Automated Bill Splitting Using NLP for Accurate Group Payments
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Solution Overview
Problem
Existing methods for splitting restaurant bills among a group of people are cumbersome and prone to errors, particularly when individuals intend to pay for items they did not order, disrupting social interactions and wasting time.
Innovation Solution
A system utilizing natural language processing and machine learning to identify users, determine their orders, and apply payment rules based on their conversations, automatically splitting and processing payments without manual input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual bill splitting is used with waiters providing bills to each individual, then payment accuracy is improved, but time consumption and operational complexity increase
Solution Approach 1:
The patent replaces the mechanical manual process of waiters writing down and distributing individual bills with an automated digital system using mobile devices. The system automatically generates, sends, and tracks digital bills for each customer, eliminating manual paperwork and reducing time consumption while maintaining payment accuracy through automated tracking and confirmation mechanisms.
Solution Approach 2:
The system enables self-service by allowing customers to automatically receive their own bills on their mobile devices without waiter intervention. Customers can view, confirm, and pay for their items autonomously, which reduces the time waiters spend on bill distribution and improves overall processing efficiency while maintaining accuracy through automated item-to-bill matching.
2Productivity
If mobile application is used for electronic ordering and payment, then operational efficiency is improved, but complexity of handling group payments increases
Solution Approach 1:
The system automatically segments the group bill into individual customer bills by tracking which items each customer ordered. The mobile application divides the total payment responsibility among customers based on their orders, eliminating the complexity of manual group payment coordination. Each customer receives a separate bill on their device, making payment management simple and straightforward.
Solution Approach 2:
The mobile application serves multiple functions: ordering food, tracking orders in real-time, generating individual bills, and processing payments. This multi-functionality consolidates what would otherwise require multiple separate systems into a single universal platform, reducing operational complexity while maintaining high efficiency for both individual and group payments.
3Measurement precision
If bill splitting is processed at the conclusion of a meal, then payment accuracy is improved, but social interaction and dining experience are disrupted
Solution Approach 1:
The system performs preliminary actions by automatically generating and sending bills to each customer's mobile device during or immediately after ordering, rather than waiting until the meal concludes. This allows customers to review their charges in advance and prepare payment beforehand, ensuring payment accuracy is maintained while eliminating the disruption of bill processing at the end of the meal and improving the overall dining experience.
Data Source
AI summary
Disclosed embodiments may include a system for providing automated bill splitting. The system may receive speech data. The system may identify, from the speech data and using natural language processing, one or more users. The system may determine, from the speech data and using natural language processing, orders of the one or more users. The system may determine, from the speech data and using natural language processing, rules for the orders of the one or more users. The system may process one or more payments for the orders based on the rules and one or more credentials associated with the one or more users.