Logistics parcel distribution system based on big data

Abstract

The invention discloses a logistics parcel distribution system based on big data, which comprises a data acquisition module, a distribution analysis module and a distribution route scheme output module, and is characterized in that the data acquisition module is used for acquiring user housing home information; the delivery analysis module is used for analyzing the delivery sequence of the parcel deliveryman to the target delivery user, the parcel deliveryman analyzes the delivery sequence of the parcel deliveryman to the target delivery user in the region, and the monitoring data in the user housing home system is called to predict the user sleep state information, so that the parcel delivery order is analyzed, and the parcel delivery order is analyzed. The preset delivery route of the parcel deliveryman is adjusted, so that the parcel deliveryman can deliver to the user through the parcel delivery route scheme planned by the system, the rationality of the logistics parcel delivery system to the delivery order of the delivery target user is improved, the delivery time of the parcel deliveryman to the target delivery user is shortened, and the delivery efficiency is improved. The method has the characteristics of high humanization degree and high logistics distribution target detection capability.

Description

Technical Field

[0001] The present invention relates to the technical field of logistics distribution management, and in particular to a logistics package distribution system based on big data. Background Art

[0002] As the trend of informatization gradually sweeps across the globe, coupled with the rise of e-commerce and the continuous growth of global logistics business, the logistics and distribution industry has also begun to develop towards networking, dataization, and informationization. Due to the rapid increase in the number of logistics packages, the distribution of logistics packages has become more complex and uncontrollable. Data-driven logistics and distribution methods can promote the intelligent transformation of the logistics and distribution industry. Combining big data technology with logistics and distribution can effectively improve logistics and distribution efficiency, enhance customer satisfaction, and meet the more diverse logistics needs of the huge market. Therefore, there is an urgent need for intelligent management of logistics and parcel delivery.

[0003] Currently, package delivery primarily involves using a mobile device carried by a delivery driver to call the target delivery user. Once the target delivery user answers the call, the delivery driver then delivers the package to the target delivery user's location. Prior art logistics package delivery systems use navigation functions to consider the transit time of different delivery routes and select the route that will deliver the package to the customer the fastest. However, since most logistics delivery operations occur over a wide range of time periods, when a delivery driver uses a mobile device to call the target delivery user, the target delivery user may still be asleep, not answering the call, and unable to receive the delivery driver's package. The delivery system is often unable to adjust the route in a timely manner, causing the delivery driver to waste unnecessary delivery time and significantly reducing delivery efficiency. Therefore, it is necessary to design a logistics package delivery system based on big data that is highly user-friendly and has strong logistics delivery target detection capabilities. Summary of the Invention

[0004] The purpose of the present invention is to provide a logistics package delivery system based on big data to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a logistics parcel delivery system based on big data, comprising a data acquisition module, a delivery analysis module and a delivery route plan output module, wherein the data acquisition module is used to monitor users through a residential home terminal using the monitoring function of the home terminal to obtain residential home information of the target delivery user; the delivery analysis module is used to analyze the order in which parcel delivery personnel deliver to target delivery users in a region; and the delivery route plan output module is used to output the parcel delivery route plan to a mobile terminal carried by the parcel delivery personnel, so that the parcel delivery personnel can deliver to the user through the parcel delivery route plan planned by the system.

[0006] According to the above technical solution, the data acquisition module includes a user feature recognition module and an action status judgment module. The user feature recognition module is used to identify whether user features appear in the house through a camera; the action status judgment module is used to judge the action status of the user corresponding to the user features identified in the house.

[0007] According to the above technical solution, the delivery analysis module includes a route possibility detection module and a delivery route formulation module. The route possibility detection module is used to detect the possibility of all routes for the package delivery person to deliver the package; the delivery route formulation module is used to analyze the possibility of all routes and formulate the most suitable delivery route.

[0008] According to the above technical solution, the delivery route formulation module includes a route simplification submodule and a user status update submodule. The route simplification submodule is used to simplify the delivery route of the parcel delivery person; the user status update submodule is used to update the action status of the remaining target delivery users based on the monitoring information of the unfinished delivery target users after the parcel delivery person completes the intermittent delivery route.

[0009] According to the above technical solution, the operation method of the logistics package delivery system based on big data includes the following steps:

[0010] Collecting the housing information of the target delivery user, wherein the housing information of the target delivery user is obtained by monitoring the user using the monitoring function of the housing terminal;

[0011] Analyze the order in which package delivery personnel deliver to multiple target delivery users within a region;

[0012] Complete the delivery route analysis and output the package delivery route plan in real time to the mobile terminal carried by the package delivery person.

[0013] According to the above technical solution, the collection of the target delivery user's housing information includes:

[0014] When it is detected that the mobile terminal carried by the package delivery person calls the target delivery user but no one answers, the mobile terminal accesses the target delivery user's home terminal to obtain the status information of the target delivery user's home;

[0015] Access the camera in the home to capture a panoramic view of the house after the camera is turned on. The user's features are identified within the panoramic view. If the user's features are identified, the user's mobile device in the house is accessed and the sleep monitoring software in the mobile device is enabled to monitor the user's sleep status and predict the user's sleep time.

[0016] The current time node is retrieved, and the time node when the user is no longer in a sleeping state is calculated based on the predicted user sleep time period information, and the time node when the user is no longer in a sleeping state is recorded as the time node when the target delivery user is no longer in a state where it is difficult to move.

[0017] According to the above technical solution, the method for accessing the home terminal of the target delivery user is specifically as follows:

[0018] In the area, the user signs a link agreement with the logistics package delivery system that enables access to data in the residential home terminal, so that the logistics package delivery system can access and collect relevant information of the residential home terminal.

[0019] According to the above technical solution, the analysis of the order in which the package delivery person delivers to multiple target delivery users in the area includes:

[0020] The built-in positioning function is used to obtain the location of the package delivery person, calibrate the current time node, and use the navigation function to obtain the possible routes of the package delivery person in the area, and store the possible routes in the route database;

[0021] Retrieve a target delivery user whose package delivery distance is less than A kilometers. Based on the obtained feasible routes, obtain the time it takes for the package delivery person to reach the target delivery user along each route. Based on the delivery time, predict the time when the package delivery person will arrive at the target user's residence according to the route. Detect whether the time when the package delivery person arrives at the target user's residence according to the route is within a first time period formed between the current time point and the time point when the target delivery user is no longer in a difficult-to-move state. If the time point is within the first time period, set the delivery tag for the user to "not on the way delivery"; conversely, if the time point is not within the first time period, set the delivery tag for the user to "on the way delivery";

[0022] Count the number of delivery target users of the packages within the route whose delivery labels are set to "not on the way delivery" and "on the way delivery" respectively S0 and n1-S0, where n1 is the total number of target delivery users retrieved, and calculate the first label ratio

[0023] According to the above steps, the label ratios of "not on the way delivery" and "on the way delivery" in different travel routes are calculated respectively, and the travel route corresponding to the minimum label ratio is obtained. The route is set as the initial delivery route. Based on the analysis of the initial delivery route, when the package delivery person detects that the current target delivery user is in a state where it is difficult to move while traveling along the initial delivery route, the first delivery route is set.

[0024] According to the above technical solution, the method for setting the first delivery route is specifically as follows:

[0025] By calculating the delivery time of a parcel delivery person to a target delivery user location corresponding to a "non-stop delivery" tag, setting the user tag of the "non-stop delivery" as the "first non-stop delivery target", marking the travel direction corresponding to the "first non-stop delivery" user tag as a first non-travel route, obtaining the route length information of the first non-travel route through the navigation function, and predicting the excess time t consumed by the parcel delivery person on the non-travel route based on the normal delivery speed of the parcel delivery person stored in the system;

[0026] After extracting the excess time t consumed by the parcel delivery person on the non-travel route, the time t is subtracted from the time nodes of the first delivery route to the different delivery target users to obtain the time nodes when the parcel delivery person does not travel to the different delivery target users from the first non-travel route.

[0027] Repeat the above steps, and detect the time nodes when the package delivery person does not travel from the first non-travel route to different delivery target users in turn, and judge whether the target delivery user corresponding to the original "not on the way delivery" label is no longer in a state of difficulty in moving when the package delivery person delivers the package to the target delivery user. If it is judged that the target delivery user is no longer in a state of difficulty in moving, the user label that meets the judgment condition is changed to "on the way delivery", and the number of delivery target users of packages in the travel route with the delivery label set to "not on the way delivery" and "on the way delivery" is re-counted. The number of labels S1 and n2-S1 are set respectively, and the second label ratio is calculated. Calculate the label ratios of "not on-the-way delivery" and "on-the-way delivery" in different routes respectively, retrieve the stored feasible route data in the route database, locate the feasible route that overlaps with the location of the package delivery person, obtain the route corresponding to the minimum label ratio among the located feasible routes, and set the route as the first delivery route, where n2 is the total number of target delivery users remaining at the current package delivery person's driving location.

[0028] According to the above technical solution, the method for completing the delivery route analysis is specifically as follows:

[0029] Repeat all the above steps, and mark the non-travel direction routes corresponding to the "not on the way delivery" label as the second non-travel direction route, the third non-travel direction route...the Cth non-travel direction route in turn. After completing the simplification of one non-travel direction route, judge whether the target delivery user corresponding to the remaining "not on the way delivery" label is no longer in a difficult-to-move state when the package delivery person arrives at the location of the target delivery user. After all the target delivery users corresponding to the "not on the way delivery" label are converted to "on the way delivery" labels or marked as the "i-th not on the way delivery target", the delivery analysis process is terminated, where C is the total number of non-travel direction routes obtained after the delivery analysis process is terminated, and i is the number of targets marked as not on the way delivery targets.

[0030] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: the present invention analyzes the order in which package delivery personnel deliver packages to target delivery users in the area, retrieves monitoring data from the user's home system, predicts the user's sleep status information, and adjusts the package delivery personnel's preset delivery route based on the living status, so that the package delivery personnel can deliver packages to users through the package delivery route plan planned by the system, thereby improving the rationality of the delivery order of the logistics package delivery system to the target delivery users and greatly reducing the delivery time of the package delivery personnel to the target delivery users. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0032] Figure 1 It is a schematic diagram of the system module composition of the present invention. DETAILED DESCRIPTION

[0033] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0034] See also Figure 1 The present invention provides a technical solution: a logistics package delivery system based on big data, comprising:

[0035] Data collection module, delivery analysis module and delivery route plan output module. The data collection module is used to monitor users through the home terminal using the monitoring function of the home terminal to obtain the home information of the target delivery user; the delivery analysis module is used to analyze the order in which the package delivery personnel deliver to the target delivery users in the area; the delivery route plan output module is used to output the package delivery route plan to the mobile terminal carried by the package delivery personnel, so that the package delivery personnel can deliver to the user through the package delivery route plan planned by the system.

[0036] The present invention analyzes the order in which package delivery personnel deliver packages to target delivery users in a region, retrieves monitoring data from the user's home system, predicts the user's sleep status information, and adjusts the package delivery personnel's preset delivery routes based on the living status, so that the package delivery personnel can deliver packages to users according to the package delivery route plan planned by the system, thereby improving the rationality of the delivery sequence of the logistics package delivery system to the target delivery users and greatly reducing the delivery time of the package delivery personnel to the target delivery users.

[0037] The data acquisition module includes a user feature recognition module and an action status judgment module. The user feature recognition module is used to identify whether user features appear in the house through the camera; the action status judgment module is used to judge the action status of the user corresponding to the user features identified in the house.

[0038] The delivery analysis module includes a route possibility detection module and a delivery route formulation module. The route possibility detection module is used to detect the possibility of all routes that the package delivery person may take to deliver the package; the delivery route formulation module is used to analyze the possibility of all routes and formulate the most appropriate delivery route.

[0039] The delivery route planning module includes a route simplification submodule and a user status update submodule. The route simplification submodule is used to simplify the delivery routes of the parcel delivery personnel; the user status update submodule is used to update the action status of the remaining target delivery users based on the monitoring information of the unfinished delivery target users after the parcel delivery personnel complete the intermittent delivery routes.

[0040] In a preferred embodiment, the operation method of the logistics package delivery system based on big data includes the following steps:

[0041] Collecting the housing and home information of the target delivery user, the housing and home information of the target delivery user is obtained by monitoring the user using the monitoring function of the housing and home terminal;

[0042] Analyze the order in which package delivery personnel deliver to multiple target delivery users within a region;

[0043] Complete the delivery route analysis and output the package delivery route plan in real time to the mobile terminal carried by the package delivery person.

[0044] In this embodiment, the collection of the target delivery user's housing information includes:

[0045] When it is detected that the mobile terminal carried by the package delivery person calls the target delivery user but no one answers, the mobile terminal accesses the target delivery user's home terminal to obtain the status information of the target delivery user's home;

[0046] Access the camera in the home to capture a panoramic view of the house after the camera is turned on. Identify the user's features within the panoramic view. If the user's features are identified, access the mobile device bound to the user in the house and access the sleep monitoring software in the mobile device to monitor the user's sleep and predict the user's sleep time period. The sleep monitoring software has a user sleep cycle monitoring function that can predict the duration of the user's sleep after the current time point.

[0047] The current time node is retrieved, and the time node when the user is no longer in a sleeping state is calculated based on the predicted user sleep time period information, and the time node when the user is no longer in a sleeping state is recorded as the time node when the target delivery user is no longer in a state where it is difficult to move.

[0048] In this embodiment, the method for accessing the home terminal of the target delivery user is specifically as follows:

[0049] Within the region, users sign a logistics package delivery system link agreement that can access data in residential home terminals, allowing the logistics package delivery system to access and collect relevant information of residential home terminals, where the region is the residential area of users who install the smart residential home system.

[0050] In this embodiment, analyzing the order in which a package delivery person delivers packages to multiple target delivery users in a region includes:

[0051] The built-in positioning function is used to obtain the location of the package delivery person, calibrate the current time node, and use the navigation function to obtain the possible routes of the package delivery person in the area, and store the possible routes in the route database;

[0052] Retrieve target delivery users whose package delivery distance is less than A kilometers. Based on the obtained travelable routes, where A is the radius limit of a single package delivery range defined by the package delivery system, obtain the time it takes for the package delivery driver to reach the target delivery user along each travel route. Based on the delivery time, predict the time when the package delivery driver will arrive at the target user's residence according to the travel route. Check whether the time when the package delivery driver arrives at the target user's residence according to the travel route is within a first time period formed between the current time point and the time point when the target delivery user is no longer in a difficult-to-move state. If the time point is within the first time period, set the delivery label for the user to "not on the way delivery"; otherwise, if the time point is not within the first time period, set the delivery label for the user to "on the way delivery";

[0053] Count the number of delivery target users of the packages within the route whose delivery labels are set to "not on the way delivery" and "on the way delivery" respectively S0 and n1-S0, where n1 is the total number of target delivery users retrieved, and calculate the first label ratio

[0054] According to the above steps, the label ratios of "not on the way delivery" and "on the way delivery" in different routes are calculated respectively, and the route corresponding to the minimum label ratio is obtained. The route is set as the initial delivery route. Based on the analysis of the initial delivery route, when the package delivery person detects that the current target delivery user is in a state where it is difficult to move while traveling along the initial delivery route, the first delivery route is set.

[0055] If the parcel delivery driver reduces the number of target delivery users, the delivery time will be reduced accordingly, which will also affect the time when the subsequent parcel delivery drivers deliver the packages to the users;

[0056] This technical solution solves the problem that when a parcel delivery person is delivering a parcel to different target delivery users, the target delivery user may be in a state of being unable to move and therefore unable to receive the parcel, causing the parcel delivery person to waste unnecessary delivery time.

[0057] In this embodiment, the method for setting the first delivery route is specifically as follows:

[0058] By calculating the delivery time of the parcel delivery person to the target delivery user location corresponding to the "off-route delivery" tag, the user tag of the "off-route delivery" is set as the "first off-route delivery target", and the travel direction corresponding to the "first off-route delivery" user tag is marked as the first off-route route. The route length information of the first off-route route is obtained through the navigation function. Based on the normal delivery speed of the parcel delivery person stored in the system, the excess time t consumed by the parcel delivery person on the off-route route is predicted;

[0059] After extracting the excess time t consumed by the parcel delivery person on the non-travel route, the time t is subtracted from the time nodes of the first delivery route to the different delivery target users in sequence to obtain the time nodes when the parcel delivery person does not travel from the first non-travel route to the different delivery target users.

[0060] Repeat the above steps, and detect the time nodes when the package delivery person does not travel from the first non-travel route to different delivery target users in turn, and judge whether the target delivery user corresponding to the original "not on the way delivery" label is no longer in a state of difficulty in moving when the package delivery person delivers the package to the target delivery user. If it is judged that the target delivery user is no longer in a state of difficulty in moving, the user label that meets the judgment condition is changed to "on the way delivery", and the number of delivery target users of packages in the travel route with the delivery label set to "not on the way delivery" and "on the way delivery" is re-counted. The number of labels S1 and n2-S1 are respectively, and the second label ratio is calculated. Calculate the label ratios of "not on-the-way delivery" and "on-the-way delivery" in different routes respectively, retrieve the stored feasible route data in the route database, locate the feasible route that overlaps with the location of the package delivery person, obtain the route corresponding to the minimum label ratio among the located feasible routes, and set the route as the first delivery route, where n2 is the total number of target delivery users remaining at the current package delivery person's driving location.

[0061] When a parcel delivery driver delivers the parcel to the user by reversing the route, additional factors need to be considered: since the first route needs to deliver to all users, a certain amount of time is consumed in the non-travel direction when selecting the delivery route;

[0062] Through technical solutions, the problem of package delivery personnel having difficulty in quickly finding the shortest delivery route in two delivery routes was solved. By retrieving monitoring data from the user's home system, the user's sleep status information was predicted, and the package delivery personnel's preset delivery route was adjusted based on the living status. This improved the rationality of the logistics package delivery system's delivery order for the target users and greatly reduced the delivery time of the package delivery personnel to the target users.

[0063] In this embodiment, the method for completing the delivery route analysis is specifically as follows:

[0064] Repeat all the above steps, and mark the non-travel direction routes corresponding to the "not on the way delivery" label as the second non-travel direction route, the third non-travel direction route...the Cth non-travel direction route in turn. After completing the simplification of one non-travel direction route, judge whether the target delivery user corresponding to the remaining "not on the way delivery" label is no longer in a difficult-to-move state when the package delivery person arrives at the location of the target delivery user. After all the target delivery users corresponding to the "not on the way delivery" label are converted to "on the way delivery" labels or marked as the "i-th not on the way delivery target", the delivery analysis process is terminated, where C is the total number of non-travel direction routes obtained after the delivery analysis process is terminated, and i is the number of targets marked as not on the way delivery targets.

[0065] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0066] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art will be able to modify the technical solutions described in the aforementioned embodiments or substitute equivalents for some of the technical features. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A logistics package delivery system based on big data, characterized by: It includes a data collection module, a delivery analysis module and a delivery route plan output module. The data collection module is used to monitor users through the home terminal using the monitoring function of the home terminal to obtain the home information of the target delivery user; The delivery analysis module is used to analyze the order in which parcel delivery personnel deliver to target delivery users in the area; the delivery route plan output module is used to output the parcel delivery route plan to the mobile terminal carried by the parcel delivery personnel, so that the parcel delivery personnel can deliver to the users according to the parcel delivery route plan planned by the system.

2. The big data-based logistics package delivery system according to claim 1, characterized in that: The data acquisition module includes a user feature recognition module and an action status judgment module. The user feature recognition module is used to identify whether user features appear in the house through a camera; the action status judgment module is used to judge the action status of the user corresponding to the user features identified in the house.

3. The big data-based logistics package delivery system according to claim 2, characterized in that: The delivery analysis module includes a route possibility detection module and a delivery route formulation module. The route possibility detection module is used to detect the possibility of all routes that the package delivery person may take to deliver the package; the delivery route formulation module is used to analyze the possibility of all routes and formulate the most appropriate delivery route.

4. The big data-based logistics package delivery system according to claim 3, characterized in that: The delivery route formulation module includes a route simplification submodule and a user status update submodule. The route simplification submodule is used to simplify the delivery route of the package delivery person; the user status update submodule is used to update the action status of the remaining target delivery users based on the monitoring information of the unfinished delivery target users after the package delivery person completes the intermittent delivery route.

5. The big data-based logistics package delivery system according to claim 4, characterized in that: The operation method of the logistics package delivery system based on big data includes the following steps: Collecting the housing information of the target delivery user, wherein the housing information of the target delivery user is obtained by monitoring the user using the monitoring function of the housing terminal; Analyze the order in which package delivery personnel deliver to multiple target delivery users within a region; Complete the delivery route analysis and output the package delivery route plan in real time to the mobile terminal carried by the package delivery person.

6. The big data-based logistics package delivery system according to claim 5, characterized in that: The housing information of the target delivery user is collected, including: When it is detected that the mobile terminal carried by the package delivery person calls the target delivery user but no one answers, the mobile terminal accesses the target delivery user's home terminal to obtain the status information of the target delivery user's home; Access the camera in the home to capture a panoramic view of the house after the camera is turned on. The user's features are identified within the panoramic view. If the user's features are identified, the user's mobile device in the house is accessed and the sleep monitoring software in the mobile device is enabled to monitor the user's sleep status and predict the user's sleep time. The current time node is retrieved, and the time node when the user is no longer in a sleeping state is calculated based on the predicted user sleep time period information, and the time node when the user is no longer in a sleeping state is recorded as the time node when the target delivery user is no longer in a state where it is difficult to move.

7. The big data-based logistics package delivery system according to claim 6, characterized in that: The method of accessing the home terminal of the target delivery user is specifically as follows: In the area, the user signs a link agreement with the logistics package delivery system that enables access to data in the residential home terminal, so that the logistics package delivery system can access and collect relevant information of the residential home terminal.

8. The big data-based logistics package delivery system according to claim 7, characterized in that: The analysis of the order in which the package delivery person delivers to multiple target delivery users in the area includes: The built-in positioning function is used to obtain the location of the package delivery person, calibrate the current time node, and use the navigation function to obtain the possible routes of the package delivery person in the area, and store the possible routes in the route database; Retrieve target delivery users whose package delivery distance is less than A kilometers. Based on the obtained feasible routes, obtain the time it takes for the package delivery personnel to reach the target delivery users along the routes. Based on the delivery time, predict the time when the package delivery personnel will arrive at the target user's residence according to the routes. Check whether the time when the package delivery personnel arrives at the target user's residence according to the routes falls within a first time period between the current time and the time when the target delivery user is no longer in a difficult-to-move state. If the time is within the first time period, set the delivery tag for the user to "not on the way delivery"; otherwise, set the delivery tag for the user to "on the way delivery"; Count the number of delivery target users with delivery labels set to "not on the way" and "on the way" for the packages within the route, and the number of labels is S0 and n1-S0 respectively, where n1 is the total number of target delivery users retrieved, and calculate the first label ratio. According to the above steps, the label ratios of "not on-the-way delivery" and "on-the-way delivery" for different routes are calculated respectively. The route corresponding to the minimum label ratio is obtained, and the route is set as the initial delivery route. Based on the analysis of the initial delivery route, when the package delivery person detects that the current target delivery user is in a state of difficulty in moving while traveling along the initial delivery route, the first delivery route is set.

9. The big data-based logistics package delivery system according to claim 8, characterized in that: The method for setting the first delivery route is specifically as follows: By calculating the delivery time of a parcel delivery person to a target delivery user location corresponding to a "non-stop delivery" tag, the user tag of the "non-stop delivery" is set as the "first non-stop delivery target", and the travel direction corresponding to the "first non-stop delivery" user tag is marked as a first non-travel route. The route length information of the first non-travel route is obtained through the navigation function, and based on the normal delivery speed of the parcel delivery person stored in the system, the excess time t consumed by the parcel delivery person on the non-travel route is predicted; After extracting the excess time t consumed by the parcel delivery person on the non-travel route, the time t is subtracted from the time nodes of the first delivery route to the different delivery target users to obtain the time nodes when the parcel delivery person does not travel to the different delivery target users from the first non-travel route. Repeat the above steps, and detect the time nodes when the package delivery person does not travel from the first non-travel route to different delivery target users in turn, and judge whether the target delivery user corresponding to the original "not on the way delivery" label is no longer in a state of difficulty in moving when the package delivery person delivers the package to the target delivery user. If it is judged that the target delivery user is no longer in a state of difficulty in moving, the user label that meets the judgment condition is changed to "on the way delivery", and the number of delivery target users of packages in the travel route with the delivery label set to "not on the way delivery" and "on the way delivery" is re-counted. The number of labels S1 and n2-S1 are set as the labels of the delivery target users of packages in the travel route, and the second label ratio is calculated. Calculate the label ratios of "not on-route delivery" and "on-route delivery" for different routes respectively, retrieve the stored feasible route data in the route database, locate the feasible route that overlaps with the parcel delivery person's location, obtain the route corresponding to the minimum label ratio among the located feasible routes, and set this route as the first delivery route, where n2 is the total number of target delivery users remaining at the current parcel delivery person's driving location.

10. The big data-based logistics package delivery system according to claim 9, characterized in that: The method for completing the delivery route analysis is specifically as follows: Repeat all the above steps, and mark the non-travel direction routes corresponding to the "not on the way delivery" label as the second non-travel direction route, the third non-travel direction route...the Cth non-travel direction route in turn. After completing the simplification of one non-travel direction route, judge whether the target delivery user corresponding to the remaining "not on the way delivery" label is no longer in a difficult-to-move state when the package delivery person arrives at the location of the target delivery user. After all the target delivery users corresponding to the "not on the way delivery" label are converted to "on the way delivery" labels or marked as the "i-th not on the way delivery target", the delivery analysis process is terminated, where C is the total number of non-travel direction routes obtained after the delivery analysis process is terminated, and i is the number of targets marked as not on the way delivery targets.

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