Departure Time Prediction Using Real-Time Sensor Data
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Solution Overview
Problem
Travelers lack real-time information about wait times at transportation facilities, leading to missed flights and delayed arrivals due to uncertainties in travel and processing times through check-in and security lines.
Innovation Solution
A system comprising sensors, processors, and mobile devices that collect and analyze real-time data on traffic and line conditions to determine optimal departure times for users, allowing them to arrive at their destination on time by selecting the best route and anticipating wait times at transportation facilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If travelers use traditional methods to estimate travel time without real-time data, then the system complexity remains low, but the reliability of arrival time prediction deteriorates leading to missed flights
Solution Approach 1:
The patent combines multiple data sources (traffic data, historical wait times, real-time sensor data from detection equipment) into a unified prediction system. The server merges these diverse inputs to calculate accurate ETAs, resolving the contradiction by integrating information streams rather than relying on simple estimates.
Solution Approach 2:
The system continuously receives real-time feedback from detection equipment monitoring line lengths and wait times at transportation facilities. This feedback loop allows the server to update predictions dynamically, improving reliability while managing complexity through automated data collection and processing.
2Measurement precision
If the system collects and processes real-time data from multiple detection equipment and sources, then the accuracy of departure time determination improves, but the device complexity increases
Solution Approach 1:
The server acts as an intermediary that receives, processes, and synthesizes data from multiple detection equipment and external sources. This centralizes complexity in a dedicated component rather than distributing it across the entire system, improving measurement precision while containing complexity in a manageable location.
Solution Approach 2:
The detection equipment is designed to collect multiple types of data (line length, wait time, traffic conditions) simultaneously. This multi-functionality reduces the need for separate specialized devices, improving measurement accuracy without proportionally increasing system complexity.
3Loss of time
If travelers depart without accurate real-time information, then the ease of operation is high, but the loss of time increases due to missed flights and delays
Solution Approach 1:
The system calculates and provides recommended departure times in advance before the traveler needs to leave. By performing the complex calculation of optimal departure time ahead of time based on real-time and historical data, the system reduces time loss while maintaining ease of operation—the traveler simply follows the pre-calculated recommendation.
Solution Approach 2:
The system automatically collects data, processes information, and generates departure time recommendations without requiring manual input from the traveler. This self-service approach minimizes the effort required from users while preventing time loss through accurate predictions.
Data Source
AI summary
Systems, devices, and methods for transmitting a selected route of travel associated with a user equipment to allow the user of the user equipment to arrive at the destination location on time, where the route is based on a determined departure time for a predetermined arrival time at a selected destination location. Additionally, the determination is based on the current location of the user equipment and real-time data pertaining to the selected destination location, where the real-time data comprises detected changes in surrounding environments at the selected destination location.