Enhanced IoT-Enabled Smart Parking system with RFID Integration and Line Assistance
This study delves into the widespread impact of the Internet of Things (IoT) on urban landscapes, with a primary focus on mitigating the prevalent challenges of traffic congestion and parking scarcity. Introducing innovative Smart Parking Systems (SPS), we harness the power of IoT, notably leveraging Raspberry Pi as a foundational platform. This SPS boasts a suite of advanced features including real-time parking spot detection and erroneous parking identification, complemented by a user-friendly mobile application offering intuitive guidance. The advanced camera infrastructure at entry points, which uses cutting-edge image processing techniques to enable the smooth recognition of permitted cars, is the central component of this system. The empirical results demonstrate how effective the SPS prototype is at easing parking-related problems; quick spot detection greatly reduces driver search times while also easing traffic congestion. Moreover, adding a mobile application improves user experience and increases SPS operational effectiveness. Considering the transformative potential of IoT, the research plays a pivotal role in alleviating congestion and parking challenges in urban environments. Furthermore, this SPS seamlessly integrates with existing payment infrastructure, enabling drivers to conveniently settle parking fees via debit/credit cards or by using the dedicated mobile application. A unique feature of this SPS is its enhanced functionality which guarantees adherence to designated parking spaces. Rigorous checks verify the proper vehicle positioning within allocated spaces, minimizing instances of haphazard parking, and optimizing space utilization within the SPS ecosystem.
Authors
- Irfanullah Khan (ORCID: https://orcid.org/0000-0003-0465-8160)
- AK Khoso
- Noufil Zahid
Institutions
- King Fahd University of Petroleum and Minerals (SA)
- Institute of Business Management (PK)
Publication Details
- Journal
- Transportation research procedia
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1016/j.trpro.2025.03.082
- Citations
- 5
- Primary Topic
- Smart Parking Systems Research
- Type
- article
- Field-Weighted Citation Impact
- 5.03