Parking Prediction in Smart Cities: A Survey

Author:

Xiao Xiao1ORCID,Peng Ziyan1,Lin Yunqing1,Jin Zhiling1ORCID,Shao Wei2ORCID,Chen Rui1ORCID,Cheng Nan1ORCID,Mao Guoqiang1ORCID

Affiliation:

1. School of Telecommunications Engineering, Xidian University, Xi’an, China

2. School of Computing Technologies, RMIT University, Melbourne, VIC, Australia

Funder

China Post-Doctoral Science Foundation

Guangzhou Science and Technology Program

Key Project of the Joint Fund of the National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

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1. A review of research on urban parking prediction;Journal of Traffic and Transportation Engineering (English Edition);2024-08

2. Dynamic Spatio-Temporal Adaptive Graph Convolutional Recurrent Networks for Vacant Parking Space Prediction;Applied Sciences;2024-07-07

3. Enhancing IoT Campus Parking Utilization to Cloud on Blynk Application;2024 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS);2024-06-29

4. Prediction of Parking Space Availability Using Improved MAT-LSTM Network;ISPRS International Journal of Geo-Information;2024-05-01

5. A secure and privacy blockchain-based data sharing scheme in mobile edge caching system;Expert Systems with Applications;2024-03

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