PARKTag: An AI-Blockchain Integrated Solution for an Efficient, Trusted, and Scalable Parking Management System

被引:0
作者
Kalbhor, Atharva [1 ]
Nair, Rashmi S. [1 ]
Phansalkar, Shraddha [1 ]
Sonkamble, Rahul [2 ]
Sharma, Abhishek [3 ]
Mohan, Harshit [4 ]
Wong, Chin Hong [5 ,6 ]
Lim, Wei Hong [7 ]
机构
[1] MIT Art Design & Technol, Dept Comp Sci & Engn, Pune 412201, Maharashtra, India
[2] Pimpri Chinchwad Univ, Dept Comp Sci & Engn, Pune 411044, Maharashtra, India
[3] Graph Era Deemed Univ, Dept Comp Sci & Engn, Dehra Dun 248002, India
[4] Univ Petr & Energy Studies, Sch Engn, Dept Elect & Elect Engn, Dehra Dun 248002, India
[5] Fuzhou Univ, Maynooth Int Engn Coll, Fuzhou 350116, Peoples R China
[6] Maynooth Univ, Maynooth Int Engn Coll, Maynooth W23 A3HY, Ireland
[7] UCSI Univ, Fac Engn Technol & Built Environm, Kuala Lumpur 56000, Malaysia
关键词
smart parking; deep learning; blockchain; smart contract; FRAMEWORK; PREDICTION;
D O I
10.3390/technologies12090155
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The imbalance between parking availability and demand has led to a rise in traffic challenges in many cities. The adoption of technologies like the Internet of Things and deep learning algorithms has been extensively explored to build automated smart parking systems in urban environments. Non-human-mediated, scalable smart parking systems that are built on decentralized blockchain systems will further enhance transparency and trust in this domain. The presented work, PARKTag, is an integration of a blockchain-based system and computer vision models to detect on-field free parking slots, efficiently navigate vehicles to those slots, and automate the computation of parking fees. This innovative approach aims to enhance the efficiency, scalability, and convenience of parking management by leveraging and integrating advanced technologies for real-time slot detection, navigation, and secure, transparent fee calculation with blockchain smart contracts. PARKTag was evaluated through implementation and emulation in selected areas of the MIT Art Design Technology University campus, with a customized built-in dataset of over 2000 images collected on-field in different conditions. The fine-tuned parking slot detection model leverages pre-trained algorithms and achieves significant performance metrics with a validation accuracy of 92.9% in free slot detection. With the Solidity smart contract deployed on the Ethereum test network, PARKTag achieved a significant throughput of 10 user requests per second in peak traffic hours. PARKTag is implemented as a mobile application and deployed in the mobile application store. Its beta version has undergone user validation for feedback and acceptance, marking a significant step toward the development of the final product.
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页数:33
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