Geo-Aware Transportation Billing Verification System
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Solution Overview
Problem
Existing electronic billing verification systems for transportation services, particularly non-emergency medical transportation, are plagued by issues of arbitrary rejections due to inflexible syntax, excessive permissiveness, and inability to self-update, leading to time-consuming disputes and inefficiencies in fraud prevention and service claim acceptance.
Innovation Solution
A geolocation-aware verification system that establishes a 'field of acceptability' using servers, GIS, and databases to dynamically adjust billing requests based on predetermined rules, allowing drivers to submit reasons and evidence, and updates parameters through user engagement panels to balance strictness and permissiveness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing electronic billing verification systems use inflexible syntax to verify transportation services, then measurement precision is improved, but device complexity increases and loss of time occurs due to arbitrary rejections and manual disputes
Solution Approach 1:
The system dynamically adjusts the field of acceptability parameters based on service type, location, and time. Instead of using fixed, inflexible syntax, the verification criteria adapt to different scenarios, allowing the system to maintain high verification accuracy while reducing arbitrary rejections and manual dispute resolution time.
Solution Approach 2:
The patent changes the parameters of verification by introducing a field of acceptability with adjustable spatial and temporal boundaries. This allows the system to verify transportation services with precision while accommodating legitimate variations in pickup/dropoff locations and times, thereby reducing time-consuming disputes.
2Reliability
If existing systems use strict syntax verification, then reliability is improved, but adaptability deteriorates due to inability to accommodate legitimate deviations
Solution Approach 1:
The field of acceptability is dynamically configured based on service characteristics, allowing the system to maintain reliable verification while adapting to different transportation scenarios and legitimate deviations in location and time.
Solution Approach 2:
Different fields of acceptability are applied to different locations and service types. The system tailors the verification criteria to local conditions, ensuring reliable verification for each specific case while accommodating location-specific legitimate deviations.
3Ease of operation
If existing systems use permissive syntax, then ease of operation is improved, but measurement precision deteriorates due to inability to prevent fraud
Solution Approach 1:
The system uses dynamic fields of acceptability that are permissive enough to ease operation and accommodate legitimate variations, yet precise enough to detect fraudulent deviations through configurable spatial and temporal boundaries.
Solution Approach 2:
The system incorporates feedback mechanisms where verification results and fraud patterns inform ongoing adjustments to the field of acceptability parameters, maintaining ease of operation while improving fraud detection precision over time.
4Manufacturing precision
If existing systems use fixed verification parameters, then manufacturing precision is improved, but adaptability deteriorates due to inability to self-update
Solution Approach 1:
The verification parameters are made dynamic rather than fixed. The field of acceptability can be updated and adjusted based on changing service patterns, location data, and fraud detection needs, maintaining consistency within each verification context while enabling overall adaptability.
Solution Approach 2:
The system incorporates self-update capabilities where verification parameters and field of acceptability boundaries are automatically adjusted based on accumulated data and patterns, reducing the need for manual re-programming while maintaining verification consistency.
Data Source
AI summary
A geo-aware transportation verification system and is disclosed. A processor receives a billing request for payment, including an actual geolocation and an actual time and date. The processor compares a service request to a billing request to determine whether a driver is within a field of acceptability. There are at least three types of fields of acceptability for assisting billing verification, where one may be active at a time. The processor automatically adjusts the billing request to match the service request if the driver is within a field of acceptability for geolocation and time. The processor conditionally rejects a billing request if the driver is not within the field of acceptability and provides a user engagement panel on which the user is allowed to submit billing relevant data for further verification. The field of acceptability is updated dynamically based on collected data.