students lead to the gathering of people and vehicles in the school area, historical data from the school shows that congestion is generally more likely to occur during dismissal time. Therefore, the weight λ2 for parents picking up students is set to a larger value, with default values ​​of λ1 = 0.4 and λ2 = 0.6. The values ​​of λ1 and λ2 will be adjusted later based on the effectiveness of the traffic strategy.

[0109] In this embodiment, the weighting factors λ1 and λ2 are set to default values, namely λ1 = 0.4 and λ2 = 0.6.

[0110] According to Table 1, there are five days a week, with students being dropped off and picked up once a day. Therefore, the values ​​of n1 and n2 are both 5.

[0111] The result of the student A's parents' timely pick-up and drop-off quota is as follows:

[0112]

[0113] The results of student B's parents' timely pick-up and drop-off quota are as follows:

[0114]

[0115] S3: Based on the parking status of parents' vehicles after arriving at the school, including parking in designated spaces, exceeding the time limit, and illegal parking, the results of the standardized parking index for motor vehicles are calculated.

[0116] The calculation method for the standard parking quota for motor vehicles is as follows:

[0117]

[0118]

[0119]

[0120]

[0121] α1+α2+α3=1

[0122] Among them, P s To regulate parking quotas for motor vehicles, P 1i For the i-th instance of illegal parking of a motor vehicle, P 2i P represents the parking status of the vehicle during its i-th parking attempt. 3i This represents the number of times a vehicle exceeds the parking time limit during its i-th parking session, where n is the number of times the vehicle is picked up or dropped off, and tc is the number of times the vehicle is parked beyond the permitted parking time. i Let t be the duration of the i-th parking of the motor vehicle. p Set a time limit for parking spaces, with a default value of 10-15 minutes; α1, α2 and α3 are weighting factors, which can be set according to the actual situation. Generally, α1 = 0.4, α2 = 0.2 and α3 = 0.4 can be used.

[0123] In practice, the license plate numbers of students' parents' vehicles are collected from the school management system. Based on designated areas and times, the traffic management records corresponding to these license plate numbers are retrieved from the vehicle parking monitoring and management system, thus obtaining P. 1i P 2i P 3i 、n、tc i and t p The record.

[0124] The setting of the weighting factors α1, α2, and α3 needs to consider the impact of different situations on traffic flow, such as whether the parking is illegal, whether the parking is in a designated space, and whether the parking exceeds the time limit. Because illegal parking and exceeding the time limit directly affect the parking of other vehicles and have a significant impact on traffic, while parking in a designated space has a relatively smaller impact, illegal parking and exceeding the time limit are given equal weight, while parking in a designated space has a smaller weight. Considering all factors, the default values ​​are α1 = 0.4, α2 = 0.2, and α3 = 0.4. In this embodiment, the weighting factors α1, α2, and α3 are set to their default values, i.e., α1 = 0.4, α2 = 0.2, and α3 = 0.4.

[0125] In this embodiment, P is calculated based on the "whether it is illegally parked" records in Table 1. 1i The value of P is calculated based on the record of "whether the parking space was filled in". 2i The value of P is calculated by comparing the records of "parking duration" and "time limit".3i The value of n is 10, which includes going to and from school.

[0126] Since Student A was picked up and dropped off by a motor vehicle, and Student B was picked up and dropped off by a non-motorized vehicle, the parking quota for Student A's parents is as follows:

[0127]

[0128] S4: Based on historical data on parents' non-motorized vehicles arriving at designated parking spots and illegal passage on road sections, the results of the non-motorized vehicle law-abiding passage index are calculated.

[0129] The calculation method for non-motorized vehicle compliance indicators is as follows:

[0130]

[0131]

[0132]

[0133]

[0134] β1+β2+β3=1

[0135] Among them, T b For non-motorized vehicle traffic compliance indicators, T 1i For the fixed-point parking situation during the i-th pick-up and drop-off, T 2i For the case of non-motorized vehicles traveling against the flow of traffic on the road segment during the i-th pick-up and drop-off, T 3i The term represents the situation where a non-motorized vehicle does not travel in the designated lane during the i-th pick-up and drop-off of a road segment. m represents the number of pick-up and drop-off trips for non-motorized vehicles. β1, β2, and β3 are weighting factors that can be set according to the actual situation. Generally, β1 = 0.4, β2 = 0.3, and β3 = 0.3 can be taken.

[0136] Similarly, by collecting the license plate numbers of students' parents' non-motorized vehicles from the school management system, and retrieving the corresponding traffic records from the non-motorized vehicle enforcement management system according to designated areas and times, T can be obtained. 1i T 2i T 3i The record of m.

[0137] Regarding the setting of the weighting factors β1, β2, and β3, it is considered that designated parking directly affects traffic flow at the school gate, while whether or not one drives against the flow of traffic or follows the designated lane affects the road segment. Their impact on the school gate is less than that of designated parking. Therefore, designated parking has a greater weight. The impact of driving against the flow of traffic and following the designated lane on the road segment is similar. Therefore, considering all factors, β1 = 0.4, β2 = 0.3, and β3 = 0.3 are taken as default values. In this embodiment, the weighting factors β1, β2, and β3 are taken as default values, i.e., β1 = 0.4, β2 = 0.3, and β3 = 0.3.

[0138] In this embodiment, T is calculated based on the "whether it is fixed-point parking" record in Table 2. 1i The value of T is calculated based on the "whether it is going in reverse" record in Table 2. 2i The value of T is calculated based on the "whether driving in the designated lane" record in Table 2. 3i The value of m is 10, which includes both picking up and dropping off students.

[0139] Since Student A was picked up and dropped off by a motor vehicle, and Student B was picked up and dropped off by a non-motorized vehicle, the result of Student B's parent's non-motorized vehicle traffic compliance index is:

[0140]

[0141] S5: Based on the results of timely pick-up and drop-off indicators, standardized parking indicators for motor vehicles, and lawful passage indicators for non-motor vehicles, the overall characteristics of parents are calculated.

[0142] The calculation method for the overall parent profile is as follows:

[0143]

[0144] μ1+μ2=1

[0145] Among them, D g For non-parental overall characteristics, A t To ensure parents can pick up and drop off students on time, P s To regulate parking quotas for motor vehicles, T bThe two numbers represent the number of times non-motorized vehicles are picked up and dropped off, respectively, where n represents the number of times motorized vehicles are used and m represents the number of times non-motorized vehicles are used. Because the ratio of non-motorized to motorized vehicles among parents' transportation varies across different school districts, but the impact of parents' compliant use of transportation on the school area is the same, this method uses m and n to describe the types of transportation. Specifically, the values ​​of m and n are collected by registering the transportation used by parents in the school's management system, and the usage frequency is obtained by collecting or calculating vehicle trajectory data from the motorized vehicle parking monitoring system and the non-motorized vehicle management system. Alternatively, data can be collected directly from traffic monitoring equipment installed in the school area and the school's own monitoring equipment at the school gate, using methods such as license plate number recognition or image recognition, to obtain the values ​​of m and n.

[0146] μ1 and μ2 are weighting factors. μ1 represents the weight of the student's parents' timely pick-up and drop-off indicator, while μ2 represents the weight of the motor vehicle's standardized parking indicator and the non-motor vehicle's lawful traffic indicator. Generally, the impact of parents' pick-up and drop-off times and the illegal and irregular behavior of their vehicles on traffic in the area surrounding the school is roughly equivalent. Therefore, the default values ​​for the two weighting factors are the same in this application. Subsequent calculations can be adjusted according to actual circumstances; the default values ​​are: μ1 = 0.5, μ2 = 0.5.

[0147] In this embodiment, the weighting factors μ1 and μ2 are set to default values, namely μ1 = 0.5 and μ2 = 0.5.

[0148] The overall characteristics of student A's parents are as follows:

[0149]

[0150] The overall characteristics of Student B's parents are as follows:

[0151]

[0152] S6: Based on the overall characteristics of parents, create a profile of each parent's pick-up and drop-off and passage behavior to obtain the parent pick-up and drop-off passage characteristic profile results;

[0153] A profile of each parent's pick-up and drop-off and travel behavior is created, specifically including the following steps:

[0154] a1: Constructs behavior colors;

[0155] Behavioral colors include: red, yellow, and green.

[0156] Among them, red represents the aggressive type, indicating a high likelihood of traffic violations;

[0157] Green represents a stable type, indicating that traffic violations are unlikely to occur;

[0158] Yellow represents the intermediate type, falling between the aggressive and the conservative types;

[0159] a2: Construct the correspondence between behavioral colors and overall parent characteristics to obtain the corresponding parent pick-up and drop-off traffic feature profile results:

[0160]

[0161] Among them, C r D creates color-coded profiles of parents' drop-off and pick-up behaviors and traffic patterns. g Results representing the overall characteristics of parents.

[0162] Based on the overall characteristics of the parents of students A and B, it can be seen that the parents of student A are of the "green and stable" type, and are unlikely to commit traffic violations; while the parents of student B are of the "yellow and intermediate" type, and are of a moderate probability of committing traffic violations.

[0163] S7: Construct school traffic management types based on historical data;

[0164] The historical data also includes the total number of traffic violations committed by parents during the entire day while picking up or dropping off their children.

[0165] The method for constructing school traffic management types includes the following steps.

[0166] c1: Identify all parents who use motor vehicles and non-motor vehicles to pick up and drop off students, denoted as: Parents to be observed.

[0167] c2: Calculate the abnormal rate of violation proportion for each parent under observation during the pick-up and drop-off period. The calculation method for the abnormal rate of violation proportion is as follows:

[0168]

[0169] Where: R l The abnormal rate of violations during pick-up and drop-off times; Q i Let be the number of violations during the i-th pick-up / drop-off; Q be the total number of violations during the i-th pick-up / drop-off period for the entire day; t 接送 The designated pick-up and drop-off time is generally based on the school arrival and dismissal times, extending one hour before and after these times. 通行 This represents the average daily passage time under normal circumstances, generally based on 12 hours of normal passage time per day.

[0170] Among them, t 接送 The settings are based on the school arrival and dismissal times configured in the school management system. Q i The number of violations during the i-th pick-up / drop-off is the number of violations counted. Violations include: parking in designated spaces after arrival, parking beyond the permitted time limit, and illegal parking of motor vehicles; and parking in designated areas and illegal passage of non-motor vehicles after arrival.

[0171] Q i Q is based on data collection from motor vehicle parking monitoring systems and non-motor vehicle management systems.

[0172] In this embodiment, the italicized text in Tables 1 and 2 represents records of illegal activities, and the "Total Number of Violations During Pick-up and Drop-off Periods" records statistical data on the number of violations. For each parent, the pick-up and drop-off period is: Pick-up and drop-off time + Drop-off time = 2h + 2h = 4h

[0173] Abnormal rate of violation rate among student A's parents during the data collection period:

[0174]

[0175] The abnormality rate of student B's parents during the data collection period:

[0176]

[0177] c3: Compare the abnormal violation rate with the preset abnormal rate threshold. When the abnormal violation rate is greater than the abnormal rate threshold, mark the corresponding parent as an "abnormal parent".

[0178] Under normal circumstances, the behavioral characteristics of drivers of motor vehicles and non-motor vehicles remain unchanged; that is, without abnormal circumstances, a parent's behavior during pick-up and drop-off times and... 通行 The violations should show the same trend.

[0179] In the technical solution of this application, the ratio of the number of motor vehicle violations and the number of non-motor vehicle violations during the pick-up and drop-off period to the total number of violations throughout the day is calculated, and then compared with the pick-up and drop-off period and t. 通行 The ratio of the two values ​​is used to determine which parents have an increase in traffic violations during pick-up and drop-off times.

[0180] Due to the specific circumstances of the school's location, a slight increase in the abnormal rate of violations by parents is considered normal. However, an excessively high abnormal rate is considered abnormal. Based on historical data, the abnormal rate of violations during pick-up and drop-off times is considered normal if it does not exceed 1.1; it is within a warning range if it exceeds 1.1 but does not exceed 1.2, requiring close monitoring; and it is considered abnormal if it exceeds 1.2.

[0181] That is, in this embodiment, the abnormality rate threshold is set to 1.2. According to the calculation results, the parents of both student A and student B are abnormal parents.

[0182] c4: Count the number of all abnormal parents and calculate the proportion of abnormal parents in the total number of parents, denoted as: abnormal proportion.

[0183] c5: Compare the abnormality rate with the preset observation threshold and alarm threshold;

[0184] When the proportion of abnormal cases exceeds the alarm threshold, the school traffic management type is set to: Controlled.

[0185] When the proportion of abnormal cases is greater than or less than the alarm threshold, but greater than the observation threshold, the school traffic management type is set to: observation type.

[0186] Otherwise, the school traffic management type is set to: Normal.

[0187] Because of the large number of people gathered near schools, some parents exhibiting unusual behavior may appear. However, if the proportion of unusual parents among all parents at a school increases, it indicates that traffic control in the school's area needs to be implemented. Therefore, the technical solution in this application uses alarm thresholds and observation thresholds to monitor the proportion of unusual parents, providing a data basis for alerting relevant departments.

[0188] Based on historical data, when the proportion of abnormal parents in the total number of parents is within a certain range, such as less than 10%, it is considered normal. When it is between 10% and 20%, schools and traffic management departments need to issue warnings. Once it exceeds 20%, traffic management departments and schools need to carry out targeted traffic management, increase police presence during pick-up and drop-off times, maintain traffic order, and optimize traffic management.

[0189] That is, in this embodiment, the observation threshold is set to 10%, and the alarm threshold is set to 20%.

[0190] The method for constructing a comprehensive behavioral profile of students' parents includes the following steps:

[0191] b1: Statistically analyze the parent pick-up and drop-off characteristics of all parents, and calculate the percentage of parents whose behavior is marked in red out of the total number of parents. This percentage is called the "aggressive type ratio".

[0192] b2: Set an aggressive proportion from historical data as the baseline data;

[0193] b3: After the specified start time, continuously acquire aggressive proportions, denoted as: data to be confirmed.

[0194] b4: Compare each data point to be confirmed with the baseline data;

[0195] A pre-defined aggressive alert threshold N is set. When N consecutive data points exceeding the baseline data occur, the overall behavioral profile of the student's parents is set to "monitoring type"; N is a natural number; for example, it is set to 24 (the data collection period includes 6 months).

[0196] Otherwise, the overall behavioral profile of the students' parents is set to: Standard.

[0197] Repeat steps b3 to b4.

[0198] Generally speaking, in traffic management measures jointly implemented by traffic management departments and schools, for parents whose traffic behavior profiles are marked in red (indicating an aggressive parenting style), the school will notify and remind the specific parents of their traffic behavior.

[0199] However, from the perspective of regional traffic management, traffic management departments still need to conduct long-term, continuous monitoring of schools. Generally, the proportion of aggressive parents may temporarily increase due to various reasons, but this increase is not sustained. Therefore, if the proportion of aggressive parents doesn't suddenly surge but remains consistently higher than previous data, it indicates an overall cause for this phenomenon. Therefore, the average proportion of aggressive parents from the previous year is typically used as a baseline, with observations conducted every six months or a year. If the proportion of aggressive parents remains higher than last year, it indicates that traffic management departments need to analyze the specific reasons and develop countermeasures. In this application's technical solution, continuous monitoring data is used to create a profile of the overall behavioral characteristics of student parents, categorized as "to be monitored" and "normal," serving as a data basis for alerting relevant departments.

[0200] S8: Set the cycle period, and execute steps S1 to S7 repeatedly according to the cycle period.

[0201] Indicators such as timely pick-up and drop-off of students by parents, standardized parking of motor vehicles, and lawful passage of non-motorized vehicles are all statistical indicators. The time interval for statistics can be set according to the actual situation. Considering the accuracy and timeliness of the statistical results, the cycle period can be selected as a week, that is, the data of the previous week is used as historical data for recalculation.

[0202] To ensure the implementation of the aforementioned method for profiling student parents' access during drop-off and pick-up, this application also discloses a system for profiling student parents' access during drop-off and pick-up, such as... Figure 2As shown, it includes: an information acquisition module, a calculation module, a determination module, and a profiling and display module. The information acquisition module communicates with the school management system, the motor vehicle parking monitoring system, and the non-motor vehicle management system. These are all existing information management systems. The school management system provides student arrival and dismissal times; the motor vehicle parking monitoring system provides information on parents' illegally parked vehicles, parking in designated spaces, and parking duration; and the non-motor vehicle management system provides information on designated parking and traffic compliance for non-motor vehicles. The information acquisition module, calculation module, profiling module, and display module are built on a server with computing capabilities.

[0203] The information acquisition module collects historical data within a preset data collection period and sends this data to the calculation module. Historical data includes: the actual arrival time of parents picking up and dropping off students at school and the school's preset pick-up and drop-off times; parking status of parents' vehicles after arrival, including whether they parked in designated spaces, exceeded the time limit, or parked illegally; and designated parking and traffic violations of non-motorized vehicles after arrival. The school management system provides student arrival and dismissal times; the motor vehicle parking monitoring system provides information on parents' illegal parking, parking in designated spaces, and parking duration; and the non-motorized vehicle management system provides information on designated parking and traffic compliance of non-motorized vehicles.

[0204] In practice, the server communicates with existing school management systems, motor vehicle parking monitoring systems, and non-motor vehicle management systems via the network. Historical data is collected periodically according to a preset cycle to ensure that the results of student and parent pick-up and drop-off traffic patterns are updated in real time based on the specific circumstances of each school. To ensure the accuracy of the calculation results, depending on the specific information management situation of each school, the information acquisition module can directly collect video or image monitoring data from road monitoring equipment in the school's area, or collect relevant data from other information systems within the school, such as parking management systems and student personal identification card recognition systems, and then send this data to the calculation module for subsequent calculations. Alternatively, relevant historical data can be directly input into the information acquisition module for subsequent calculations via an information input device.

[0205] In this application, the characteristic data of parents picking up and dropping off students are calculated based on actual data from the school management system, motor vehicle parking monitoring system, and non-motor vehicle management system, ensuring the accuracy of the calculation results. The characteristic profile results of parents picking up and dropping off students are used as the data basis to deploy traffic control measures, ensuring the effectiveness of subsequent traffic control measures in the school area based on the characteristic data of parents picking up and dropping off students.

[0206] The calculation module performs calculations based on historical data collected by the information acquisition module.

[0207] The portrait module completes the corresponding graphic drawing according to the user's preset needs and rules, and sends it to the display module for display.

[0208] Based on historical data, the calculation module calculates the results of parents' timely pick-up and drop-off indicators, motor vehicle standardized parking indicators, and non-motor vehicle law-abiding traffic indicators. Then, it calculates the overall characteristics of parents and sends the results to the profiling module.

[0209] In the profile module, based on the preset behavior colors and the correspondence between behavior colors and the overall characteristics of parents, the overall characteristics of parents are obtained. Then, based on the correspondence, the profile is compared with the preset behavior color classification to obtain the color profile results of parents' pick-up and drop-off and passage behaviors, and then sent to the display module for display.

[0210] The calculations performed in the calculation module also include:

[0211] Based on the school management system, all parents who use motor vehicles and non-motor vehicles to pick up and drop off students are recorded as: parents to be observed; based on the motor vehicle parking monitoring system and the non-motor vehicle management system, the number of violations during the pick-up and drop-off period and the total number of violations for each parent to be observed are counted.

[0212] The abnormal violation rate of each parent under observation during the pick-up and drop-off period is calculated: the abnormal violation rate of each parent is compared with the preset abnormal rate threshold. When the abnormal violation rate is greater than the abnormal rate threshold, the corresponding parent is marked as an "abnormal parent". The proportion of abnormal parents in the total number of parents is calculated and recorded as the "abnormal proportion". The abnormal proportion is compared with the preset observation threshold and alarm threshold to determine the school traffic management type. The calculation results are stored on the server for later use.

[0213] The calculations performed in the calculation module also include: statistically analyzing the parent pick-up and drop-off characteristic profiles of all parents, calculating the percentage of parents whose behavior is marked in red out of the total number of parents, denoted as the "aggressive proportion"; continuously acquiring the aggressive proportions after a specified start time, denoted as "data to be confirmed", comparing each data to a preset baseline data, and when N consecutive data points of data to be confirmed are greater than the baseline data, setting the overall behavioral characteristic profile of the student's parents to "monitoring type"; where N is a preset aggressive alarm threshold.

[0214] The calculation module transmits each piece of data to be confirmed and the corresponding comparison result with the baseline data to the profiling module;

[0215] The image processing module displays each piece of data to be confirmed using a specified graphic. For each piece of data to be confirmed that is larger than the baseline data, it marks it with a preset specified color and then passes the image to the display module for display.

[0216] For example, by displaying each piece of data to be confirmed using a bar chart, and marking each piece of data that is greater than the baseline data in red, the monitoring results can be displayed directly.

[0217] This method calculates indicators such as parents' timely pick-up and drop-off, proper parking for motor vehicles, and lawful traffic flow on road sections based on data related to parents' activities. These indicators, along with individual and overall parent profiles, are generated using different colors (red, yellow, green) to represent the parents. The results provide a basis and support for traffic management departments to implement targeted traffic management measures for parents with different characteristics. Furthermore, the proportion of parents with different profile types relative to the total number of parents determines the corresponding traffic management type for the school, providing a data foundation for the school's subsequent traffic management resource allocation.

Claims

1. A method for creating a profile of student parents' traffic characteristics during drop-off and pick-up, characterized in that, It includes the following steps: S1: Set the data collection time period and collect historical data within the data collection time period; The historical data includes: the actual arrival time of parents picking up and dropping off students at school and the school's preset pick-up and drop-off time; the parking status of parents' motor vehicles after arrival, including parking in designated spaces, parking beyond the time limit, and illegal parking; and the parking status of non-motorized vehicles at designated locations and illegal passage on road sections after arrival. S2: Based on the actual arrival time of parents picking up and dropping off students at school and the school's preset pick-up and drop-off time, the results of the parents' on-time pick-up and drop-off index are calculated. S3: Based on the parking status of parents' vehicles after arriving at the school, including parking in designated spaces, exceeding the time limit, and illegal parking, the results of the standardized parking index for motor vehicles are calculated. S4: Based on the historical data of parents' non-motorized vehicles arriving at designated parking spots and illegal passage on road sections, the non-motorized vehicle law-abiding passage index result is calculated; S5: Based on the results of the on-time pick-up and drop-off indicators, the standardized parking indicators for motor vehicles, and the law-abiding traffic indicators for non-motor vehicles, the overall characteristics of parents are calculated. The method for calculating the overall characteristics of the parents is as follows: μ1+μ2=1 Among them, D g For the overall characteristics of parents, A t To ensure parents can pick up and drop off students on time, P s To regulate parking quotas for motor vehicles, T b The non-motorized vehicle compliance index is defined as follows: n is the number of times a motorized vehicle picks up and drops off passengers, m is the number of times a non-motorized vehicle picks up and drops off passengers, and μ1 and μ2 are weighting factors. S6: Based on the overall characteristics of the parents, create a profile of each parent's pick-up and drop-off and passage behavior to obtain the parent pick-up and drop-off passage characteristic profile results; A profile of each parent's pick-up and drop-off and travel behavior is created, specifically including the following steps: a1: Constructs behavior colors; The colors of the behavior include: red, yellow, and green. Among them, red represents the aggressive type, indicating a high likelihood of traffic violations; Green represents a stable type, indicating that traffic violations are unlikely to occur; Yellow represents the intermediate type, falling between the aggressive and the conservative types; a2: Construct the correspondence between behavioral colors and the overall characteristics of the parents to obtain the parent pick-up and drop-off access feature profile results corresponding to the parents: Among them, C r The results of the traffic profile analysis for parents picking up and dropping off their children, D g Results representing the overall characteristics of parents.

2. The method for creating a profile of student parents' pick-up and drop-off traffic characteristics according to claim 1, characterized in that: It also includes the following steps: S7: Based on the results of the parent pick-up and drop-off traffic feature profile, construct an overall behavioral feature profile of the student's parents; The method for constructing a comprehensive behavioral profile of students' parents includes the following steps: b1: Statistically analyze the parent pick-up and drop-off characteristics of all parents and count the percentage of parents whose behavior is marked in red out of the total number of parents. This percentage is called the "aggressive type" ratio. b2: Set the radical proportion from historical data as the baseline data; b3: After the specified start time, continuously acquire the aggressive ratio, and record it as: data to be confirmed. b4: Compare each of the data to be confirmed with the baseline data; A preset aggressive alarm threshold N is set. When N consecutive data points to be confirmed exceed the baseline data, the overall behavioral profile of the student's parents is set to "to be monitored"; where N is a natural number. Otherwise, the overall behavioral profile of the students' parents is set to: Standard. Repeat steps b3 to b4. S8: Set the cycle period, and execute steps S1 to S7 repeatedly according to the cycle period.

3. The method for creating a profile of student parents' pick-up and drop-off traffic characteristics according to claim 1, characterized in that: Before step S8 is implemented, a school traffic management type is constructed based on the historical data. The method for constructing school traffic management types includes the following steps: c1: Identify all parents who use motor vehicles and non-motor vehicles to pick up and drop off students, and denot them as: Parents to be observed; c2: Calculate the abnormal rate of violation proportion for each parent to be observed during the pick-up and drop-off period. The method for calculating the abnormal rate of violation proportion is as follows: Where: R l The abnormal rate of violations during pick-up and drop-off times; Q i Let be the number of violations during the i-th pick-up / drop-off; Q be the total number of violations during the i-th pick-up / drop-off period for the entire day; t 接送 For pick-up and drop-off times; t 通行 This represents the average time it takes for the road to pass under normal circumstances. c3: Compare the violation rate with a preset abnormality threshold. When the violation rate is greater than the abnormality threshold, mark the corresponding parent as an "abnormal parent". c4: Count the number of all the aforementioned abnormal parents and calculate the proportion of the abnormal parents in the total number of parents, denoted as: abnormal proportion; c5: Compare the abnormality ratio with the preset observation threshold and alarm threshold; When the proportion of abnormal cases exceeds the alarm threshold, the school traffic management type is set to: Controlled. When the proportion of abnormal cases is less than or equal to the alarm threshold, but greater than the observation threshold, the school traffic management type is set to: observation type. Otherwise, the school traffic management type is set to: Normal.

4. The method for creating a profile of student parents' pick-up and drop-off traffic characteristics according to claim 1, characterized in that: The calculation method for the parent pick-up and drop-off time indicator is as follows: λ1+λ2=1 Among them, A t A provides a quota for parents to pick up and drop off students on time. 1i To ensure parents drop off their children on time, A 2j For statistics on parents picking up their children on time, n1 represents the number of times students were dropped off, n2 represents the number of times students were picked up, and t represents the number of times students were picked up. 上 For the school's designated school hours, t 1i For the first time a parent drops off their child at school, t 放 The staggered dismissal times for students as stipulated by the school 2i Let λ1 and λ2 be the arrival time of the parents when they pick up their children from school for the i-th time, and let λ1 and λ2 be the weighting factors.

5. The method for creating a profile of student parents' pick-up and drop-off traffic characteristics according to claim 1, characterized in that: The method for calculating the standard parking quota for motor vehicles is as follows: α1+α2+α3＝1 Among them, P s To regulate parking quotas for motor vehicles, P 1i For the i-th instance of illegal parking of a motor vehicle, P 2i P represents the parking status of the vehicle during its i-th parking attempt. 3i This represents the number of times a vehicle exceeds the parking time limit during its i-th parking session, where n is the number of times the vehicle is picked up or dropped off, and tc is the number of times the vehicle is parked beyond the permitted parking time. i Let t be the duration of the i-th parking of the motor vehicle. p A time limit for parking spaces is set, with α1, α2, and α3 as weighting factors.

6. The method for creating a student parent's profile based on their pick-up and drop-off traffic characteristics according to claim 1, characterized in that: The calculation method for the non-motorized vehicle compliance index is as follows: β1+β2+β3＝1 Among them, T b For non-motorized vehicle traffic compliance indicators, T 1i For the fixed-point parking situation during the i-th pick-up and drop-off, T 2i For the case of non-motorized vehicles traveling against the flow of traffic on the road segment during the i-th pick-up and drop-off, T 3i , where m represents the number of times a non-motorized vehicle is picked up or dropped off, and β1, β2, and β3 are weighting factors.

7. A student parent pick-up and drop-off traffic feature profiling system that implements the student parent pick-up and drop-off traffic feature profiling method of claim 1, characterized in that, It includes: information The module includes an acquisition module, a calculation module, a profiling module, and a display module. The information acquisition module collects historical data within a preset data collection time period and sends the historical data into the calculation module. The historical data includes: the actual arrival time of parents picking up and dropping off students at school and the school's preset pick-up and drop-off time; the parking status of parents' motor vehicles after arrival, including parking in designated spaces, parking beyond the time limit, and illegal parking; and the parking status of non-motorized vehicles at designated locations and illegal passage on road sections after arrival. Based on the historical data, the calculation module calculates the results of parents' timely pick-up and drop-off indicators, motor vehicle standardized parking indicators, and non-motor vehicle law-abiding traffic indicators, and then calculates the overall characteristics of parents and sends the results to the profiling module. The profiling module obtains the overall characteristics of the parents based on preset behavior colors and the correspondence between behavior colors and the overall characteristics of the parents. Then, it compares the results with preset behavior color categories based on the correspondence to obtain the color profiling results of the parents' pick-up and drop-off and passage behaviors, and sends them to the display module for display.

8. The student parent pick-up and drop-off traffic feature profiling system according to claim 7, characterized in that: The information acquisition module is communicatively connected to the school management system, the motor vehicle parking monitoring system, and the non-motor vehicle management system. The school management system provides students' school arrival and staggered dismissal times; the motor vehicle parking monitoring system provides information on parents' illegal parking, parking in designated spaces, and parking duration; and the non-motor vehicle management system provides information on non-motor vehicle parking at designated locations and compliance with traffic regulations.

9. The student parent pick-up and drop-off traffic feature profiling system according to claim 8, characterized in that: The calculations performed in the calculation module also include: Based on the school management system, all parents who use motor vehicles and non-motor vehicles to pick up and drop off students are counted and recorded as: parents to be observed; based on the motor vehicle parking monitoring system and the non-motor vehicle management system, the number of violations during the pick-up and drop-off period and the total number of violations for each parent to be observed are counted. The abnormal violation rate of each parent under observation during the pick-up and drop-off period is calculated: the abnormal violation rate of each parent is compared with a preset abnormal rate threshold. When the abnormal violation rate is greater than the abnormal rate threshold, the corresponding parent is marked as an abnormal parent. The proportion of the abnormal parents in the total number of parents is calculated and denoted as the abnormal proportion. The abnormal proportion is compared with a preset observation threshold and an alarm threshold to determine the school traffic management type.

10. The student parent pick-up and drop-off traffic feature profiling system according to claim 7, characterized in that: The calculations performed in the calculation module also include: statistically analyzing the parent pick-up and drop-off characteristic profiles of all parents, and calculating the percentage of parents whose behavior is marked in red out of the total number of parents, denoted as: aggressive proportion; after a specified start time, continuously acquiring the aggressive proportion, denoted as: data to be confirmed, comparing each data to be confirmed with a preset benchmark data, and when N consecutive data to be confirmed are greater than the benchmark data, setting the overall behavioral characteristic profile of the student's parents as: to be monitored; where N is a preset aggressive alarm threshold; The calculation module transmits each piece of data to be confirmed and the corresponding comparison result with the benchmark data to the portrait module; The image module displays each piece of data to be confirmed using a specified graphic. For each piece of data to be confirmed that is greater than the baseline data, it marks it with a preset specified color and then transmits the image to the display module for display.

Images