METHOD AND SYSTEM FOR AI-BASED PARKING MANAGEMENT

Abstract

A system for an automated processing of parking data based on user-related data including a processor of a parking processing server node configured to host a machine learning (ML) module and connected to at least one user-entity node over a network and a memory on which are stored machine-readable instructions that when executed by the processor, cause the processor to receive a parking request comprising user profile data from the at least one user-entity node, derive the user profile data from the parking request, acquire sensory data from a vicinity of at least one vacant parking spot, parse the sensory data based on the user profile data to derive a plurality of key classifying features, query a local parking database to retrieve local historical parking spot allocation'-related data based on the plurality of key classifying features, generate at least one classifier feature vector based on the plurality of key classifying features and the historical parking spot allocation'-related data, provide the at least one classifier feature vector to the ML module configured to generate a predictive model for producing at least one parking recommendation parameter and generate a parking allocation verdict based on the at least one parking recommendation parameter and provide a verdict-related notification to the at least one user-entity node.

CPC Classifications