Parking Sensor Cloud System for Occupancy Prediction
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Solution Overview
Problem
In densely populated urban areas, parking systems face challenges such as time-consuming and expensive parking experiences for consumers due to inefficient parking data collection and management, leading to congestion, revenue maximization issues for operators, and ineffective enforcement.
Innovation Solution
A system comprising parking sensors, gateway devices, and a cloud service for collecting and aggregating occupancy and turnover data, using algorithms to predict future occupancy and turnover based on external factors, and providing a dashboard for operators and consumers to make informed decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional manual parking enforcement and data collection methods are used, then operational simplicity is maintained, but productivity and measurement precision deteriorate due to delayed detection and manual processing
Solution Approach 1:
The parking sensor system performs self-service by automatically detecting vehicle occupancy, monitoring payment status, and generating enforcement data without requiring manual intervention. The sensors continuously monitor parking spots and autonomously identify violations, eliminating the need for human officers to physically patrol and check each spot manually.
Solution Approach 2:
The patent replaces manual mechanical enforcement methods with electronic sensing and automated data processing systems. Parking sensors use electromagnetic or optical fields to detect vehicle presence and payment status, substituting human officers and manual inspection processes with automated electronic monitoring and communication networks.
2Loss of information
If no real-time parking data collection system is implemented, then device complexity remains low, but loss of information increases due to lack of occupancy and turnover data
Solution Approach 1:
The system implements feedback by continuously collecting occupancy data from sensors and transmitting it to centralized databases. The data flows back to operators and consumers through interfaces, enabling real-time monitoring of parking availability, turnover rates, and enforcement status. This closed-loop feedback ensures no information is lost between vehicle arrival and enforcement action.
Solution Approach 2:
The parking sensor system performs multiple functions simultaneously: detecting vehicle occupancy, monitoring payment status, tracking turnover events, and generating enforcement data. This multi-functional approach consolidates what would otherwise require separate systems into a single integrated platform, reducing overall system complexity while comprehensive data collection.
3Adaptability or versatility
If parking operators use traditional pricing methods without data analytics, then adaptability is limited, but loss of time increases due to delayed pricing adjustments
Solution Approach 1:
The system performs preliminary action by continuously collecting and analyzing parking data in advance, enabling operators to proactively adjust pricing before demand changes occur. The predictive analytics process historical occupancy and turnover data to forecast future parking demand, allowing pricing adjustments to be made ahead of time rather than reacting to past conditions.
Solution Approach 2:
The pricing system transitions from static to dynamic by automatically adjusting rates based on real-time occupancy data and predictive analytics. The system continuously monitors parking utilization patterns and modifies pricing structures dynamically to optimize revenue, enabling rapid adaptation to changing demand conditions without manual intervention delays.
4Loss of time
If consumers search for parking spots manually without real-time information, then device complexity is low, but loss of time increases due to circling and searching
Solution Approach 1:
The system introduces an intermediary information layer between consumers and parking spots. Real-time occupancy data from sensors is transmitted through communication networks to consumer interfaces (mobile apps, display signs), serving as an intermediary that guides drivers directly to available spots without requiring physical searching or circling.
Data Source
AI summary
A system of parking data aggregation and distribution may comprise a plurality of parking sensors, at least one of the plurality of parking sensors located proximate a parking area and one or more gateway devices. The system may further comprise an administrator interface, a parking operator dashboard interface, and a cloud service component. The cloud service component receives parking sensor data indicating occupancy and turnover from the gateway devices and transmits the parking sensor data to the parking operator dashboard web interface. The cloud service component may comprise a database for storing the parking sensor data and a software application for implementing an algorithm to create one or more predictions for future occupancy and future turnover during a future time period. The parking operator dashboard interface may display one or more representations of the parking sensor data over the past time period and predictions for future occupancy and future turnover.