Intelligent water distribution method

Abstract

This invention relates to the field of water station transportation technology, and more particularly to an intelligent water distribution method, comprising: a delivery task acquisition unit for acquiring delivery tasks from a water station management platform, cleaning and parsing delivery addresses, and converting them into user coordinates using GIS geocoding; a delivery level determination unit for determining the delivery level and delivery time limit based on task type, delivery timeliness, task volume, and user service level; a delivery process control unit for accessing real-time road conditions, weather, and traffic control information to dynamically replan delivery routes; and a delivery effect verification unit for verifying delivery timeliness, completion status, and user satisfaction, and optimizing scheduling algorithms and route strategies based on the verification results. The route algorithm of this invention is optimal, significantly reducing delivery mileage, fuel consumption, and labor costs.

Description

Technical Field

[0001] This invention relates to the field of water station transportation technology, and in particular to an intelligent water distribution method. Background Technology

[0002] Currently, the delivery of bottled and packaged water stations generally relies on manual experience for order assignment, which leads to problems such as unreasonable route planning, many duplicate routes, high empty running rate, and high transportation costs; there is a lack of task level mechanism, making it difficult to prioritize emergency water use and scheduled water use; there is no real-time road condition perception and dynamic adjustment capability, resulting in unstable delivery time; and there is no closed-loop verification and optimization mechanism, making it impossible to continuously iterate the scheduling strategy. Summary of the Invention

[0003] The purpose of this invention is to address the above-mentioned shortcomings in the existing technology by proposing an intelligent water distribution method.

[0004] To achieve the above objectives, the present invention adopts the following technical solution: A smart water allocation method includes: a delivery task acquisition unit for acquiring delivery tasks from a water station management platform, cleaning and parsing delivery addresses, and converting them into user coordinates using GIS geocoding; a delivery level determination unit for determining the delivery level and delivery time limit based on task type, delivery timeliness, task volume, and user service level; a delivery route planning unit for generating the optimal delivery route using a multi-objective optimization algorithm based on water station coordinates, user coordinates, delivery level, and vehicle load constraints; a delivery capacity allocation unit for optimally matching tasks with vehicles based on vehicle location, status, and load capacity, generating delivery work orders; a delivery process control unit for dynamically replanning delivery routes by accessing real-time road conditions, weather, and traffic control information; and a delivery effect verification unit for verifying delivery timeliness, completion status, and user satisfaction, and optimizing scheduling algorithms and route strategies based on the verification results.

[0005] Furthermore, the delivery task acquisition unit includes: a task acquisition subunit, which acquires user information, address, water volume, delivery requirements, and appointment time for the task to be delivered via an API interface; an address normalization subunit, which removes garbled characters and special symbols from the address and standardizes the address representation format; an address parsing subunit, which uses a natural language processing algorithm to split the address elements and combines the address database to complete validity verification and error correction; and a coordinate transformation subunit, which calls the map API to convert the structured address into latitude and longitude coordinates, prioritizes matching building and house number, and degrades the matching level if the match fails.

[0006] Furthermore, the delivery level determination unit includes: a type classification subunit, which classifies tasks into emergency water use, expedited reservations, regular delivery, and general delivery; an attribute evaluation subunit, which performs a comprehensive evaluation based on task value, water volume, user level, and timeliness requirements; a weight configuration subunit, which configures weights based on type, timeliness, value, and user level, and calculates the comprehensive delivery level score; and a level labeling subunit, which divides the delivery level into four levels based on preset thresholds and binds them to corresponding delivery time limits.

[0007] Furthermore, the delivery route planning unit includes: a constraint configuration subunit, which sets constraints on maximum vehicle load, maximum delivery distance, single task limit, and latest delivery time; an information mapping subunit, which establishes a mapping table of water station coordinates, user coordinates, delivery level, and task weight and volume; a route generation subunit, which uses an improved genetic algorithm to generate the optimal route sequence that meets the timeliness and load constraints; and a clustering and integration subunit, which merges and clusters tasks in the same area, of the same level, and along the same route to generate the final delivery route.

[0008] Furthermore, the delivery capacity allocation unit includes: a vehicle perception subunit, which acquires the location, status, remaining load, and availability of delivery vehicles; a task matching subunit, which completes task matching based on vehicle proximity, route overlap, and remaining load; a job generation subunit, which generates delivery work orders for vehicles, including delivery sequence, address, coordinates, timeliness, and water quantity; and a scheduling optimization subunit, which generates an optimal scheduling scheme with the goals of shortest total mileage, highest timeliness achievement rate, and lowest transportation cost.

[0009] Furthermore, the delivery process control unit includes: a real-time access subunit to obtain real-time road conditions, congestion, weather, and traffic control information; a traffic assessment subunit to calculate the road segment traffic index and mark congested and impassable road segments; a route redrawing subunit to use AI pathfinding algorithms to avoid obstructed road segments and regenerate the delivery order and route; and an early warning push subunit to push route change and timeliness warning information to drivers and the dispatch center.

[0010] Furthermore, the delivery performance verification unit includes: a receipt confirmation subunit, which obtains electronic signatures, delivery photos, delivery time, and user ratings as delivery vouchers; a timeliness verification subunit, which compares planned and actual delivery times, marks delayed tasks, and statistically analyzes the reasons for delays; an operational analysis subunit, which statistically analyzes timeliness achievement rate, delivery mileage, transportation costs, user satisfaction, and delivery anomaly rate; and a strategy iteration subunit, which adjusts route algorithm weights, level rules, and scheduling strategies based on analysis results to achieve system iteration.

[0011] Furthermore, it also includes an emergency response unit, configured to: monitor vehicle malfunctions, accidents, and congestion timeouts in real time; automatically initiate dispatch for urgent and expedited tasks, assigning the nearest available vehicle to take over delivery; and push abnormal notifications, new delivery information, and estimated delivery times to users.

[0012] Furthermore, it also includes an empty bucket recycling unit, which is configured to: simultaneously plan empty bucket recycling points in the delivery route; insert them into the delivery sequence according to recycling priority and route convenience; record the number of recycled buckets in real time, and generate a recycling list and settlement data.

[0013] The beneficial effects of this invention are: 1. Optimal route algorithm, significantly reducing delivery mileage, fuel consumption, and labor costs; 2. Multi-dimensional hierarchical mechanism, ensuring timely delivery of emergency water and scheduled tasks; 3. Real-time traffic dynamic route redrawing, strong anti-interference ability, and high timeliness stability; 4. Closed-loop verification iteration, continuous system optimization, and continuous improvement in long-term efficiency; 5. It supports integrated delivery and recycling, simplifies operational processes, and improves management efficiency. Attached Figure Description

[0014] Figure 1 This is a schematic diagram of the process of an intelligent water distribution method proposed in this invention; Figure 2 This is a schematic diagram of the empty tank recycling unit in an intelligent water distribution method proposed in this invention; Figure 3 This is a functional diagram of the delivery task acquisition unit of an intelligent water distribution method proposed in this invention. Detailed Implementation

[0015] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0016] In the description of this invention, unless otherwise stated, "a plurality of" means two or more; the terms "upper," "lower," "left," "right," "inner," "outer," "front end," "rear end," "head," "tail," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, the terms "first," "second," "third," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0017] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "connected" and "linked" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0018] In this embodiment, an intelligent water distribution method includes: Example 1: Basic delivery service with a single water station, regular residential orders, no emergencies, and no returned containers. This embodiment represents the most basic operating mode, suitable for small community water stations that only handle daily bottled water delivery to residents, with no urgent orders, no emergency order transfers, and no need for empty bottle collection. System execution steps: The delivery task acquisition unit uses the water station management platform API to batch obtain 23 orders to be delivered that day, extracting user addresses, number of buckets ordered, and appointment time slots. The addresses are then standardized, removing spaces and special characters, and parsed using NLP algorithms into province-city-district-street-community-building-unit-household number. The map API is then used to convert the addresses into latitude and longitude coordinates, achieving building-level accuracy in coordinate matching.

[0019] The delivery level determination unit classifies all orders as regular residential water use. Orders with similar value and water volume are uniformly set as regular delivery level, with a delivery deadline of 18:00 on the same day.

[0020] The delivery route planning unit sets constraints: the maximum load of a single vehicle is 30 barrels, the maximum number of deliveries per trip is 12, and the maximum one-way distance is 5km; a mapping table is established with the water station as the starting point and the user coordinates as the nodes; an improved genetic algorithm is used to iterate for 50 generations to generate the route sequence with the shortest total mileage; orders from the same community and building are clustered and integrated to form 3 independent delivery routes.

[0021] The delivery capacity allocation unit obtains the real-time GPS location, empty status, and availability status of 3 delivery vehicles; based on the principle of proximity and route overlap, it assigns the 3 routes to the 3 vehicles respectively, generating a work order that includes delivery order, address, number of bins, and delivery time.

[0022] The delivery process control unit is connected to the map for real-time traffic conditions. The entire route remains unchanged, with no congestion, no traffic control, and no severe weather. Drivers travel along the planned route.

[0023] The delivery performance verification unit collects electronic signatures, on-site photos, and delivery time for each order upon delivery. After all deliveries are completed, the system compares the timeliness with the planned delivery time; all 23 orders were delivered on time. Total mileage, average mileage per order, and cost are calculated, and the system records the data for the day for subsequent algorithm optimization. This embodiment optimizes basic routes and dispatches orders, significantly reducing manual planning costs and improving delivery efficiency.

[0024] Example 2: Single water station, including emergency water orders, activation of emergency response unit This embodiment applies to medium-sized water stations that handle emergency medical / water shortage orders, activating the emergency response unit and prioritizing high-priority orders. System execution steps: The delivery task acquisition unit collected 36 orders for the day, including 1 hospital emergency water order, 3 scheduled on-time delivery orders, and 32 regular residential orders; it completed address parsing and coordinate conversion, and the coordinates of the emergency water order were accurate to the department floor.

[0025] The delivery level determination unit marks emergency water as emergency, pre-orders as expedited, and regular orders as regular. After weighting, emergency orders are required to be delivered within 2 hours, and expedited orders are required to be delivered within 4 hours.

[0026] The delivery route planning unit locks urgent orders separately and prioritizes direct routes; the remaining orders are clustered and optimized under the weight constraint to generate a route sequence that includes urgent priority.

[0027] The delivery capacity allocation unit assigns the nearest empty vehicle to the water station to handle emergency orders, while the remaining vehicles are assigned to regular and expedited orders.

[0028] The delivery process control unit detects temporary traffic control on the route of the emergency order vehicle; the traffic assessment subunit marks the route as impassable; the route redrawing subunit immediately uses AI to detour, regenerates the shortest route, and sends a warning to the driver and dispatch center.

[0029] The emergency response unit monitors the vehicle status throughout the process. If the vehicle is fault-free, the emergency order will be delivered on time; the system will send a delivery reminder to the user.

[0030] The delivery performance verification unit verifies the timeliness of all orders, ensuring 100% compliance for urgent and expedited orders. It also analyzes the reasons for delays and optimizes route weights. This implementation provides robust guarantees for high-level orders and significantly improves the ability to handle abnormal road conditions.

[0031] Example 3: Single water station, simultaneous delivery and empty barrel recycling, activation of empty barrel recycling unit This embodiment is applicable to well-established water stations that require a large number of empty barrels for recycling, integrating delivery and barrel return into a single process. System execution steps: When the delivery task collection unit obtains an order, it simultaneously reads the number of empty buckets to be recycled noted by the user and binds the return information to the order.

[0032] The delivery level is determined by classifying according to standard rules, and a return-to-bucket marker is added for users who need to return their goods to the bucket.

[0033] After the delivery route planning unit completes route clustering, the empty bin recycling unit inserts the bin return points into the corresponding delivery sequence according to the principles of prioritizing routes that are in the same direction, avoiding detours, and not increasing mileage; new bins are delivered to the same building first, and empty bins are collected later, and the same vehicle can return no more than 15 bins at a time.

[0034] The delivery capacity allocation unit adds fields for the number of returned bins and recycling requirements to the delivery work order, and the driver executes the order accordingly.

[0035] The delivery process control unit maintained road condition monitoring, and there were no major changes to the route.

[0036] The delivery performance verification unit simultaneously verifies the completion status of delivery and bin return, automatically generating a bin return list, empty bin statistics, and settlement reports. This embodiment integrates delivery and collection, reducing the number of separate bin return trips and lowering operating costs.

[0037] Example 4: Multi-water station network scheduling and cross-station order collaborative delivery This embodiment is applicable to a chain of water stations under unified management in urban areas, supporting cross-station dispatching and order assignment based on proximity. System execution steps: The delivery task collection unit uniformly accesses all orders from the four water stations within the region and completes address resolution and coordinate positioning.

[0038] Delivery level is determined by a unified classification system, with emergency orders receiving the highest level across the entire region.

[0039] The delivery capacity allocation unit obtains the real-time location, water station, and remaining load of all 12 delivery vehicles in the entire area; breaking the single water station limitation, it dispatches orders across stations based on the principle of the closest distance between the order coordinates and the vehicle.

[0040] The delivery route planning unit generates the optimal cross-regional route for each vehicle, merging orders that travel in the same direction and along the same route to avoid duplicate routes.

[0041] The delivery process control unit monitors the entire road network in a unified manner, and detours are made to congested road sections.

[0042] The emergency response unit supports cross-station transfer; when a vehicle breaks down at a station, the nearest vehicle in the entire area will be assigned to take over.

[0043] The delivery performance verification unit calculates efficiency by water station and region, and outputs a regional dispatch optimization report. This embodiment achieves regional capacity sharing, reducing overall empty-run rate and improving delivery time.

[0044] Example 5: High-volume, high-density clustered delivery during peak hours (summer / holidays) This embodiment is suitable for scenarios with peak summer water usage and explosive order growth, emphasizing high concurrency and high-density clustering. System execution steps: The delivery task collection unit acquired 86 orders in a single day, with addresses concentrated in 6 large residential communities, showing a high-density distribution.

[0045] The delivery rating assessment unit upgrades the rating of pre-orders and high-volume orders.

[0046] The delivery route planning unit is strongly clustered by community, and orders from the same community are uniformly assigned to the same vehicle; the vehicle is constrained to depart when fully loaded, so as to maximize the utilization rate of the single vehicle's load capacity.

[0047] Delivery capacity allocation units distribute vehicles according to community clusters, reducing cross-regional travel.

[0048] The delivery process control unit plans alternative routes in advance for peak congestion areas.

[0049] The delivery performance verification unit focuses on statistics of load factor and on-time delivery rate, and optimizes clustering threshold and load parameters. This embodiment maintains high efficiency, low cost, and low delay operation even during peak order periods. The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the technical scope disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A smart water distribution method, characterized in that, include: The delivery task acquisition unit is used to obtain the tasks to be delivered from the water station management platform, clean and parse the delivery addresses, and convert them into user coordinates using GIS geocoding; the delivery level determination unit is used to determine the delivery level and delivery time limit based on the task type, delivery timeliness, task volume, and user service level; the delivery route planning unit is used to generate the optimal delivery route based on water station coordinates, user coordinates, delivery level, and vehicle load constraints using a multi-objective optimization algorithm. The delivery capacity allocation unit is used to optimally match tasks with vehicles based on the location, status, and load capacity of delivery vehicles, and generate delivery work orders. The delivery process control unit is used to access real-time road conditions, weather, and traffic control information to dynamically replan delivery routes; the delivery effect verification unit is used to verify delivery timeliness, completion status, and user satisfaction, and optimize scheduling algorithms and route strategies based on the verification results.

2. The intelligent water distribution method according to claim 1, characterized in that, The delivery task acquisition unit includes: The task acquisition sub-unit obtains user information, address, water volume, delivery requirements, and appointment time for the task to be delivered through the API interface; Address standardization sub-unit: Removes garbled addresses and special characters, and standardizes the address representation format; The address resolution subunit uses natural language processing algorithms to split address elements and combines the address database to complete validity verification and error correction. The coordinate transformation subunit calls the map API to convert the structured address into latitude and longitude coordinates, prioritizing matching building and house number, and downgrading the matching level if a match fails.

3. The intelligent water distribution method according to claim 1, characterized in that, The delivery level determination unit includes: The system is divided into sub-units based on task type: emergency water supply, expedited reservation, routine delivery, and general delivery. The attribute evaluation sub-unit conducts a comprehensive evaluation based on task value, water volume, user level, and timeliness requirements. The weight configuration sub-unit configures weights according to type, timeliness, value, and user level, and calculates the comprehensive delivery level score; The grade labeling sub-unit is divided into four levels of delivery grade labels according to preset thresholds, and the corresponding delivery time limits are bound to them.

4. The intelligent water distribution method according to claim 1, characterized in that, The delivery route planning unit includes: a constraint configuration subunit, which sets constraints on maximum vehicle load, maximum delivery distance, single task limit, and latest delivery time; an information mapping subunit, which establishes a mapping table of water station coordinates, user coordinates, delivery level, and task weight and volume; a route generation subunit, which uses an improved genetic algorithm to generate the optimal route sequence that meets the timeliness and load constraints; and a clustering and integration subunit, which merges and clusters tasks in the same area, of the same level, and along the same route to generate the final delivery route.

5. The intelligent water distribution method according to claim 1, characterized in that, The delivery capacity allocation unit includes: a vehicle perception subunit, which acquires the location, status, remaining load, and availability of delivery vehicles; a task matching subunit, which completes task matching based on vehicle proximity, route overlap, and remaining load; a job generation subunit, which generates delivery work orders for vehicles, including delivery sequence, address, coordinates, timeliness, and water quantity; and a scheduling optimization subunit, which generates the optimal scheduling plan with the goals of shortest total mileage, highest timeliness achievement rate, and lowest transportation cost.

6. The intelligent water distribution method according to claim 1, characterized in that, The delivery process control unit includes: a real-time access subunit, which acquires real-time road conditions, congestion, weather, and traffic control information; a traffic assessment subunit, which calculates the road segment traffic index and marks congested and impassable road segments; a route redrawing subunit, which uses AI pathfinding algorithms to avoid obstructed road segments and regenerates the delivery order and route; and an early warning push subunit, which pushes route change and timeliness warning information to drivers and the dispatch center.

7. The intelligent water distribution method according to claim 1, characterized in that, The delivery performance verification unit includes: a receipt confirmation subunit, which obtains electronic signatures, delivery photos, delivery time, and user ratings as delivery vouchers; a timeliness verification subunit, which compares planned and actual delivery times, marks delayed tasks, and statistically analyzes the reasons for delays; an operational analysis subunit, which statistically analyzes timeliness achievement rate, delivery mileage, transportation costs, user satisfaction, and delivery anomaly rate; and a strategy iteration subunit, which adjusts route algorithm weights, level rules, and scheduling strategies based on analysis results to achieve system iteration.

8. The intelligent water distribution method according to claim 1, characterized in that, It also includes an emergency response unit, configured to: monitor vehicle malfunctions, accidents, and congestion timeouts in real time; automatically initiate dispatch for urgent and expedited tasks, assigning the nearest available vehicle to take over delivery; and push abnormal notifications, new delivery information, and estimated delivery time to users.

9. The intelligent water distribution method according to claim 1, characterized in that, It also includes an empty bucket recycling unit, which is configured to: simultaneously plan empty bucket recycling points in the delivery route; insert them into the delivery sequence according to recycling priority and route convenience; record the number of recycled buckets in real time, and generate a recycling list and settlement data.

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