Smart Park - A Predictive and User Centric Parking Platform
Year: 2025
Type: article
Abstract: Traditional city parking infrastructures cannot adapt to the demands of modern motorists, resulting in congestion, delay, and increased emissions. This project aims to optimize parking space utilization and user experience by employing machine learning algorithms. Based on historical data as well as real-time user-updated information, the system predicts parking availability, optimal parking management without extensive-scale IoT infrastructure. The app utilizes Firebase for a scalable and secure database and authentication mechanism, and Google Maps integration provides real-time navigation assistance for better parking direction. Flutter ensures cross-platform compatibility, making it possible for Android as well as iOS users to have an intuitive and smooth UI/UX. The primary features are advance booking of parking lots, possibility of time extension, and slot availability based on an hour, granting flexibility to users. A secure reservation system prevents double booking, and GPS-based navigation simplifies finding a parking space in an easy and convenient way. By preventing the use of costly hardware installations, this cost-effective, scalable, and eco-friendly solution enables sustainable urban mobility by reducing emissions and improving the parking experience overall.
Authors: Devasenan S., Gana Shree C., Rathakrishnan M., Swathi S.
Language: English
Subfield: Building and Construction
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6930874727
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