On-Demand Delivery Coordination System
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Solution Overview
Problem
Existing delivery systems for construction materials and other items are inefficient, leading to delays and resource wastage due to manual processes, subjective selection of retailers, and inadequate coordination for on-demand delivery, especially for multi-party transactions and complex logistics.
Innovation Solution
A device-based system that coordinates payment and delivery processes through a server communicating with contractors, homeowners, retailers, pullers, and drivers, using objective criteria to optimize the selection of fulfillment centers, pullers, and drivers, and facilitating multi-party approvals and payments via mobile devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual processes are used for item delivery coordination, then device complexity is reduced, but productivity and delivery speed deteriorate
Solution Approach 1:
The patent introduces a server as an intermediary component that automatically coordinates between multiple devices (contractor's device, retailer's device, driver's device, puller's device). The server receives order information, processes it according to stored criteria, and automatically assigns tasks to appropriate resources, eliminating manual coordination while managing system complexity through centralized automation.
Solution Approach 2:
The system enables self-service through automated decision-making where the server independently selects fulfillment centers, pullers, and drivers based on pre-stored objective criteria. The system automatically coordinates deliveries without requiring manual intervention from contractors or retailers, allowing the system to serve itself through algorithmic processing.
2Measurement precision
If subjective selection of retailers is used, then device complexity is reduced, but measurement precision and objectivity deteriorate
Solution Approach 1:
The patent transforms subjective selection into objective parameter-based selection by storing specific criteria (geographic location, item availability, price) in the server. The system automatically compares retailers against these predefined parameters and selects the optimal fulfillment center, replacing human judgment with quantifiable, objective measurements that can be precisely controlled and reproduced.
Solution Approach 2:
The system incorporates feedback mechanisms where the server receives order information, processes it against stored criteria, and automatically adjusts selections based on real-time data from retailers and fulfillment centers. This feedback loop ensures that selection accuracy is continuously optimized based on actual system conditions rather than relying on initial subjective assumptions.
3Productivity
If retailer resources are used for delivery, then device complexity is reduced, but productivity and delivery timing deteriorate
Solution Approach 1:
The patent segments the delivery process into distinct functional components: order placement by contractors, item collection by pullers, transportation by drivers, and fulfillment by retailers. Each component is handled by a dedicated device or resource type, allowing specialized optimization of each function while the server coordinates them sequentially, improving overall delivery efficiency through functional segmentation.
Solution Approach 2:
The system performs preliminary actions by pre-storing objective selection criteria in the server before deliveries occur. The server is configured with stored criteria that guide automatic selections of fulfillment centers, pullers, and drivers in advance, enabling rapid decision-making during actual deliveries without requiring complex real-time calculations or coordination.
4Productivity
If automated selection of fulfillment centers is implemented, then productivity improves, but device complexity increases
Solution Approach 1:
The server acts as an intermediary that manages the complexity of automated selection by receiving order information from contractors, processing it against stored criteria, and automatically assigning fulfillment centers, pullers, and drivers. This centralized intermediary approach consolidates automation complexity into a single coordinating system rather than distributing it across multiple independent systems.
Solution Approach 2:
The system uses copied or replicated data structures where the server stores copies of retailer information, fulfillment center locations, and selection criteria in its memory. These stored copies enable rapid automated comparisons and selections without requiring the system to re-query or re-process original data sources, improving processing speed while managing complexity through data replication.
Data Source
AI summary
Systems and techniques are disclosed that provide device-based coordination of multi-party delivery processes. One example implementation involves receiving a payer-invite request from a requester device. The payer-invite request requests an invitation be sent to a payer to pay for a delivery order. The delivery order specifying one or more items to be purchased and delivered to a requester location associated with the requester device or inputted by the requester. The system sends the invitation to a payer device associated with the payer and receives a payment from the payer device. The system fulfills the delivery order by identifying a fulfillment center, a driver, and/or a puller and sending communications with order information and instructions to the devices of those parties to coordinate the delivery. For example, the system sends a driving instruction to a driver device instructing the driver to pick up and deliver the items.