Low Cost Smart Parking with QR-Code
This paper presents a new structure for the autonomous parking system (AAPS) developed to eliminate the inefficiency of urban parking. The proposed system integrates IoT sensors, computer visions and individual deep sea education models (DRL) to optimize the distribution of parking spaces and the exploration of vehicles. AAP uses real -time data built in a slot based on an ultrasonic sensor and a vision based on a vision to dynamically prescribe the parking space and generate it without colliding. In the simulated urban environment, experimental verification showed that parking time decreased by 40% and space efficiency increased by 35% compared to traditional methods. The results emphasize the potential of the system to alleviate congestion in the exercise of sustainable development and sustainable development of smart cities.
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-05-09
- DOI
- https://doi.org/10.5281/zenodo.15375497
- Primary Topic
- Smart Parking Systems Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00