TY - GEN
T1 - Smart Parking Innovations using Internet of Things, Computer Vision, and Artificial Intelligence - Recent Research Solutions
AU - Murugan, Thangavel
AU - Mohammed, Hikma
AU - Fitigu, Hermela
AU - Yigezu, Sisay
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - The growing challenges of urban parking, driven by increasing urbanization and the rising number of vehicles, create daily issues with parking space availability. Conventional parking systems do not leverage modern technology and automation; instead, they contribute to traffic congestion, fuel wastage, and environmental pollution due to their lack of real-time monitoring and management of parking space availability. Smart parking solutions also enhance space utilization, ensure data security, and improve user experience through real-time data analysis, automated transactions, and privacy protection. IoT-based smart parking systems present a practical solution by facilitating real-time data monitoring. Live data on parking spaces collected using IoT sensors can be processed with various microcontroller technologies. Computer vision-based smart parking systems employ object detection schemes to automatically map parking spaces in a lot, eliminating the need for manual mapping. Using AI techniques, vast amounts of parking data can be analyzed to identify patterns, enabling intelligent allocation and dynamic scheduling of parking spaces based on demand. These technologies can be used to develop mobile applications that allow drivers to view, reserve, and navigate to available parking spots. This paper aims to study recent research solutions on smart parking management systems that harness IoT, computer vision, and AI. The study provides a comprehensive overview of existing research while offering insights into current technological solutions and suggesting future research directions to improve performance, reduce congestion, and enhance user experience.
AB - The growing challenges of urban parking, driven by increasing urbanization and the rising number of vehicles, create daily issues with parking space availability. Conventional parking systems do not leverage modern technology and automation; instead, they contribute to traffic congestion, fuel wastage, and environmental pollution due to their lack of real-time monitoring and management of parking space availability. Smart parking solutions also enhance space utilization, ensure data security, and improve user experience through real-time data analysis, automated transactions, and privacy protection. IoT-based smart parking systems present a practical solution by facilitating real-time data monitoring. Live data on parking spaces collected using IoT sensors can be processed with various microcontroller technologies. Computer vision-based smart parking systems employ object detection schemes to automatically map parking spaces in a lot, eliminating the need for manual mapping. Using AI techniques, vast amounts of parking data can be analyzed to identify patterns, enabling intelligent allocation and dynamic scheduling of parking spaces based on demand. These technologies can be used to develop mobile applications that allow drivers to view, reserve, and navigate to available parking spots. This paper aims to study recent research solutions on smart parking management systems that harness IoT, computer vision, and AI. The study provides a comprehensive overview of existing research while offering insights into current technological solutions and suggesting future research directions to improve performance, reduce congestion, and enhance user experience.
KW - AI
KW - Computer Vision
KW - Internet of Things
KW - Real-time monitoring
KW - Smart Parking
KW - Space management
UR - https://www.scopus.com/pages/publications/105016673852
UR - https://www.scopus.com/pages/publications/105016673852#tab=citedBy
U2 - 10.1109/CCNCPS66785.2025.11135545
DO - 10.1109/CCNCPS66785.2025.11135545
M3 - Conference contribution
AN - SCOPUS:105016673852
T3 - International Conference on Communication, Computing, Networking, and Control in Cyber-Physical Systems, CCNCPS 2025
SP - 55
EP - 62
BT - International Conference on Communication, Computing, Networking, and Control in Cyber-Physical Systems, CCNCPS 2025
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 1st International Conference on Communication, Computing, Networking, and Control in Cyber-Physical Systems, CCNCPS 2025
Y2 - 10 June 2025 through 12 June 2025
ER -