Proximity-Based Delivery Routing with Predictive User Notifications

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Solution Overview

Problem

Traditional delivery service platforms require users to place an order and wait for a delivery vehicle to pick up goods, which is inefficient due to the lack of advance knowledge of user demands.

Innovation Solution

A proximity-based delivery service system that generates notifications and routes based on user engagement history and current traffic, allowing delivery vehicles to deliver pre-stored goods when within a predetermined distance of users, optimizing delivery efficiency by targeting high-demand areas.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If traditional delivery service platforms wait for users to place orders before dispatching vehicles, then delivery services can be provided on-demand, but delivery time and operational efficiency deteriorate due to lack of advance preparation

Engineering Contradiction:

Improvedelivery efficiencyVSAvoiddelivery time

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The system performs preliminary actions by analyzing user engagement history and predicting future delivery requests before users actually place orders. Delivery vehicles are pre-dispatched to high-probability locations with pre-stored goods, eliminating the waiting period between order placement and vehicle dispatch. This predictive approach transforms reactive on-demand delivery into proactive pre-positioned delivery.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The service area is segmented into multiple zones based on user engagement history and delivery probability. Instead of treating all areas uniformly, the system identifies and prioritizes high-engagement zones for pre-positioning goods, allowing differentiated delivery strategies across different geographic segments to optimize overall efficiency.

Inventive Principle:

Principle #1Segmentation

2Productivity

If delivery vehicles serve all areas uniformly, then comprehensive coverage is achieved, but delivery efficiency deteriorates due to unnecessary trips to low-demand areas

Engineering Contradiction:

Improvedelivery efficiencyVSAvoidservice coverage area

Core Design Contradiction:

ProductivityVSArea of stationary object

Solution Approach 1:

The system applies local quality by tailoring delivery strategies to specific geographic zones based on their characteristics. High-engagement areas receive pre-positioned goods and priority service, while low-engagement areas are served on-demand. This localized differentiation optimizes delivery efficiency in high-priority zones without completely abandoning comprehensive coverage.

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The system performs partial action by focusing pre-positioning efforts only on high-probability delivery zones rather than uniformly across all service areas. Delivery vehicles are strategically deployed to specific high-engagement neighborhoods, performing excessive action (pre-positioning) only where needed, thereby improving efficiency without sacrificing overall service coverage.

Inventive Principle:

Principle #16Partial or excessive action

3Productivity

If users must place orders in advance, then delivery planning can be optimized, but user convenience deteriorates due to required advance commitment

Engineering Contradiction:

Improvedelivery planning efficiencyVSAvoiduser convenience

Core Design Contradiction:

ProductivityVSEase of operation

Solution Approach 1:

The system enables self-service by allowing users to receive deliveries without actively placing orders. Through predictive analytics based on engagement history, the system automatically identifies when and where users are likely to need deliveries, and pre-positiones goods accordingly. Users simply receive notifications when vehicles are nearby, eliminating the need for advance ordering while maintaining optimized delivery planning.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system uses feedback from user engagement history and real-time vehicle location data to continuously refine delivery predictions. User responses to proximity notifications provide additional feedback that helps the system learn and improve its predictive accuracy over time, balancing automated planning with user convenience.

Inventive Principle:

Principle #23Feedback

4Adaptability or versatility

If delivery vehicles travel long distances to pick up orders, then service flexibility is maintained, but energy consumption and time loss increase

Engineering Contradiction:

Improveservice flexibilityVSAvoidvehicle energy consumption

Core Design Contradiction:

Adaptability or versatilityVSUse of energy by moving object

Solution Approach 1:

The system performs preliminary action by pre-positioning goods in delivery vehicles before users place orders. Vehicles are dispatched in advance to high-probability locations with pre-stored inventory, eliminating the need for long return trips to fulfillment centers or vendor locations. This transforms the traditional pick-up-delivery model into a pre-positioned local delivery model, dramatically reducing vehicle travel distances and energy consumption while maintaining service flexibility.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS12406222B1System and method for providing proximity-based delivery service

Publication Date: 2025.09.02 KOSOSKI TRAVIS

AI summary

A method of providing proximity-based delivery service comprises generating, by one or more processors, a neighborhood boundary; generating, by the one or more processors, a delivery service route within the neighborhood boundary; and generating, by the one or more processors, a notification on a user terminal located within the neighborhood boundary when a geolocation of a delivery service vehicle is within a predetermined distance from a geolocation of the user terminal.