Personalized Gas Station Recommendation System

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Solution Overview

Problem

Conventional navigation systems do not effectively account for individual user preferences when recommending gas stations, leading to suboptimal choices based solely on proximity.

Innovation Solution

A computer-implemented method and mobile computing device system that determines preferred gas stations by comparing user-specific refueling preferences with information about nearby stations, incorporating factors such as brand, price, and third-party ratings, to provide personalized recommendations.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If gas stations are recommended based solely on proximity to the user, then the system is simple to operate and quick to provide results, but the recommendations do not account for individual user preferences such as brand, price, and ratings

Engineering Contradiction:

Improvesimplicity of gas station recommendationVSAvoidpersonalization to user preferences

Core Design Contradiction:

Ease of operationVSAdaptability or versatility

Solution Approach 1:

The system performs preliminary action by pre-establishing user profiles with refueling preferences and pre-computing gas station information (brand, price, ratings) before the user needs recommendations. When a user requests gas station recommendations, the system already has the necessary data structured and ready for comparison, allowing personalized recommendations to be generated quickly without complex real-time processing.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system introduces an intermediary mechanism in the form of a comparison algorithm that mediates between user preference profiles and gas station information. This intermediary component systematically compares the two datasets and produces personalized recommendations, bridging the gap between simple proximity-based suggestions and complex preference-matched recommendations.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Measurement precision

If the system incorporates multiple factors such as brand preference, price, and third-party ratings into gas station recommendations, then the relevance and accuracy of recommendations improve, but the system complexity increases

Engineering Contradiction:

Improveaccuracy of gas station recommendationVSAvoidcomplexity of recommendation system

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system segments the recommendation process into distinct components: (1) user profile management, (2) gas station information collection, (3) preference factor extraction, and (4) comparison algorithm. By dividing the complex recommendation task into separate modular segments, each handling a specific aspect, the overall system complexity becomes more manageable and easier to implement while maintaining high recommendation accuracy.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system changes parameters by transforming raw gas station data into standardized preference factors (brand preference, price sensitivity, rating thresholds). This parameter transformation allows diverse information to be uniformly compared against user profiles using consistent metrics, simplifying the comparison process while improving recommendation precision.

Inventive Principle:

Principle #35Parameter changes

3Productivity

If the system uses GPS and proximity to determine gas station lists, then the system is easy to implement and provides quick results, but it fails to consider individual user refueling preferences and habits

Engineering Contradiction:

Improvespeed of gas station recommendationVSAvoidcustomization to user refueling behavior

Core Design Contradiction:

ProductivityVSAdaptability or versatility

Solution Approach 1:

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system replaces the purely mechanical proximity-based recommendation approach with a hybrid system that incorporates data-driven preference matching. Instead of relying solely on geometric distance calculations, the system substitutes this with algorithmic comparison of user profiles and gas station attributes, enabling both speed and personalization.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS8738277B1Gas station recommendation systems and methods

Publication Date: 2014.05.27 HONDA MOTOR CO LTD

AI summary

A method for determining a preferred gas station comprises determining gas stations in range of a vehicle, receiving one or more factors associated with refueling preferences for a profile associated with the vehicle, the factor being derived at least in part from data associated with previous refueling of the vehicle, comparing the factor with information associated with the gas stations to determine the preferred gas station. A system comprises a receiver configured to enable communications with a remote server and receive a factor associated with refueling preferences, and a processor configured to determine gas stations in range of a vehicle, and compare the factor with information about the gas stations to determine a preferred gas station.