Facility Usage Change Detection via Vehicle Parking Patterns
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Solution Overview
Problem
Current technologies cannot automatically detect changes in the usage mode of facilities, such as a business transitioning from a men's clothing store to an internet café, without manual intervention, using Floating Car Data (FCD) and positional information.
Innovation Solution
An information analysis device and method that generates visit pattern information and vehicle information based on positional data from vehicles to detect changes in facility usage modes by analyzing parking patterns and vehicle types, without relying on manual surveys.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If field survey or manual methods are used to detect facility usage mode changes, then detection accuracy is improved, but labor cost and time consumption increase
Solution Approach 1:
The patent replaces manual field survey methods with an automated information processing system that uses vehicle travel data (GPS coordinates, timestamps, parking duration) to detect facility usage mode changes. The system automatically analyzes parking patterns and compares them against database records to identify changes in facility usage, eliminating the need for manual surveys while maintaining detection accuracy.
Solution Approach 2:
The patent introduces vehicle travel data as an intermediary indicator to indirectly detect facility usage mode changes. Instead of directly observing facility changes through field surveys, the system uses parking behavior data from vehicles as a mediator to infer changes in facility usage patterns, enabling automated detection without manual intervention.
2Ease of manufacture
If automated detection methods are used, then labor cost is reduced, but ability to detect usage mode changes deteriorates
Solution Approach 1:
The patent implements a feedback mechanism where the system continuously collects vehicle parking data, compares it with stored facility information, and refines its detection algorithms based on the results. The system learns from accumulated data to improve its ability to distinguish between normal parking variations and actual facility usage mode changes, enhancing detection capability while maintaining automation.
Solution Approach 2:
The patent performs preliminary actions by pre-processing and storing vehicle travel data, parking patterns, and facility information in databases before detection is needed. The system pre-establishes detection rules and thresholds based on historical data, enabling automated real-time detection without requiring manual setup for each detection task, thus maintaining both low labor cost and high detection capability.
3Measurement precision
If comprehensive vehicle data analysis is performed, then detection accuracy is improved, but data processing complexity increases
Solution Approach 1:
The patent segments the data processing task into distinct modules: data collection from multiple vehicles, parking pattern recognition, facility matching, change detection, and result validation. Each module processes specific aspects of the data independently, reducing overall complexity while maintaining comprehensive analysis capability for accurate detection.
Solution Approach 2:
The patent extracts only the essential features from comprehensive vehicle data that are relevant for detecting facility usage mode changes, such as parking duration, parking location, and visit frequency. By filtering out irrelevant data elements and focusing only on key indicators, the system maintains high detection accuracy while reducing data processing complexity.
Data Source
AI summary
A change in usage mode of a facility is detected. An information analysis device (1) includes a visit pattern information creation section (112) which creates visit pattern information related to a facility from vehicle information from a plurality of vehicles and a transition in successive positional information, and creates visit vehicle information related to the facility by cumulating vehicles parked in a parking lot of the facility for every vehicle information; a visit pattern change determination section (113) which determines whether both a change amount after a predetermined time period of the visit pattern information and a change amount after a predetermined time period of the visit vehicle information have changed; and a facility change information creation section (114) which creates facility change information indicating a change in facility information.