Parking Management System Using CQRS for Granular Allocation
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Solution Overview
Problem
Existing parking management systems lack flexibility and efficiency in managing parking space reservations, leading to suboptimal space allocation and lost revenue, as they do not allow for specific time interval purchases or dynamic pricing adjustments based on actual occupancy.
Innovation Solution
A real-time online parking management system that uses a Command and Query Responsibility Segregation (CQRS) pattern framework to efficiently allocate parking reservations over granular time intervals, allowing customers to purchase parking for specific days and times, and enabling operators to dynamically configure pricing and space allocations based on real-time occupancy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If parking permits are reserved for full days or fixed time periods, then parking facility space allocation is simplified and permit management is easier, but actual facility occupancy cannot be accurately reflected and revenue optimization is prevented
Solution Approach 1:
The patent segments the parking facility into multiple zones and divides time periods into granular intervals (e.g., hourly, daily, weekly). This allows permits to be allocated specifically to zones and time intervals rather than blanket full-day permits, enabling accurate tracking of actual occupancy patterns while simplifying management through structured zone-based control.
Solution Approach 2:
The system dynamically adjusts permit allocations and pricing based on real-time or historical occupancy data. Parking permits can be modified or renewed with updated zone assignments and time interval specifications, allowing the system to adapt to changing occupancy patterns and optimize revenue accordingly.
2Device complexity
If customers are forced to purchase parking for entire time blocks, then permit reservation system is simpler to implement, but customer flexibility is reduced and revenue optimization is lost
Solution Approach 1:
Time blocks are segmented into smaller granular intervals that customers can select based on their specific needs. Rather than forcing purchase of entire day or semester permits, customers can allocate permits to specific zones for specific time intervals (e.g., Monday-Wednesday mornings only), providing flexibility while maintaining system simplicity through standardized interval options.
Solution Approach 2:
Different pricing and allocation rules are applied to different zones and time intervals based on local demand characteristics. High-demand zones during peak hours can be priced differently than low-demand zones during off-peak hours, allowing customers to flexibly allocate permits to match their actual parking needs while the system optimizes revenue from each zone independently.
3Device complexity
If traditional permit allocation methods are used, then implementation is easier and system complexity is lower, but space utilization optimization cannot be achieved and revenue is lost
Solution Approach 1:
The system implements dynamic pricing and allocation that automatically adjusts based on occupancy data. As occupancy patterns emerge from permit usage tracking, the system can modify pricing for different zones and time intervals to optimize utilization, moving from static blanket permits to dynamic, data-driven allocation without requiring complete system redesign.
Solution Approach 2:
The system continuously monitors actual permit usage and occupancy patterns, feeding this information back into allocation and pricing decisions. This feedback loop enables optimization of space utilization by identifying underutilized zones or time periods that could generate additional revenue, while maintaining relatively simple implementation through automated data collection and analysis.
Data Source
AI summary
A parking management system, method, and apparatus are provided with a processor, memory, and separate read and write databases connected to implement a CQRS database access pattern, where the processor executes instructions to communicate with a customer web application to receive a parking space search request which specifies a parking facility selected from a plurality of parking facilities, and a plurality of parking dates and times selected from a plurality of configurable time intervals using a customer-selected recurrence measure; to retrieve a list of parking spaces from the read database which are available at the plurality of parking dates and times; to communicate with the customer web application to display the list of parking spaces; to receive a parking space reservation request which selects a first parking space from the available parking spaces; and to submit a command service request to the write database to update a parking space allocation.