Personal Mobility Reservation System with Predictive Allocation
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Solution Overview
Problem
Users face difficulties in finding available personal mobility devices due to incorrect location information and high demand, leading to rental failures and increased hassle in searching for suitable devices.
Innovation Solution
A personal mobility reservation system that predicts rental scenarios based on user schedules and usage history, recommending suitable reservations by integrating user information, device information, and traffic data, and providing push notifications for optimized reservation times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If users search for personal mobility devices manually based on current location, then users can find available devices, but rental failures occur due to location errors and devices being borrowed by others
Solution Approach 1:
The system performs preliminary actions by predicting user rental needs based on schedule data and usage history, proactively recommending reservations before the user actually searches for devices. This advance reservation approach prevents rental failures caused by location errors or devices being borrowed, while eliminating the time users would spend searching manually.
2Productivity
If users search for personal mobility devices in high demand periods, then users can attempt to rent devices, but difficulties arise in occupying available devices
Solution Approach 1:
During high demand periods, the system applies preliminary action by predicting which devices the user will need and reserving them in advance. This ensures reservation success even when demand is high, as the system secures device allocation before other users can borrow them, thereby maintaining both efficiency and reliability.
Solution Approach 2:
The system utilizes feedback from usage history data to continuously improve its predictions. By analyzing past rental patterns and schedule data, the system refines its ability to predict future needs accurately, enhancing reservation success rates during high demand periods through data-driven decision making.
3Ease of operation
If the system provides manual search functionality, then users can locate devices, but the process becomes cumbersome and rental failures increase
Solution Approach 1:
The system applies self-service by automatically predicting user needs and generating reservation recommendations without requiring manual device search. The system autonomously processes schedule data and usage history to provide convenient reservations, eliminating the cumbersome search process while ensuring reliable device allocation through predictive analytics.
Data Source
AI summary
A personal mobility reservation system comprises a user terminal, a personal mobility and a server connected to the user terminal and the personal mobility through a network, wherein the server is configured to obtain user information from the user terminal, to obtain device information from the personal mobility, to generate recommended reservation information based on at least two of the user information, the device information and traffic information, to transmit the recommended reservation information to the user terminal, and to perform a reservation of the personal mobility based on a reservation request signal received from the user terminal regarding the recommended reservation information.