A Digital Twin-Enabled Smart Car Park Management System: Architecture and Impact on Emission Reduction

Parking challenges in urban areas and educational institutions have become increasingly common due to rising vehicle numbers and rapid urbanization. The University of Lagos Engineering Car Park exemplifies these issues, experiencing inefficient space utilization, a lack of real-time monitoring, and extended search times for parking spaces. These issues mirror global parking management problems, where inadequate use of parking facilities contributes to traffic congestion and unnecessary fuel consumption. Although existing literature proposes solutions such as computer vision-based systems and sensor-based detection technologies, both approaches have their respective strengths and limitations. This work proposes a digital twin model for the smart management of the University of Lagos Engineering Car Park. The system integrates ultrasonic sensor pairs, an ESP32 microcontroller, and the Blynk IoT platform to create a real-time parking occupancy monitoring system. Ultrasonic sensor pairs are strategically positioned in each parking spot to detect vehicle presence, with data transmitted to the ESP32 microcontroller, which processes the information and sends it to the cloud via the Blynk platform. This cloud-based system provides real-time visualization of parking availability through a user-friendly interface, together with a Firebase and React-based application to display a 2D digital twin of parking spots and effectively monitor occupancy, reducing search times. The system was tested for vehicle detection accuracy, achieving 99.3% accuracy with the ultrasonic sensors. Results demonstrated a high degree of precision in detecting vehicles, with minimal delays in transmitting data from sensors to the cloud. Additionally, the system provided continuous real-time updates on parking availability through the user interface. The digital twin model would effectively reduce parking search times, improve overall campus traffic flow, minimize environmental impacts, and thus aligns with the industry 5.0 paradigm.