Data acquisition and processing method and system based on crowdsourcing

Abstract

The invention relates to the technical field of big data processing, and discloses a crowdsourcing-based data acquisition and processing method and system, and provides a crowdsourcing-based data acquisition and processing method, which is used for distributing user orders to proper transportation units, and comprises the following steps of: firstly, sorting according to the time and distance of the user orders; and then screening is performed according to the working state of the transportation unit. If no idle transport unit exists nearby, the time for each transport unit to complete the order is predicted according to the historical order information and the current route condition, the route is optimized, and finally the transport unit with the optimal route is selected to complete the order. In the whole process, through the steps of data collection, full arrangement, time judgment, insertion processing and the like, efficient order distribution is realized, and the crowdsourcing logistics distribution efficiency and the user experience are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of big data processing, and in particular to a method and system for collecting and processing data based on crowdsourcing. Background Art

[0002] With the rapid development of Internet technology, people's lifestyles have also changed dramatically, and more and more users choose to trade goods and consume services through online platforms. This trend has given rise to the crowdsourcing model, which has gradually been applied to logistics, distribution and other fields.

[0003] The traditional logistics distribution model usually relies on professional logistics companies, and its process is relatively complicated, requiring multiple links such as receiving, loading and unloading, transportation, and delivery. The crowdsourcing model breaks the limitations of the traditional model and assigns logistics distribution tasks to a wider group, such as individual car owners, couriers, etc. This model can effectively improve distribution efficiency, reduce logistics costs, and provide users with more flexible distribution services.

[0004] However, in crowdsourcing logistics, how to assign orders to appropriate transport units remains a challenge. Traditional order allocation methods usually make simple judgments based on factors such as distance and price, while ignoring factors such as the actual working status of the transport unit, historical order information, and user needs.

[0005] In order to solve the problems in the existing crowdsourcing logistics distribution model, it is necessary to develop a more efficient and intelligent order allocation method. This method needs to consider the following aspects: The working status of the transport unit needs to be considered to avoid assigning orders to transport units that are performing other tasks; historical order information needs to refer to the historical order information of the transport unit, such as average transport speed, order processing time, etc., in order to more accurately predict the transport time; user needs need to consider the user's delivery needs, such as the user's desired delivery time, in order to provide users with more personalized services.

[0006] Therefore, the present invention provides a data collection and processing method based on crowdsourcing, aiming to solve the deficiencies in the prior art and improve the efficiency of crowdsourcing logistics distribution and user experience. Summary of the invention

[0007] The present invention provides a method and system for data collection and processing based on crowdsourcing, which are used to promote the solution of the problems mentioned in the above background technology.

[0008] The present invention provides the following technical solution: a method and system for data collection and processing based on crowdsourcing, comprising: S1 sets a time threshold, obtains all orders of the user within the time threshold, and enters the user order set, and sorts the order in descending order according to the distance between the merchant address and the user address corresponding to each order in the user order set; S2 selects the elements in the user order set as the target order in turn according to the descending sorting result, obtains the merchant corresponding to the target order, and divides all the transport units near the merchant according to their working status; Working status includes transportation status and non-transportation status; According to the number of transport units whose working status is non-transportation status, user orders are allocated or transport screening strategies are implemented; If the transport screening strategy is executed, S3 obtains the transport screening strategy result and enters the distance set; S4 collects data on the transport unit corresponding to each element in the distance set, arranges the data collection results, and enters them into the first set; S5 executes the first time judgment strategy for each element in the first set, and records the execution result into the second set; S6 performs insertion processing on each element in the second set; S7 executes the second time judgment strategy for each insertion processing result, and enters the execution result into the qualified set; S8 assigns the target order to the transport unit corresponding to the smallest element in the qualified set.

[0009] Optionally, setting a time threshold, obtaining all orders of the user within the time threshold, and recording the user order set, and sorting the order set in descending order according to the distance between the merchant address corresponding to each order in the user order set and the user address, includes: When a user generates an order, the order is entered into the user order set, and the time when the user generates the order is recorded as the starting time; Select a time after the start time and with a time interval equal to the time threshold as the end time; The time period between the start time and the end time is recorded as the prediction interval; Enter all orders generated by the user within the forecast period into the user order set; Get the merchant address corresponding to each element in the user order set, and sort the elements in the user order set from large to small according to the distance between the merchant address and the user address.

[0010] Optionally, the step of determining to allocate user orders or to execute a transportation screening strategy according to the number of transportation units whose working status is a non-transportation status includes: Select elements in the user order set as target orders in sequence; Draw a circle with the merchant address corresponding to the target order as the dot and r as the radius to form a circular area; Get all transport units in the circular area and determine the working status of the transport units; Enter the transport units in the circular area that are in transport status into the transport collection; Enter the transport units in the circular area that are in a non-transportation state into the free set; If the number of elements in the free set is greater than zero, the target order is assigned to the transport unit in the free set that is the smallest distance from the merchant address corresponding to the target order; If the number of free units is equal to zero, the transport filtering strategy is executed.

[0011] Optionally, the transport screening strategy includes: Obtain all historical order processing times of the merchant corresponding to the target order and enter the time processing set; The order processing time is the time from when the merchant receives the user's order to when the merchant allocates the user's order to the transport unit; Calculate the ratio of the sum of all elements in the time processing set to the number of elements in the time processing set, and record it as the average order processing time; Randomly select an element in the transport set as the target transport unit; Record the merchant address corresponding to the target order as the target address; Get the orders currently being transported by the target transport unit and their corresponding transport routes; According to the distance that the target transport unit has traveled in the transport route and the time it has taken, the average speed of the target transport unit is calculated and recorded as the average transport speed; According to the average transportation speed of the target transportation unit and the average order processing time of the merchant corresponding to the target order, the position of the target transportation unit on the transportation route after the average order processing time is calculated and recorded as the prediction point; Calculate the distance between the predicted point and the target address, record it as the predicted distance, and enter it into the distance set; Reselect the elements in the transport set as new target transport units and execute the transport screening strategy; If all elements in the transport set are traversed, the elements in the distance set are sorted in order from small to large predicted distances, and the transport screening strategy ends.

[0012] Optionally, the data collection for the transport unit corresponding to each element in the distance set, allocating the data collection results, and entering them into the first set includes: Select the transport units corresponding to the elements in the distance set as the judgment units in turn; Obtain all orders that have not been delivered by the judgment unit and enter them into the collection to be completed; According to the average transportation speed of the judgment unit and the corresponding predicted distance of the judgment unit in the distance set, the time taken by the judgment unit from the predicted point to the target address is calculated and recorded as the excess time; Get the user address corresponding to each element in the to-be-completed set and enter it into the address set; All elements in the address set are fully arranged to form multiple sequence combinations, and each sequence combination is entered into the first set as a predicted driving route; Get the user's ideal time corresponding to each element in the to-be-completed set and enter the user's time set; The user's ideal time is the time when each order is expected to be shipped; Execute the first time judgment strategy.

[0013] Optionally, the first time judgment strategy includes: Randomly select an element from the first set as the simulation route; Starting from the target address, drive in the order of the user addresses in the simulated route; If the user address in the simulated route is passed, the current user address is used as the statistical point; According to the average transport speed of the judgment unit and the distance between the starting point and the statistical point, the time when the target transport unit arrives at the statistical point is calculated and recorded as the simulation time; If the simulation time is less than or equal to the difference between the ideal time of the user corresponding to the statistical point in the user time set and the excess time, the current statistical point is used as the new starting point and the vehicle is driven in the order of the user addresses in the simulation route; If the simulation time is greater than the difference between the ideal time of the user corresponding to the statistical point in the user time set and the excess time, then reselect the element in the first set as the new simulation route and execute the first time judgment strategy; If the user addresses in all simulated routes are passed, and the simulated time of each user address is less than or equal to the difference between the corresponding user ideal time and the excess time in the user time set, then the simulated route is entered into the second set, and the first set is reselected as the new simulated route, and the first time judgment strategy is executed; If all elements in the first set are traversed, the first time judgment strategy is stopped.

[0014] Optionally, the insertion process includes: Randomly select any element in the second set as a test route; Get all user addresses in the simulated route and number all user addresses in the test route from 1 to n according to the test route driving order; Select the adjacent elements of the user address in the test route in the order of numbers from 1 to n+1; If the number of adjacent elements is greater than 1, the target address is inserted between the current user address and the adjacent element behind it; If the number of adjacent elements is equal to 1, the target address is inserted after the current user address; The simulated route after inserting the target address is used as the actual route, and the second time judgment strategy is executed.

[0015] Optionally, the second time judgment strategy includes: Starting from the target address, the route is driven in the order of the user addresses in the actual route; If the route passes through a user address in the actual route, the current user address is used as a temporary point; According to the average transport speed of the judgment unit and the distance between the starting point and the temporary point, the time when the target transport unit arrives at the temporary point is calculated and recorded as the actual time; If the actual time is less than or equal to the difference between the user's ideal time corresponding to the temporary point in the user's time set and the excess time, the current temporary point is used as the new starting point, and the route is driven in the order of the user addresses in the actual route; If the actual time is greater than the difference between the user's ideal time corresponding to the temporary point in the user's time set and the excess time, the insertion process is re-executed; If all user addresses in the actual route are traversed, and the actual time of each user address is less than or equal to the difference between the user's ideal time and the excess time at the corresponding temporary point, the time taken to pass the actual route will be entered into the qualified set and the insertion process will be performed; When the number of times the insertion process is executed is equal to n+1, an element in the second set is reselected as a new test route and the insertion process is executed.

[0016] Optionally, allocating the current user order to the transport unit corresponding to the smallest element in the qualified set includes: If all elements in the second set are traversed, a new element in the distance set is selected, the transportation unit corresponding to the element is used as the new judgment unit, and S4 to S7 are executed; If all elements in the distance set are traversed, the route corresponding to the smallest element in the qualified set is selected as the recommended route; Allocate the target order to the transport unit corresponding to the recommended route; Reselect elements in the user order set as new target orders and execute operations S2 to S8.

[0017] Optionally, the system for data collection and processing method based on crowdsourcing is characterized by comprising: The user order collection module sets a time threshold and obtains all orders of users within the time threshold; The order preprocessing module sorts the user orders in descending order according to the distance between the merchant address corresponding to each order and the user address, and publishes the orders to the merchants; The transport unit preliminary screening module performs preliminary screening of all transport units near the merchant based on the movement status of the transport units; The transport screening strategy module predicts the distance of transport units in transport status and sorts them according to the distance prediction results; The route simulation module simulates the routes of the orders accepted by the transport unit in turn; The order insertion module inserts the current user into the adjacent addresses in each route simulation as the actual route; The time judgment module performs time judgment on each address in each route simulation and actual route.

[0018] The present invention has the following beneficial effects: 1. A method and system for data collection and processing based on crowdsourcing obtains the time when the user places an order in real time, sets a prediction interval according to the time when the user places the order and a time threshold, obtains all the user's orders within the prediction interval, and releases the orders in order from far to near according to the distance between the merchant address corresponding to each order of the user and the user address. Through this order release method, the orders farthest from the user can be released first, thereby reducing the waiting time for all the user's orders.

[0019] 2. This method and system of data collection and processing based on crowdsourcing obtains all the transport units near the merchant address, divides all the transport units according to their working status, and monitors the working status of the transport units in real time, and gives priority to allocating orders to idle transport units. This can improve resource utilization, reduce empty driving rate, and reduce logistics costs.

[0020] 3. This method and system for data collection and processing based on crowdsourcing calculates the average order processing time by obtaining the historical order processing time of the merchant to which the target order belongs; randomly selects a transport unit that is performing a task, predicts its route position after the average order processing time based on its average speed and current route, and calculates the distance from the predicted position to the target merchant address. Repeat this process, predict and calculate all transport units that are performing tasks, and finally sort them from small to large according to the predicted distance, and perform subsequent operations in sequence according to the sorting results, which can improve the efficiency and accuracy of subsequent order allocation.

[0021] 4. This method and system for data collection and processing based on crowdsourcing collects the existing route information and excess time of the judgment unit and generates all possible route combinations. Then, simulate driving for each route combination, calculate the time to reach each user address, and compare it with the user's ideal time. If all user addresses can be reached within the ideal time, the route is entered into the second set. Finally, by inserting the elements in the second set respectively, try to insert the target address into the existing route, and make a time judgment again. Finally, the optimal route is selected according to the time taken for each route. By simulating and optimizing the route of the transport unit, the target order is inserted into the optimal position, which can effectively shorten the transportation time and reduce the distribution cost.

[0022] 5. This method and system for data collection and processing based on crowdsourcing can simulate the possibility of all transportation routes by cyclically simulating routes and judging time for all transportation units in transportation status near merchants, thereby enhancing the comprehensiveness of data and improving the accuracy of order allocation.

[0023] 6. This crowdsourcing-based data collection and processing method and system can quickly find the most suitable transport unit to complete the order by screening and sorting user orders and transport units, and making predictions based on historical order information and current route conditions, avoiding inefficient allocation caused by simple distance or price judgments in traditional methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a schematic diagram of the process of the present invention. DETAILED DESCRIPTION

[0025] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0026] Example 1, see Figure 1 , a method for data collection and processing based on crowdsourcing, characterized in that it includes: S1 sets a time threshold, obtains all orders of the user within the time threshold, and enters the user order set, and sorts the order in descending order according to the distance between the merchant address and the user address corresponding to each order in the user order set; The time threshold is a constant, which is used for the length of time for data collection and can be adjusted according to user behavior habits; S2 selects the elements in the user order set as the target order in turn according to the descending sorting result, obtains the merchant corresponding to the target order, and divides all the transport units near the merchant according to their working status; Working status includes transportation status and non-transportation status; According to the number of transport units whose working status is non-transportation status, user orders are allocated or transport screening strategies are implemented; If the transport screening strategy is executed, S3 obtains the transport screening strategy result and enters the distance set; S4 collects data on the transport unit corresponding to each element in the distance set, arranges the data collection results, and enters them into the first set; S5 executes the first time judgment strategy for each element in the first set, and records the execution result into the second set; S6 performs insertion processing on each element in the second set; S7 executes the second time judgment strategy for each insertion processing result, and enters the execution result into the qualified set; S8 assigns the target order to the transport unit corresponding to the smallest element in the qualified set; By screening and sorting user orders and transport units, and making predictions based on historical order information and current route conditions, it is possible to quickly find the most suitable transport unit to complete the order, avoiding inefficient allocation caused by simple distance or price judgments in traditional methods.

[0027] The step of setting a time threshold, obtaining all orders of the user within the time threshold, and recording the order set of the user, and sorting the order set in descending order according to the distance between the merchant address corresponding to each order in the order set and the user address, includes: When a user generates an order, the order is entered into the user order set, and the time when the user generates the order is recorded as the starting time; Select a time after the start time and with a time interval equal to the time threshold as the end time; The time period between the start time and the end time is recorded as the prediction interval; Enter all orders generated by the user within the forecast period into the user order set; Get the merchant address corresponding to each element in the user order set, and sort the elements in the user order set from large to small according to the distance between the merchant address and the user address; By obtaining the time when the user places an order in real time and setting the prediction interval according to the time and time threshold of the user's order, all the user's orders within the prediction interval are obtained, and the orders are released in sequence from far to near according to the distance between the merchant address corresponding to each order of the user and the user address. Through this order release method, the orders farthest from the user can be released first, reducing the waiting time for all the user's orders.

[0028] The method of determining to allocate user orders or to execute a transportation screening strategy according to the number of transportation units whose working status is a non-transportation status includes: Select elements in the user order set as target orders in sequence; Draw a circle with the merchant address corresponding to the target order as the dot and r as the radius to form a circular area; Get all transport units in the circular area and determine the working status of the transport units; Enter the transport units in the circular area that are in transport status into the transport collection; Enter the transport units in the circular area that are in a non-transportation state into the free set; If the number of elements in the free set is greater than zero, the target order is assigned to the transport unit in the free set that is the smallest distance from the merchant address corresponding to the target order; If the number of free units is equal to zero, the transport screening strategy is executed; By obtaining all the transport units near the merchant address, dividing all the transport units according to their working status, and monitoring the working status of the transport units in real time, orders are allocated to idle transport units first. This can improve resource utilization, reduce empty driving rate, and reduce logistics costs.

[0029] The transport screening strategy includes: Obtain all historical order processing times of the merchant corresponding to the target order and enter the time processing set; The order processing time is the time from when the merchant receives the user's order to when the merchant allocates the user's order to the transport unit; Calculate the ratio of the sum of all elements in the time processing set to the number of elements in the time processing set, and record it as the average order processing time; Randomly select an element in the transport set as the target transport unit; Record the merchant address corresponding to the target order as the target address; Get the orders currently being transported by the target transport unit and their corresponding transport routes; According to the distance that the target transport unit has traveled in the transport route and the time it has taken, the average speed of the target transport unit is calculated and recorded as the average transport speed; According to the average transportation speed of the target transportation unit and the average order processing time of the merchant corresponding to the target order, the position of the target transportation unit on the transportation route after the average order processing time is calculated and recorded as the prediction point; Calculate the distance between the predicted point and the target address, record it as the predicted distance, and enter it into the distance set; Reselect the elements in the transport set as new target transport units and execute the transport screening strategy; If all elements in the transport set are traversed, the elements in the distance set are sorted in order from the smallest predicted distance to the largest, and the transport screening strategy ends; By obtaining the historical order processing time of the merchant to which the target order belongs, the average order processing time is calculated; a transport unit that is performing a task is randomly selected, and its route position after the average order processing time is predicted based on its average speed and current route, and the distance from the predicted position to the target merchant address is calculated. Repeat this process, predict and calculate all transport units that are performing tasks, and finally sort them from small to large according to the predicted distance, and perform subsequent operations in sequence according to the sorting results, which can improve the efficiency and accuracy of subsequent order allocation.

[0030] The data collection for the transport unit corresponding to each element in the distance set, the full arrangement of the data collection results, and the entry into the first set include: Select the transport units corresponding to the elements in the distance set as the judgment units in turn; Obtain all orders that have not been delivered by the judgment unit and enter them into the collection to be completed; According to the average transportation speed of the judgment unit and the corresponding predicted distance of the judgment unit in the distance set, the time taken by the judgment unit from the predicted point to the target address is calculated and recorded as the excess time; Get the user address corresponding to each element in the to-be-completed set and enter it into the address set; All elements in the address set are fully arranged to form multiple sequence combinations, and each sequence combination is entered into the first set as a predicted driving route; Get the user's ideal time corresponding to each element in the to-be-completed set and enter the user's time set; The user's ideal time is the time when each order is expected to be shipped; Execute the first time judgment strategy.

[0031] The first time judgment strategy includes: Randomly select an element from the first set as the simulation route; Starting from the target address, drive in the order of the user addresses in the simulated route; If the user address in the simulated route is passed, the current user address is used as the statistical point; According to the average transport speed of the judgment unit and the distance between the starting point and the statistical point, the time when the target transport unit arrives at the statistical point is calculated and recorded as the simulation time; If the simulation time is less than or equal to the difference between the ideal time of the user corresponding to the statistical point in the user time set and the excess time, the current statistical point is used as the new starting point and the vehicle is driven in the order of the user addresses in the simulation route; If the simulation time is greater than the difference between the ideal time of the user corresponding to the statistical point in the user time set and the excess time, then reselect the element in the first set as the new simulation route and execute the first time judgment strategy; If the user addresses in all simulated routes are passed, and the simulated time of each user address is less than or equal to the difference between the corresponding user ideal time and the excess time in the user time set, then the simulated route is entered into the second set, and the first set is reselected as the new simulated route, and the first time judgment strategy is executed; If all elements in the first set are traversed, the first time judgment strategy is stopped.

[0032] The insertion process comprises: Randomly select any element in the second set as a test route; Get all user addresses in the simulated route and number all user addresses in the test route from 1 to n according to the test route driving order; Select the adjacent elements of the user address in the test route in the order of numbers from 1 to n+1; If the number of adjacent elements is greater than 1, the target address is inserted between the current user address and the adjacent element behind it; If the number of adjacent elements is equal to 1, the target address is inserted after the current user address; The simulated route after inserting the target address is used as the actual route, and the second time judgment strategy is executed.

[0033] The second time judgment strategy includes: Starting from the target address, the route is driven in the order of the user addresses in the actual route; If the route passes through a user address in the actual route, the current user address is used as a temporary point; According to the average transport speed of the judgment unit and the distance between the starting point and the temporary point, the time when the target transport unit arrives at the temporary point is calculated and recorded as the actual time; If the actual time is less than or equal to the difference between the user's ideal time corresponding to the temporary point in the user's time set and the excess time, the current temporary point is used as the new starting point, and the route is driven in the order of the user addresses in the actual route; If the actual time is greater than the difference between the user's ideal time corresponding to the temporary point in the user's time set and the excess time, the insertion process is re-executed; If all user addresses in the actual route are traversed, and the actual time of each user address is less than or equal to the difference between the user's ideal time and the excess time at the corresponding temporary point, the time taken to pass the actual route will be entered into the qualified set and the insertion process will be performed; When the number of times the insertion process is executed is equal to n+1, an element in the second set is reselected as a new test route and the insertion process is executed; By collecting the existing route information and excess time of the judgment unit, all possible route combinations are generated. Then, each route combination is simulated, the time to reach each user address is calculated, and compared with the user's ideal time. If all user addresses can be reached within the ideal time, the route is entered into the second set. Finally, by inserting the elements in the second set respectively, try to insert the target address into the existing route, and make a time judgment again. Finally, the optimal route is selected according to the time taken for each route. By simulating and optimizing the route of the transport unit, the target order is inserted into the optimal position, which can effectively shorten the transportation time and reduce the distribution cost.

[0034] The step of allocating the current user order to the transport unit corresponding to the smallest element in the qualified set includes: If all elements in the second set are traversed, a new element in the distance set is selected, the transportation unit corresponding to the element is used as the new judgment unit, and S4 to S7 are executed; If all elements in the distance set are traversed, the route corresponding to the smallest element in the qualified set is selected as the recommended route; Allocate the target order to the transport unit corresponding to the recommended route; Reselect an element in the user order set as a new target order and execute operations S2 to S8; By cyclically simulating the routes and making time judgments for all transport units in all transport states near the merchant, the possibilities of all transport routes can be simulated, thereby enhancing the comprehensiveness of the data and improving the accuracy of order allocation.

[0035] The system of the data collection and processing method based on crowdsourcing is characterized by comprising: The user order collection module sets a time threshold and obtains all orders of users within the time threshold; The order preprocessing module sorts the user orders in descending order according to the distance between the merchant address corresponding to each order and the user address, and publishes the orders to the merchants; The transport unit preliminary screening module performs preliminary screening of all transport units near the merchant based on the movement status of the transport units; The transport screening strategy module predicts the distance of transport units in transport status and sorts them according to the distance prediction results; The route simulation module simulates the routes of the orders accepted by the transport unit in turn; The order insertion module inserts the current user into the adjacent addresses in each route simulation as the actual route; The time judgment module performs time judgment on each address in each route simulation and actual route.

[0036] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0037] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for data collection and processing based on crowdsourcing, characterized in that: include, S1 sets a time threshold, obtains all orders of the user within the time threshold, and enters the user order set, and sorts the order in descending order according to the distance between the merchant address and the user address corresponding to each order in the user order set; S2 selects the elements in the user order set as the target order in turn according to the descending sorting result, obtains the merchant corresponding to the target order, and divides all the transport units near the merchant according to their working status; Working status includes transportation status and non-transportation status; According to the number of transport units whose working status is non-transportation status, user orders are allocated or transport screening strategies are implemented; If the transport screening strategy is executed, S3 obtains the transport screening strategy result and enters the distance set; S4 collects data on the transport unit corresponding to each element in the distance set, arranges the data collection results, and enters them into the first set; S5 executes the first time judgment strategy for each element in the first set, and records the execution result into the second set; S6 performs insertion processing on each element in the second set; S7 executes the second time judgment strategy for each insertion processing result, and enters the execution result into the qualified set; S8 assigns the target order to the transport unit corresponding to the smallest element in the qualified set.

2. The method for data collection and processing based on crowdsourcing according to claim 1, characterized in that: The step of setting a time threshold, obtaining all orders of the user within the time threshold, and recording the order set of the user, and sorting the order set in descending order according to the distance between the merchant address corresponding to each order in the order set and the user address, includes: When a user generates an order, the order is entered into the user order set, and the time when the user generates the order is recorded as the starting time; Select a time after the start time and with a time interval equal to the time threshold as the end time; The time period between the start time and the end time is recorded as the prediction interval; Enter all orders generated by the user within the forecast period into the user order set; Get the merchant address corresponding to each element in the user order set, and sort the elements in the user order set from large to small according to the distance between the merchant address and the user address.

3. The method for data collection and processing based on crowdsourcing according to claim 1, characterized in that: The method of determining to allocate user orders or to execute a transportation screening strategy according to the number of transportation units whose working status is a non-transportation status includes: Select elements in the user order set as target orders in sequence; Draw a circle with the merchant address corresponding to the target order as the dot and r as the radius to form a circular area; Get all transport units in the circular area and determine the working status of the transport units; Enter the transport units in the circular area that are in transport status into the transport collection; Enter the transport units in the circular area that are in a non-transportation state into the free set; If the number of elements in the free set is greater than zero, the target order is assigned to the transport unit in the free set that is the smallest distance from the merchant address corresponding to the target order; If the number of free units is equal to zero, the transport filtering strategy is executed.

4. The method for data collection and processing based on crowdsourcing according to claim 1, characterized in that: The transport screening strategy includes: Obtain all historical order processing times of the merchant corresponding to the target order and enter the time processing set; The order processing time is the time from when the merchant receives the user's order to when the merchant allocates the user's order to the transport unit; Calculate the ratio of the sum of all elements in the time processing set to the number of elements in the time processing set, and record it as the average order processing time; Randomly select an element in the transport set as the target transport unit; Record the merchant address corresponding to the target order as the target address; Get the orders currently being transported by the target transport unit and their corresponding transport routes; According to the distance that the target transport unit has traveled in the transport route and the time it has taken, the average speed of the target transport unit is calculated and recorded as the average transport speed; According to the average transportation speed of the target transportation unit and the average order processing time of the merchant corresponding to the target order, the position of the target transportation unit on the transportation route after the average order processing time is calculated and recorded as the prediction point; Calculate the distance between the predicted point and the target address, record it as the predicted distance, and enter it into the distance set; Reselect the elements in the transport set as new target transport units and execute the transport screening strategy; If all elements in the transport set are traversed, the elements in the distance set are sorted in order from small to large predicted distances, and the transport screening strategy ends.

5. The method for data collection and processing based on crowdsourcing according to claim 1, characterized in that: The data collection for the transport unit corresponding to each element in the distance set, the full arrangement of the data collection results, and the entry into the first set include: Select the transport units corresponding to the elements in the distance set as the judgment units in turn; Obtain all orders that have not been delivered by the judgment unit and enter them into the collection to be completed; According to the average transportation speed of the judgment unit and the corresponding predicted distance of the judgment unit in the distance set, the time taken by the judgment unit from the predicted point to the target address is calculated and recorded as the excess time; Get the user address corresponding to each element in the to-be-completed set and enter it into the address set; All elements in the address set are fully arranged to form multiple sequence combinations, and each sequence combination is entered into the first set as a predicted driving route; Get the user's ideal time corresponding to each element in the to-be-completed set and enter the user's time set; The user's ideal time is the time when each order is expected to be shipped; Execute the first time judgment strategy.

6. The method for data collection and processing based on crowdsourcing according to claim 5, characterized in that: The first time judgment strategy includes: Randomly select an element from the first set as the simulation route; Starting from the target address, drive in the order of the user addresses in the simulated route; If the user address in the simulated route is passed, the current user address is used as the statistical point; According to the average transport speed of the judgment unit and the distance between the starting point and the statistical point, the time when the target transport unit arrives at the statistical point is calculated and recorded as the simulation time; If the simulation time is less than or equal to the difference between the ideal time of the user corresponding to the statistical point in the user time set and the excess time, the current statistical point is used as the new starting point and the vehicle is driven in the order of the user addresses in the simulation route; If the simulation time is greater than the difference between the ideal time of the user corresponding to the statistical point in the user time set and the excess time, then reselect the element in the first set as the new simulation route and execute the first time judgment strategy; If the user addresses in all simulated routes are passed, and the simulated time of each user address is less than or equal to the difference between the corresponding user ideal time and the excess time in the user time set, then the simulated route is entered into the second set, and the first set is reselected as the new simulated route, and the first time judgment strategy is executed; If all elements in the first set are traversed, the first time judgment strategy is stopped.

7. The method for data collection and processing based on crowdsourcing according to claim 1, characterized in that: The insertion process comprises: Randomly select any element in the second set as a test route; Get all user addresses in the simulated route and number all user addresses in the test route from 1 to n according to the test route driving order; Select the adjacent elements of the user address in the test route in the order of numbers from 1 to n+1; If the number of adjacent elements is greater than 1, the target address is inserted between the current user address and the adjacent element behind it; If the number of adjacent elements is equal to 1, the target address is inserted after the current user address; The simulated route after inserting the target address is used as the actual route, and the second time judgment strategy is executed.

8. The method for data collection and processing based on crowdsourcing according to claim 1, characterized in that: The second time judgment strategy includes: Starting from the target address, the route is driven in the order of the user addresses in the actual route; If the route passes through a user address in the actual route, the current user address is used as a temporary point; According to the average transport speed of the judgment unit and the distance between the starting point and the temporary point, the time when the target transport unit arrives at the temporary point is calculated and recorded as the actual time; If the actual time is less than or equal to the difference between the user's ideal time corresponding to the temporary point in the user's time set and the excess time, the current temporary point is used as the new starting point, and the route is driven in the order of the user addresses in the actual route; If the actual time is greater than the difference between the user's ideal time corresponding to the temporary point in the user's time set and the excess time, the insertion process is re-executed; If all user addresses in the actual route are traversed, and the actual time of each user address is less than or equal to the difference between the user's ideal time and the excess time at the corresponding temporary point, the time taken to pass the actual route will be entered into the qualified set and the insertion process will be performed; When the number of times the insertion process is executed is equal to n+1, an element in the second set is reselected as a new test route and the insertion process is executed.

9. The method for data collection and processing based on crowdsourcing according to claim 1, characterized in that: The step of allocating the current user order to the transport unit corresponding to the smallest element in the qualified set includes: If all elements in the second set are traversed, a new element in the distance set is selected, the transportation unit corresponding to the element is used as the new judgment unit, and S4 to S7 are executed; If all elements in the distance set are traversed, the route corresponding to the smallest element in the qualified set is selected as the recommended route; Allocate the target order to the transport unit corresponding to the recommended route; Reselect elements in the user order set as new target orders and execute operations S2 to S8.

10. A system using the crowdsourcing-based data collection and processing method of claim 1, characterized in that: include: The user order collection module sets a time threshold and obtains all orders of users within the time threshold; The order preprocessing module sorts the user orders in descending order according to the distance between the merchant address corresponding to each order and the user address, and publishes the orders to the merchants; The transport unit preliminary screening module performs preliminary screening of all transport units near the merchant based on the movement status of the transport units; The transport screening strategy module predicts the distance of transport units in transport status and sorts them according to the distance prediction results; The route simulation module simulates the routes of the orders accepted by the transport unit in turn; The order insertion module inserts the current user into the adjacent addresses in each route simulation as the actual route; The time judgment module performs time judgment on each address in each route simulation and actual route.

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