Intelligent Seating Plan Recognition System
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Solution Overview
Problem
Manually creating and updating seating plans for seating reservation systems is tedious and time-consuming, requiring significant effort from venue employees.
Innovation Solution
An intelligent system trained to recognize repetitive visual features in seating floor plans, capable of detecting individual seats and assigning metadata automatically, reducing the need for manual input and streamlining the process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual methods are used to create and update seating plans, then accuracy and control over seat metadata are maintained, but the process is tedious and time-consuming
Solution Approach 1:
The patent replaces manual mechanical processes of seat detection and metadata assignment with an automated intelligent system using image processing and machine learning algorithms. The system automatically analyzes seating floor plan images, detects seat locations, and assigns metadata without human intervention, thereby resolving the contradiction between productivity improvement and system complexity.
Solution Approach 2:
The intelligent system performs self-service by automatically detecting seats and assigning metadata to itself without requiring manual input. The system processes seating floor plan images independently, generating seat location data and metadata assignments autonomously, which eliminates the tedious manual work while maintaining accuracy.
2Loss of time
If manual seat detection and metadata assignment is performed, then control over data accuracy is maintained, but significant time and effort are required from venue employees
Solution Approach 1:
The system incorporates feedback mechanisms where the intelligent system processes seating floor plan images, detects seat locations and types, and assigns metadata. The process can be validated and adjusted based on feedback, ensuring both speed and precision in seat identification while reducing manual time investment.
Solution Approach 2:
The system creates a digital copy of the seating floor plan image and processes this copy to extract seat location and type information. By working with an image copy rather than manually inspecting each seat, the system achieves both rapid processing and accurate detection of seat characteristics.
Data Source
AI summary
A seating reservation system running on a network server has functionality that can be trained to detect information relating to individual seats, their locations, and different seating types in a new or modified seating plan loaded into the system. This detected seating information can be maintained in seating plan files that can be edited to include metadata. Upon request, by a client application running under control a user, portions or all of the information in a seating plan file can be transferred as a web page to the client application for display and interaction with by the client application user for the purpose of completing a seat reservation process.