Machine Learning Parking Space Detection for Real-Time Availability
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Locating public parking spaces is time-consuming, difficult, and inefficient, especially in urban environments, leading to wasted time, fuel, and increased pollution.
Innovation Solution
A vehicle platform utilizing a machine learning model processes geographical and vehicle data to identify public parking spaces, providing real-time notifications to drivers, thereby reducing the time required to find available spaces and conserving resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If drivers manually search for public parking spaces by driving around and visually searching, then they can locate parking spaces, but the process is time-consuming and inefficient
Solution Approach 1:
The system performs preliminary actions by continuously collecting vehicle location data and automatically identifying public parking spaces before drivers need them. The machine learning model pre-processes geographical data and vehicle data to create a database of public parking spaces, so when drivers search, the information is already prepared and immediately available, eliminating the time-consuming manual search process.
Solution Approach 2:
The patent replaces the mechanical manual searching process with an automated electronic system. Instead of drivers physically driving around and visually searching for parking spaces, the system uses machine learning models, geographic data processing, and automated notification systems to identify and communicate parking space locations to drivers, substituting mechanical effort with computational intelligence.
2Productivity
If drivers continuously drive around searching for parking spaces, then they can find available spaces, but this causes unnecessary traffic and pollution
Solution Approach 1:
The system implements feedback by continuously monitoring vehicle data, determining when vehicles are parked in public spaces, and using this information to update and refine the public parking space database. This feedback loop allows the machine learning model to improve its identification accuracy over time and provide more accurate real-time notifications, reducing unnecessary driving as drivers receive reliable information before arriving at locations.
Solution Approach 2:
The system enables self-service by automatically collecting data from vehicles, processing it through machine learning models, and generating notifications without requiring driver intervention. The system autonomously identifies public parking spaces, determines their availability, and communicates this information to drivers, eliminating the need for drivers to manually search and reducing traffic caused by searching behavior.
3Measurement precision
If the system processes large amounts of geographical and vehicle data to identify public parking spaces, then accuracy improves, but system complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the complex data processing task into distinct modules: a machine learning model that processes geographical data to identify public parking spaces, a separate component that collects and processes vehicle data, and another module that determines parking space availability. This segmentation allows each component to specialize in specific data processing tasks, improving accuracy while managing system complexity through modular architecture.
Data Source
AI summary
A device may receive geographical data identifying a geographical area, and may receive, from vehicle devices of vehicles, first vehicle data identifying engine off conditions, locations during engine off conditions, and durations of the engine off conditions. The device may divide, based on the geographical data, the geographical area into clusters with particular dimensions, and may process data identifying the clusters and the first vehicle data, with a machine learning model, to determine parking data identifying public parking spaces in the geographical area. The device may receive, from a set of the vehicle devices associated with vehicles parked in the public parking spaces, vehicle data identifying engine on conditions and locations during the engine on conditions, and may identify available public parking spaces based on the second vehicle data and the parking data. The device may perform one or more actions based on data identifying the available public parking spaces.