Smart Park - A Predictive and User Centric Parking Platform

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.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-03-11
DOI
https://doi.org/10.5281/zenodo.14979635
Primary Topic
Regulation of Appetite and Obesity
Type
article
Field-Weighted Citation Impact
0.00
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article

Smart Park - A Predictive and User Centric Parking Platform

Zenodo (CERN European Organization for Nuclear Research)
Regulation of Appetite and Obesity
article

Smart Park - A Predictive and User Centric Parking Platform

article en

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.

Zenodo (CERN European Organization for Nuclear Research)
Sustainable cities and communities
Openalex Percentile: Top 51%
Regulation of Appetite and Obesity
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Smart Park - A Predictive and User Centric Parking Platform · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS