# Parking Analytics Framework using Deep Learning

arXiv: https://arxiv.org/abs/2203.07792 · HTML: https://mlsanity.com/paper/2203.07792/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 24 references that are in the map.
- First posted on arXiv 15 Mar 2022.

## Builds on (most cited first, 5 of 5)

- [YOLOv3: An Incremental Improvement](https://mlsanity.com/paper/1804.02767/) (2018)
- [Simple Online and Realtime Tracking with a Deep Association Metric](https://mlsanity.com/paper/1703.07402/) (2017)
- [A Smart, Efficient, and Reliable Parking Surveillance System with Edge Artificial Intelligence on IoT Devices](https://mlsanity.com/paper/2001.00269/) (2020)
- [Deep Learning Based Video System for Accurate and Real-Time Parking Measurement](https://mlsanity.com/paper/1902.07401/) (2019)
- [A Deep Learning-based Approach for Real-time Facemask Detection](https://mlsanity.com/paper/2110.08732/) (2021)

## Built on by (most cited first, 1 of 1)

- [TAU: A Framework for Video-Based Traffic Analytics Leveraging Artificial Intelligence and Unmanned Aerial Systems](https://mlsanity.com/paper/2303.00337/) (2023)

## Abstract (arXiv)

With the number of vehicles continuously increasing, parking monitoring and analysis are becoming a substantial feature of modern cities. In this study, we present a methodology to monitor car parking areas and to analyze their occupancy in real-time. The solution is based on a combination between image analysis and deep learning techniques. It incorporates four building blocks put inside a pipeline: vehicle detection, vehicle tracking, manual annotation of parking slots, and occupancy estimation using the Ray Tracing algorithm. The aim of this methodology is to optimize the use of parking areas and to reduce the time wasted by daily drivers to find the right parking slot for their cars. Also, it helps to better manage the space of the parking areas and to discover misuse cases. A demonstration of the provided solution is shown in the following video link: https://www.youtube.com/watch?v=KbAt8zT14Tc.