CN109146150B - Method, system, storage medium and mobile terminal for intelligently selecting logistics collection points - Google Patents

Abstract

The invention discloses a method, a system, a storage medium and a mobile terminal for intelligently selecting a logistics collection point, wherein the method comprises the following steps: the method comprises the steps that a mobile terminal of a first user collects travel data information of the first user, and a travel rule of the first user is analyzed based on the thermal distribution of the first user on a map; analyzing the times of the first user appearing in a preset distance range of each logistics collection point in a preset time range according to the travel rule of the first user; and setting the logistics collection point with the largest number of times as a target collection point, and sending the position information of the target collection point to the mobile terminal of the second user so as to enable the mobile terminal of the second user to carry out path planning. According to the invention, the travel rule of the first user is acquired and analyzed based on the thermal distribution, and the optimal logistics collection point is selected according to the travel rule of the first user, so that the distribution path of the second user to the logistics is improved, the distribution space-time mismatch rate is effectively reduced, and the distribution efficiency is improved.

Description

Method, system, storage medium and mobile terminal for intelligently selecting logistics collection points

technical field

The invention relates to the technical field of logistics distribution, in particular to a method, a system, a storage medium and a mobile terminal for intelligently selecting a logistics collection point.

Background technique

The cost of distribution at the end of logistics has always been a key factor restricting the logistics industry from improving efficiency and reducing costs. With the rapid development of my country's e-commerce in recent years, the number of express delivery has soared. The sharp increase in the number of express packages has put enormous pressure on the logistics end. Facing the end pressure, a new distribution method has been introduced in the end distribution in the city, and user self-pickup has become the mainstream method. Smart express cabinets are constantly being promoted in cities due to their safety, high flexibility and low cost. The "terminal + community O2O" method is currently widely used because it expands the business scope of the original commercial point and adapts to the development of terminal distribution under the situation of tight land use and high rent in the city.

Although the terminal delivery method adopts the user's self-pickup method, which can reduce the proportion of delivery to the door to a certain extent, saving the courier's time, and at the same time, the 24-hour uninterrupted operation of the self-pickup cabinet gives users the convenience of choosing the time to receive the express delivery. However, this method does not greatly improve the time and space difference between the courier and the user, but only gives the user the freedom to choose the time to receive the courier. When the express delivery increases sharply, the self-pickup point at the end also faces the problem of insufficient storage space and the backlog of express delivery by users, which affects the delivery efficiency of express delivery.

Therefore, the prior art still needs to be improved and developed.

Contents of the invention

The technical problem to be solved by the present invention is to provide a method, system, storage medium and mobile terminal for intelligently selecting a logistics collection point in view of the above-mentioned defects of the prior art, aiming at solving the problems of the courier and the user in the prior art. There is no major improvement in the time-space difference, and the delivery efficiency of express delivery is low.

The technical solution adopted by the present invention to solve technical problems is as follows:

A method for intelligently selecting logistics collection points, wherein the method includes:

The mobile terminal of the first user collects the travel data information of the first user, and analyzes the travel rules of the first user based on the heat distribution of the first user on the map;

According to the travel rules of the first user, analyze the number of times the first user appears within the preset distance range of each logistics collection point within the preset time range;

Set the logistics collection point with the largest number of times as the target collection point, and send the location information of the target collection point to the preset mobile terminal of the second user, so that the mobile terminal of the second user can complete the route planning.

In the method for intelligently selecting logistics collection points, the first user is a user who receives logistics, and the second user is a user who distributes logistics.

The method for intelligently selecting logistics collection points, wherein the mobile terminal of the first user collects the travel space information of the first user, and analyzes the first user's travel space based on the heat distribution of the first user on the map. The user's travel rules specifically include:

The mobile terminal of the first user collects and records the travel data information of the first user through a built-in GPS module;

Map the location point where the first user appears in the collected travel data information on the map, and present it in the form of heat distribution;

The travel pattern of the first user is analyzed according to the heat distribution of the first user on the map.

In the method for intelligently selecting a logistics collection point, the travel data includes: the longitude, latitude and current time of the location of the first user.

The method for intelligently selecting logistics collection points, wherein the method also includes:

Presetting a time range and a distance range;

The time range and the distance range are used to filter travel location points that meet the conditions from the travel rules of the first user, and remove travel location points that do not meet the conditions.

The method for intelligently selecting a logistics collection point, wherein, according to the travel rules of the first user, analyzing the preset times when the first user appears at each logistics collection point within a preset time range Specific times within the distance range include:

Calculate the distance from the first user's travel location point to each known logistics collection point, and compare it with a preset distance range;

When the calculated distance satisfies the distance range, the number of times the first user appears at each logistics collection point within a preset time range is calculated.

The method for intelligently selecting a logistics collection point, wherein the logistics collection point with the largest number of times is set as the target collection point, and the location information of the target collection point is sent to the preset second user The mobile terminal of the second user, so that the mobile terminal of the second user performs path planning specifically includes:

The mobile terminal of the first user sets the most calculated logistics collection point as the target collection point;

Acquiring the location information of the target collection point, and sending the location information of the target collection point to the mobile terminal of the second user;

After receiving the location information of the target collection point, the mobile terminal of the second user acquires the current location information of the second user and performs route planning.

A system for intelligently selecting logistics collection points, wherein the system includes: a mobile terminal of a first user and a mobile terminal of a second user connected to the mobile terminal of the first user;

The mobile terminal of the first user includes:

A data acquisition module, configured to collect the travel data information of the first user, and analyze the travel rules of the first user based on the heat distribution of the first user on the map;

The data analysis module is used to analyze the number of times the first user appears within the preset distance range of each logistics collection point within the preset time range according to the travel rules of the first user;

A target selection module, configured to set the logistics collection point with the largest number of times as the target collection point, and send the location information of the target collection point to the preset mobile terminal of the second user;

The mobile terminal user of the second user receives the location information of the target collection point sent by the mobile terminal of the first user, and performs path planning according to the location information;

The first user is a user receiving logistics, and the second user is a user delivering logistics.

A storage medium, on which a plurality of instructions are stored, wherein the instructions are suitable for being loaded and executed by a processor, so as to implement the steps of the method for intelligently selecting logistics collection points described in any one of the above.

A mobile terminal, including: a processor, a storage medium communicated with the processor, the storage medium is suitable for storing a plurality of instructions; the processor is suitable for calling the instructions in the storage medium to execute the implementation The steps of the method for intelligently selecting logistics collection points described in any one of the above.

Beneficial effects of the present invention: the present invention obtains and analyzes the travel rules of the first user based on the heat distribution, and selects the best logistics collection point for the travel rules of the first user, so that the second user can deliver the logistics The route is improved, which effectively reduces the space-time mismatch rate of distribution and improves the distribution efficiency.

Description of drawings

Fig. 1 is a flow chart of a preferred embodiment of the method for intelligently selecting logistics collection points in the present invention.

Fig. 2 is a heat distribution diagram of the user on the map in the method for intelligently selecting logistics collection points of the present invention.

Fig. 3 is a functional principle diagram of the mobile terminal of the present invention.

detailed description

In order to make the object, technical solution and advantages of the present invention more clear and definite, the present invention will be further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

In recent years, the rapid development of my country's e-commerce has led to a sharp increase in the number of express delivery. In 2017, the volume of express delivery in my country exceeded 40 billion pieces, and it is expected to grow at a rate of 10 billion pieces every year. According to the data published on the official website of the State Post Bureau, from January to May 2018, the business income of the postal industry (excluding the direct operating income of Postal Savings Bank) totaled 307.17 billion yuan, a year-on-year increase of 22.9%. In terms of express delivery services, from January to May, the cumulative business volume of express service companies across the country was 17.85 billion pieces, an increase of 28.3% year-on-year; among them, the cumulative business volume of the same city was 4.11 billion pieces, a year-on-year increase of 27.1%; the cumulative business volume of different places was 13.3 billion pieces , an increase of 28.1% year-on-year. Among them, in May, the business volume of national express service companies completed 4.18 billion pieces, a year-on-year increase of 25.1%.

The sharp increase in the number of express packages has put enormous pressure on the logistics end. It is mainly manifested in three aspects. The increase in the number of express delivery has increased the pressure on the distribution center at the end. When the volume of express delivery orders increases sharply, the distribution point at the end is often faced with the risk of warehouse explosion. Secondly, a large number of express packages are backlogged at the end, causing a large number of logistics and delivery delays, and the user experience is also reduced. The cost of the final distribution point also increases accordingly. In my country, the cost of terminal distribution is often higher than 30%, and it will be more obvious in cities due to factors such as rent, transportation, delivery environment, and employment costs.

Facing the end pressure, a new distribution method has been introduced in the end distribution in the city, and user self-pickup has become the mainstream method. While the self-pickup method improves efficiency, it does not improve the time mismatch of delivery. Although the end delivery method adopts the method of user self-pickup, it can reduce the proportion of delivery to the door to a certain extent and save the courier's time. At the same time, the 24-hour uninterrupted operation of the self-pickup cabinet gives users the convenience of choosing a time to collect express delivery. However, this method does not greatly improve the time and space difference between the courier and the user, but only gives the user the freedom to choose the time to receive the courier. When the express delivery increased sharply, the self-pickup point at the end also faced the problem of insufficient storage space and the backlog of express delivery by users.

In order to solve the above problems, the present invention provides a method for intelligently selecting logistics collection points, as shown in Figure 1, the method includes:

Step S100, the mobile terminal of the first user collects the travel data information of the first user, and analyzes the travel rules of the first user based on the heat distribution of the first user on the map;

Step S200, according to the travel pattern of the first user, analyze the number of times the first user appears within the preset distance range of each logistics collection point within the preset time range;

Step S300, set the logistics collection point with the largest number of times as the target collection point, and send the location information of the target collection point to the preset mobile terminal of the second user, so that the mobile terminal of the second user The terminal performs path planning.

The present invention acquires and analyzes the travel rules of the first user based on thermal distribution, and selects the best logistics collection point according to the travel rules of the first user. When the second user receives the best logistics collection point After the address, path planning is carried out to improve the distribution path of the second user for logistics, effectively reducing the time-space mismatch rate of distribution, and improving distribution efficiency.

With the development of mobile terminals, mobile APPs and geographic information technology, it is possible to find the best point of logistics terminal distribution by perceiving user spatial information and combining it with existing logistics technology. The invention gathers user trips in the geographical information in space, presents the law of hotspot distribution, and combines it with the problem of vehicle routing, so as to realize the intelligent selection and route optimization of logistics collection points in the logistics distribution process at the end of the city.

During specific implementation, the present invention predefines two mobile terminals, that is, the mobile terminal of the first user and the mobile terminal of the second user, the first user is the user receiving the logistics, and the second user is the user delivering the logistics ( Courier). The mobile terminal of the first user will collect and record the travel data information of the first user through the built-in GPS module, and the travel data includes: the longitude, latitude and current time of the location of the first user. After the travel data collection is completed, the location point where the first user appears in the collected travel data information is mapped on the map and presented in the form of heat distribution, as shown in Figure 3. According to the heat distribution on the map, the travel pattern of the first user can be analyzed.

It can be seen from Figure 3 that when the first user appears at a certain location, corresponding shadow traces will be left on the map, and the higher the frequency of the first user appearing at the same location, the higher the frequency of the first user appearing on the map. The shadow left will be deeper, so the location where the first user appears most frequently can be known through the position and color depth of the shadow trace on the map, and the mobile terminal of the present invention will know the time when the first user travels to different locations. Recording is performed, so it is possible to quickly obtain the time period in which the most frequently visited places of the first user are roughly distributed, that is, the travel pattern of the first user can be obtained. It can be seen that the present invention maps the collected location points on the map, gathers the user's travel location data in space, and presents them with the distribution of hot spots, and can make the travel rules of the first user more obvious through time constraints embodiment.

Preferably, the present invention can also filter the travel location points of the first user based on the travel data of the first user, delete the location points whose frequency is obviously lower than a certain value, and not display them on the map, so as to better The travel pattern of the first user is analyzed. For example, when the average number of times that the first user appears at the same location per week is less than 3 times, it is considered that the location is not a location that the first user often visits, and the location does not have much influence on the analysis of the travel pattern of the first user. Meaning, in turn, the data of the location can be deleted, the heat distribution is not displayed on the map, and the accuracy of the analysis of travel rules can be improved.

Further, after obtaining the travel data of the first user, the mobile terminal of the first user will calculate the distance from the travel location point of the first user to each known logistics collection point, and compare it with the Preset distance range comparison; when the calculated distance satisfies the distance range, then calculate the number of times the first user appears at each logistics collection point within the preset time range.

The present invention firstly compares the time of the first user at a certain travel location point with the time range, so as to screen out the travel location points that do not meet the time range, and then calculates the selected travel location points and logistics collection points distance, and compare it with the distance range, so as to further filter out the travel location points that meet the distance range. Therefore, the final selected travel location points need to satisfy both the time range and the distance range. Preferably, since the travel data of the first user includes the longitude and latitude data of each location point, the method for calculating the distance in the present invention can adopt the method for calculating the distance between two points on a spherical surface.

Preferably, the present invention presets a time range and a distance range; the time range and distance range are used to further filter out travel location points that meet the conditions from the travel rules of the first user, and eliminate those that do not meet the conditions. point of travel. Since the present invention is mainly aimed at the logistics distribution industry, the convenient time for the first user to receive accessories (from 9:00 am to 18:00 pm) can be set as this time range, and only the travel position points that meet this time range can further calculate the travel position The distance from the point to the known logistics collection point, thus realizing the further screening of the travel location point. In addition, the distance range in the present invention is the best self-collection express mail distance of the first user, for example, 0-500 meters. According to the distance range, further screen out whether the location from the first user's travel location to the known logistics collection point meets the conditions. If the distance from the first user's travel location to the logistics collection point is greater than 500 meters, it means the If the logistics collection point is not the best logistics collection point, the logistics collection point is directly excluded.

After the time range and distance range are screened for the travel location of the first user, the number of occurrences of the first user at each fulfilling logistics collection point is calculated. Since the number of occurrences of the first user at different logistics collection points is different, the logistics collection point with the largest number of occurrences is the best target collection point.

其中Q表示物流代收点的集合，P代表第一用户的集合，i表示用户，j表示物流代收点，Q_j表示物流代收点集合，P_i表示用户集合，k表示用户i的位置点，

表示预设范围内满足预设时间以及预设距离的位置点数量求和，I表示某个记录的位置点是否满足预设时间[t′,t″]以及预设距离L的0-1变量。当其同时满足条件时I＝1否则I＝0。Specifically, in this embodiment, the following algorithm may be used to calculate the number of occurrences of the first user at each logistics collection point. For example, it is necessary to analyze the number of times that the first user appears within the preset distance range L of each logistics collection point within the preset time range [t′,t″], and the recorded times formula

Among them, Q represents the collection of logistics collection points, P represents the collection of the first user, i represents the user, j represents the logistics collection point, Q _j represents the collection of logistics collection points, P _i represents the collection of users, and k represents the location of user i point,

Indicates the sum of the number of location points that meet the preset time and preset distance within the preset range, and I indicates whether a recorded location point meets the preset time [t′,t″] and the 0-1 variable of the preset distance L .I=1 when it satisfies the conditions at the same time, otherwise I=0.

In the formula, D represents the distance function between two points, i represents the user, j represents the logistics collection point, k represents the location of user i, x _ik represents the longitude of user i at the kth position, and y _ik represents the kth position of user i a j represents the longitude position information of the _{j-th logistics collection point, b j represents} the latitude position information of the j-th logistics collection point, and t _ik represents the time of user i at the k-th point.

其中M表示代收点的个数，t_j表示物流代收点j开放时间，t_max表示物流代收点最大开放时间。For the first user, the logistics collection point that satisfies the preset time [t', t"] and the location data recorded by the preset distance L is set as the target collection point. Its model is expressed as

Among them, M represents the number of collection points, t _j represents the opening time of logistics collection point j, and t _max represents the maximum opening time of logistics collection point.

Further, the mobile terminal of the first user sets the most calculated logistics collection point as the target collection point; and obtains the location information of the target collection point, and sets the target collection point The location information is sent to the mobile terminal of the second user. After receiving the location information of the target collection point, the mobile terminal of the second user acquires the current location information of the second user and performs route planning. Preferably, the route planning method in the present invention is also different from the traditional route planning. The present invention combines the route planning of the first user's travel rules, that is, the first user's delivery time range is included in the optimization link, not the traditional one. Consider the shortest distance or the lowest cost of the second user, that is, the courier, for planning. For example, when the second user receives the location information of the target collection point set by the first user, the mobile terminal of the second user will automatically perform route planning, and the convenience of the first user will be taken into account when planning the route. The time of receiving logistics (for example, the first user is only between 9:00 am and 11:00 am for the convenience of receiving logistics), so as to carry out logistics delivery more accurately.

Preferably, in the present invention, the mobile terminal of the first user and the mobile terminal of the second user need to establish a communication connection in advance, and there may be various ways of communication connection, which is not limited in this embodiment. For example, the communication method can adopt the existing communication technology, and design an application program, the mobile terminal of the first user and the mobile terminal of the second user can both log in with their respective ports, and can carry out real-time communication on the application program. In addition, the first user can select and update the target collection point on the application program, and the second user can view the target collection point selected by the first user on the application program, thereby facilitating route planning. Preferably, in the present invention, the route planning of the target collection point for the second user's mobile terminal can be equipped with an existing navigation application to provide the second user (courier) with more convenient navigation services and improve logistics delivery efficiency.

It can be seen that the selection of the target collection point in the present invention is not only based on the first user's travel location point needing to meet the conditions of time range and distance range, but also needs to meet the total number of times the first user appears at each logistics collection point Maximize this condition, so that the selected logistics collection point is the best collection point, and the second user (courier) can carry out logistics distribution according to the selected best collection point, so that the express can be delivered to the receiving point The best collection point for the sender, reducing the time-space mismatch rate of distribution, effectively improving the efficiency of logistics distribution, and not all of them are delivered to the same collection point, causing the risk of warehouse explosion at the collection point.

Based on the above embodiments, the present invention also provides a system for intelligently selecting logistics collection points, the system comprising: a mobile terminal of a first user and a mobile terminal of a second user connected to the mobile terminal of the first user. The first user is a user receiving logistics, and the second user is a user delivering logistics.

The mobile terminal of the first user includes:

A data acquisition module, configured to collect the travel data information of the first user, and analyze the travel rules of the first user based on the heat distribution of the first user on the map;

The data analysis module is used to analyze the number of times the first user appears within the preset distance range of each logistics collection point within the preset time range according to the travel rules of the first user;

The target selection module is configured to set the logistics collection point with the largest number of times as the target collection point, and send the location information of the target collection point to the preset mobile terminal of the second user.

The mobile terminal user of the second user receives the location information of the target collection point sent by the mobile terminal of the first user, and performs path planning according to the location information.

Further, the data acquisition module includes:

The data collection unit is used for the mobile terminal of the first user to collect and record the travel data information of the first user through the built-in GPS module;

The data presentation unit is used to map the location point where the first user appears in the collected travel data information on the map, and present it in the form of heat distribution;

A rule analysis unit, configured to analyze the travel rule of the first user according to the heat distribution of the first user on the map.

The data analysis module includes:

The first calculation unit is used to calculate the distance from the first user's travel location point to each known logistics collection point, and compare it with a preset distance range;

The second calculation unit is configured to calculate the number of times the first user appears at each logistics collection point within a preset time range when the calculated distance satisfies the distance range.

The target selection module includes:

The target setting unit is used for the mobile terminal of the first user to set the most calculated logistics collection point as the target collection point;

An information sending unit, configured to obtain the location information of the target collection point, and send the location information of the target collection point to the mobile terminal of the second user, so that the mobile terminal of the second user can perform route planning .

Based on the above-mentioned embodiments, the present invention also discloses a mobile terminal, as shown in FIG. 3 , including: a processor (processor) 10, a storage medium (memory) 20 connected to the processor 10; It is used to call the program instructions in the storage medium 20 to execute the methods provided in the above embodiments, for example:

The mobile terminal of the first user collects the travel data information of the first user, and analyzes the travel rules of the first user based on the heat distribution of the first user on the map;

According to the travel rules of the first user, analyze the number of times the first user appears within the preset distance range of each logistics collection point within the preset time range;

Set the logistics collection point with the largest number of times as the target collection point, and send the location information of the target collection point to the preset mobile terminal of the second user, so that the mobile terminal of the second user can complete the route planning.

It should be noted that the mobile terminal in this embodiment includes the mobile terminal of the first user and the mobile terminal of the second user, and the mobile terminal of the first user and the mobile terminal of the second user are interchangeable.

An embodiment of the present invention also provides a storage medium, where computer instructions are stored on the storage medium, and the computer instructions cause a computer to execute the methods provided in the foregoing embodiments.

In summary, the present invention provides a method, system, storage medium, and mobile terminal for intelligently selecting logistics collection points. The method includes: the mobile terminal of the first user collects the travel data information of the first user, and based on the first The thermal distribution of the user on the map analyzes the first user's travel law; according to the first user's travel law, analyze the first user's appearance within the preset distance range of each logistics collection point within the preset time range Number of times: set the logistics collection point with the largest number of times as the target collection point, and send the location information of the target collection point to the mobile terminal of the second user, so that the mobile terminal of the second user can perform path planning. The present invention obtains and analyzes the travel rules of the first user based on the thermal distribution, and selects the best logistics collection point according to the travel rules of the first user, so that the distribution path of the second user for the logistics is improved, effectively reducing the The time-space mismatch rate of distribution is reduced, and the distribution efficiency is improved.

It should be understood that the application of the present invention is not limited to the above examples, and those skilled in the art can make improvements or transformations according to the above descriptions, and all these improvements and transformations should belong to the protection scope of the appended claims of the present invention.

Claims (7)

1. A method of intelligently selecting logistics collection point, characterized in that, the method comprises: The mobile terminal of the first user collects the travel data information of the first user, and analyzes the travel rules of the first user based on the heat distribution of the first user on the map; According to the travel rules of the first user, analyze the number of times the first user appears within the preset distance range of each logistics collection point within the preset time range; Set the logistics collection point with the largest number of times as the target collection point, and send the location information of the target collection point to the preset mobile terminal of the second user, so that the mobile terminal of the second user can complete the route planning; The first user is a user receiving logistics, and the second user is a user delivering logistics; According to the travel rules of the first user, analyzing the number of times the first user appears within the preset distance range of each logistics collection point within the preset time range specifically includes: Calculate the distance from the first user's travel location point to each known logistics collection point, and compare it with a preset distance range; When the calculated distance satisfies the distance range, calculate the number of times the first user appears at each logistics collection point within the preset time range; The method further includes: the mobile terminal of the first user updates the target collection point, and sends the updated target collection point to the mobile terminal of the second user; The method also includes: Presetting a time range and a distance range; The time range and the distance range are used to filter out the travel location points that meet the conditions from the travel rules of the first user, and remove the travel location points that do not meet the conditions; When the calculated distance satisfies the distance range, the calculation of the number of times the first user appears at each logistics collection point within the preset time range includes: It is necessary to analyze the number of times that the first user appears within the preset distance range L of each logistics collection point within the preset time range [t′,t″], and the recorded times formula

Among them, Q represents the set of logistics collection points, P represents the set of first users, i represents the user, j represents the logistics collection point, Q _j represents the collection of logistics collection points, P _i represents the set of users, and k represents the location of user i point,

Indicates the sum of the number of location points that meet the preset time and preset distance within the preset range, and I indicates whether a recorded location point meets the preset time [t′,t″] and the 0-1 variable of the preset distance L , when it satisfies the conditions at the same time, I=1, otherwise I=0,

In the formula, D represents the distance function between two points, i represents the user, j represents the logistics collection point, k represents the location of user i, x _ik represents the longitude of user i at the kth position, and y _ik represents the kth position of user i The latitude of a location point, _aj represents the longitude location information of the jth logistics collection point, _bj represents the latitude location information of the jth logistics collection point, and _tik represents the time of user i at the kth location point; For the first user, the logistics collection point that satisfies the preset time [t',t"] and the preset distance L with the most recorded location data is set as the target collection point, and the model is expressed as

Among them, M represents the number of collection points, t _j represents the opening time of logistics collection point j, and t _max represents the maximum opening time of logistics collection point. 2. The method for intelligently selecting logistics collection points according to claim 1, wherein the mobile terminal of the first user collects the travel space information of the first user, and based on the information of the first user on the map, According to the heat distribution analysis, the travel rules of the first user specifically include: The mobile terminal of the first user collects and records the travel data information of the first user through a built-in GPS module; Map the location point where the first user appears in the collected travel data information on the map, and present it in the form of heat distribution; The travel pattern of the first user is analyzed according to the heat distribution of the first user on the map. 3. The method for intelligently selecting a logistics collection point according to claim 2, wherein the travel data includes: the longitude, latitude and current time of the location of the first user. 4. The method for intelligently selecting a logistics collection point according to claim 1, wherein the logistics collection point with the largest number of times is set as a target collection point, and the location information of the target collection point is The sending to the preset mobile terminal of the second user, so that the mobile terminal of the second user performs path planning specifically includes: The mobile terminal of the first user sets the most calculated logistics collection point as the target collection point; Acquiring the location information of the target collection point, and sending the location information of the target collection point to the mobile terminal of the second user; After receiving the location information of the target collection point, the mobile terminal of the second user acquires the current location information of the second user and performs route planning. 5. A system for intelligently selecting logistics collection points, characterized in that the system includes: a mobile terminal of a first user and a mobile terminal of a second user connected to the mobile terminal of the first user; The mobile terminal of the first user includes: A data acquisition module, configured to collect the travel data information of the first user, and analyze the travel rules of the first user based on the heat distribution of the first user on the map; The data analysis module is used to analyze the number of times the first user appears within the preset distance range of each logistics collection point within the preset time range according to the travel rules of the first user; A target selection module, configured to set the logistics collection point with the largest number of times as the target collection point, and send the location information of the target collection point to the preset mobile terminal of the second user; The mobile terminal user of the second user receives the location information of the target collection point sent by the mobile terminal of the first user, and performs path planning according to the location information; The first user is a user receiving logistics, and the second user is a user delivering logistics; According to the travel rules of the first user, analyzing the number of times the first user appears within the preset distance range of each logistics collection point within the preset time range specifically includes: Calculate the distance from the first user's travel location point to each known logistics collection point, and compare it with a preset distance range; When the calculated distance satisfies the distance range, calculate the number of times the first user appears at each logistics collection point within the preset time range; Presetting a time range and a distance range; The time range and the distance range are used to filter out the travel location points that meet the conditions from the travel rules of the first user, and remove the travel location points that do not meet the conditions; When the calculated distance satisfies the distance range, the calculation of the number of times the first user appears at each logistics collection point within the preset time range includes: It is necessary to analyze the number of times that the first user appears within the preset distance range L of each logistics collection point within the preset time range [t′,t″], and the recorded times formula

Among them, Q represents the set of logistics collection points, P represents the set of first users, i represents the user, j represents the logistics collection point, Q _j represents the collection of logistics collection points, P _i represents the set of users, and k represents the location of user i point,

Indicates the sum of the number of location points that meet the preset time and preset distance within the preset range, and I indicates whether a recorded location point meets the preset time [t′,t″] and the 0-1 variable of the preset distance L , when it satisfies the conditions at the same time, I=1, otherwise I=0,

In the formula, D represents the distance function between two points, i represents the user, j represents the logistics collection point, k represents the location of user i, x _ik represents the longitude of user i at the kth position, and y _ik represents the kth position of user i The latitude of a location point, _aj represents the longitude location information of the jth logistics collection point, _bj represents the latitude location information of the jth logistics collection point, and _tik represents the time of user i at the kth location point; For the first user, the logistics collection point that satisfies the preset time [t',t"] and the preset distance L with the most recorded location data is set as the target collection point, and the model is expressed as

Among them, M represents the number of collection points, t _j represents the opening time of logistics collection point j, and t _max represents the maximum opening time of logistics collection point. 6. A storage medium on which a plurality of instructions are stored, wherein the instructions are adapted to be loaded and executed by a processor, so as to implement the intelligent selection logistics agent described in any one of claims 1-4. The steps of the method of collecting points. 7. A mobile terminal, characterized in that it comprises: a processor, a storage medium communicatively connected to the processor, the storage medium is suitable for storing multiple instructions; the processor is suitable for calling the instructions in the storage medium , to execute the steps for implementing the method for intelligently selecting logistics collection points described in any one of claims 1-4 above.

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