Decentralized Parking AI Networks for Space Identification
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Solution Overview
Problem
Finding a parking space within a parking lot is complicated and aggravating for both vehicles and parking lot operators, as existing systems lack efficient methods to identify available spaces and notify vehicle operators.
Innovation Solution
A decentralized parking fulfillment system that utilizes sensor technologies and V2X communications to identify available parking spaces and notify vehicle operators, employing artificial intelligence networks in connected computing devices and vehicles to determine optimal parking spaces based on personalized parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a decentralized parking fulfillment system with AI networks is implemented, then parking space identification efficiency is improved, but system complexity increases
Solution Approach 1:
The system divides the parking fulfillment functionality into separate AI networks deployed in different locations: parking lot agents in parking lots and vehicle agents in vehicles. Each agent independently performs local processing and decision-making, eliminating the need for a complex centralized system while improving identification efficiency through distributed intelligence.
2Measurement precision
If sensor technologies and V2X communications are used to identify parking spaces, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system employs sensor technologies and V2X communications that automatically detect and communicate parking space availability without requiring complex manual intervention. The sensors and communication systems self-organize into a coordinated network, providing precise detection while keeping operational complexity manageable through automated processes.
3Adaptability or versatility
If AI networks execute on both connected computing devices and vehicles, then adaptability is improved, but loss of time increases
Solution Approach 1:
The system pre-loads and executes AI networks on both connected computing devices and vehicles in advance, enabling them to independently process personalized parameters and make parking decisions without requiring real-time centralized computation. This preliminary deployment of intelligence reduces computation time while maintaining high adaptability to individual user preferences.
Data Source
AI summary
In some implementations, a method for providing a decentralized parking fulfillment service may include executing, by a first processor of a connected computing device, a first artificial intelligence network. In addition, the decentralized parking fulfillment service may include executing, by a second processor of a connected vehicle, a second artificial intelligence network. The decentralized parking fulfillment service may include providing the decentralized parking fulfillment service including solving, by the first artificial intelligence network and the second artificial intelligence network, a function that determines a parking space for the connected vehicle. In some implementations, a decentralized parking fulfillment system for providing the decentralized parking fulfillment system includes a parking lot agent stored in a first non-transitory memory of the connected computing device and a vehicle parking agent stored in a second non-transitory memory of the connected vehicle.