{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T19:16:55Z","timestamp":1780082215999,"version":"3.54.0"},"reference-count":28,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2023,10,27]],"date-time":"2023-10-27T00:00:00Z","timestamp":1698364800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Deanship of Scientific Research, Islamic University of Madinah, KSA"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Smart cities have emerged as a specialized domain encompassing various technologies, transitioning from civil engineering to technology-driven solutions. The accelerated development of technologies, such as the Internet of Things (IoT), software-defined networks (SDN), 5G, artificial intelligence, cognitive science, and analytics, has played a crucial role in providing solutions for smart cities. Smart cities heavily rely on devices, ad hoc networks, and cloud computing to integrate and streamline various activities towards common goals. However, the complexity arising from multiple cloud service providers offering myriad services necessitates a stable and coherent platform for sustainable operations. The Smart City Operational Platform Ecology (SCOPE) model has been developed to address the growing demands, and incorporates machine learning, cognitive correlates, ecosystem management, and security. SCOPE provides an ecosystem that establishes a balance for achieving sustainability and progress. In the context of smart cities, Internet of Things (IoT) devices play a significant role in enabling automation and data capture. This research paper focuses on a specific module of SCOPE, which deals with data processing and learning mechanisms for object identification in smart cities. Specifically, it presents a car parking system that utilizes smart identification techniques to identify vacant slots. The learning controller in SCOPE employs a two-tier approach, and utilizes two different models, namely Alex Net and YOLO, to ensure procedural stability and improvement.<\/jats:p>","DOI":"10.3390\/s23218753","type":"journal-article","created":{"date-parts":[[2023,10,27]],"date-time":"2023-10-27T11:50:18Z","timestamp":1698407418000},"page":"8753","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":27,"title":["Revolutionizing Urban Mobility: IoT-Enhanced Autonomous Parking Solutions with Transfer Learning for Smart Cities"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1870-0884","authenticated-orcid":false,"given":"Qaiser","family":"Abbas","sequence":"first","affiliation":[{"name":"Faculty of Computer and Information Systems, Islamic University of Madinah, Madinah 42351, Saudi Arabia"},{"name":"Department of Computer Science & IT, University of Sargodha, Sargodha 40100, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7930-6683","authenticated-orcid":false,"given":"Gulzar","family":"Ahmad","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of South Asia, Lahore 54000, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0938-3127","authenticated-orcid":false,"given":"Tahir","family":"Alyas","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Lahore Garrison University, Lahore 54000, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5286-1863","authenticated-orcid":false,"given":"Turki","family":"Alghamdi","sequence":"additional","affiliation":[{"name":"Faculty of Computer and Information Systems, Islamic University of Madinah, Madinah 42351, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5031-3388","authenticated-orcid":false,"given":"Yazed","family":"Alsaawy","sequence":"additional","affiliation":[{"name":"Faculty of Computer and Information Systems, Islamic University of Madinah, Madinah 42351, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ali","family":"Alzahrani","sequence":"additional","affiliation":[{"name":"Faculty of Computer and Information Systems, Islamic University of Madinah, Madinah 42351, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,10,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"15298","DOI":"10.1109\/TITS.2022.3140219","article-title":"On-Ramp Merging Strategies of Connected and Automated Vehicles Considering Communication Delay","volume":"23","author":"Fang","year":"2022","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_2","first-page":"244","article-title":"Getting clever about smart cities: New opportunities require new business models","volume":"193","author":"Belissent","year":"2010","journal-title":"Camb. Mass."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Draz, U., Ali, T., Khan, J.A., Majid, M., and Yasin, S. (2017, January 14\u201316). Areal-time smart dumpsters monitoring and garbage collection system. Proceedings of the 2017 Fifth International Conference on Aerospace Science & Engineering (ICASE), Islamabad, Pakistan.","DOI":"10.1109\/ICASE.2017.8374268"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Yue, W., Li, C., Wang, S., Xue, N., and Wu, J. (2023). Cooperative Incident Management in Mixed Traffic of CAVs and Human-Driven Vehicles. IEEE Trans. Intell. Transp. Syst.","DOI":"10.1109\/TITS.2023.3289983"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.comnet.2018.03.034","article-title":"SVPS: Cloud-based smart vehicle parking system over ubiquitous VANETs","volume":"138","author":"Safi","year":"2018","journal-title":"Comput. Netw."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"735","DOI":"10.1049\/iet-its.2017.0406","article-title":"Smart parking sensors, technologies and applications for open parking lots: A review","volume":"12","author":"Paidi","year":"2018","journal-title":"IET Intell. Transp. Syst."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"7693","DOI":"10.1109\/JIOT.2019.2902887","article-title":"Deep Learning-Based Video System for Accurate and Real-Time Parking Measurement","volume":"6","author":"Cai","year":"2019","journal-title":"IEEE Internet Things J."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1194","DOI":"10.1109\/TCSVT.2018.2826053","article-title":"Parking space status inference upon a deep CNN and multi-task contrastive network with spatial transform","volume":"29","author":"Vu","year":"2018","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"5350","DOI":"10.1109\/TIP.2018.2857407","article-title":"Vision-based parking-slot detection: A DCNN-based approach and a large-scale benchmark dataset","volume":"27","author":"Zhang","year":"2018","journal-title":"IEEE Trans. Image Process."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"19954","DOI":"10.1109\/TITS.2022.3182410","article-title":"A Review of Vision-Based Traffic Semantic Understanding in ITSs","volume":"23","author":"Chen","year":"2022","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_11","first-page":"687","article-title":"Improving parking availability prediction in smart cities with IoT and ensemble-based model","volume":"34","author":"Tekouabou","year":"2020","journal-title":"J. King Saud Univ. Comput. Inf. Sci."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"6585","DOI":"10.1007\/s00521-021-06015-5","article-title":"Transport infrastructure connectivity and conflict resolution: A machine learning analysis","volume":"34","author":"Luo","year":"2022","journal-title":"Neural Comput. Appl."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Orrie, O., Silva, B., and Hancke, G.P. (2015, January 9\u201312). A Wireless Smart Parking System. Proceedings of the 41st Annual Conference of the IEEE Industrial Electronics Society (IECON), Yokohama, Japan.","DOI":"10.1109\/IECON.2015.7392741"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Karthi, M., and Preethi, H. (2016, January 19\u201321). Smart Parking with Reservation in Cloud based environment. Proceedings of the 2016 IEEE International Conference on Cloud Computing in Emerging Markets, Bangalore, India.","DOI":"10.1109\/CCEM.2016.038"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Tabassum, N., Namoun, A., Alyas, T., Tufail, A., Taqi, M., and Kim, K.-H. (2023). Classification of Bugs in Cloud Computing Applications Using Machine Learning Techniques. Appl. Sci., 13.","DOI":"10.3390\/app13052880"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Xu, J., Guo, K., Zhang, X., and Sun, P.Z.H. (2023). Left Gaze Bias between LHT and RHT: A Recommendation Strategy to Mitigate Human Errors in Left- and Right-Hand Driving. IEEE Trans. Intell. Veh.","DOI":"10.1109\/TIV.2023.3298481"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Arora, D., Garg, M., and Gupta, M. (2020, January 18\u201319). Diving deep in Deep Convolutional Neural Network. Proceedings of the 2020 2nd International Conference on Advances in Computing, Communication Control and Networking (ICACCCN), Greater Noida, India.","DOI":"10.1109\/ICACCCN51052.2020.9362907"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"107572","DOI":"10.1016\/j.compeleceng.2021.107572","article-title":"Enhanced air quality prediction by edge-based spatiotemporal data preprocessing","volume":"96 Pt B","author":"Ojagh","year":"2021","journal-title":"Comput. Electr. Eng."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"10067","DOI":"10.1109\/TITS.2023.3269794","article-title":"A Flow Feedback Traffic Prediction Based on Visual Quantified Features","volume":"24","author":"Chen","year":"2023","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"908","DOI":"10.1109\/TIV.2022.3200592","article-title":"Driving Performance Under Violations of Traffic Rules: Novice Vs. Experienced Drivers","volume":"7","author":"Xu","year":"2022","journal-title":"IEEE Trans. Intell. Veh."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Assim, M., and Al-Omary, A. (2020, January 21\u201323). A survey of IoT-based smart parking systems in smart cities. Proceedings of the 3rd Smart Cities Symposium (SCS 2020), Online Conference.","DOI":"10.1049\/icp.2021.0911"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Takehara, R., and Gonsalves, T. (2021, January 23\u201325). Autonomous Car Parking System using Deep Reinforcement Learning. Proceedings of the 2021 2nd International Conference on Innovative and Creative Information Technology (ICITech), Salatiga, Indonesia.","DOI":"10.1109\/ICITech50181.2021.9590169"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Tiwari, R., Pavone, M.F., and Ravindranathan Nair, R. (2023). Proceedings of the International Conference on Computational Intelligence. Algorithms for Intelligent Systems, Springer.","DOI":"10.1007\/978-981-19-2126-1"},{"key":"ref_24","first-page":"1595","article-title":"Autonomous Parking-Lots Detection with Multi-Sensor Data Fusion Using Machine Deep Learning Techniques","volume":"66","author":"Iqbal","year":"2021","journal-title":"CMC-Comput. Mater. Contin."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Chen, Z., Wang, X., Zhang, W., Yao, G., Li, D., and Zeng, L. (2023). Autonomous Parking Space Detection for Electric Vehicles Based on Improved YOLOV5-OBB Algorithm. World Electr. Veh. J., 14.","DOI":"10.3390\/wevj14100276"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"4937","DOI":"10.1016\/j.eswa.2015.02.009","article-title":"PKLot\u2014A robust dataset for parking lot classification","volume":"42","author":"Almeida","year":"2015","journal-title":"Expert Syst. Appl."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"109930","DOI":"10.1016\/j.ymssp.2022.109930","article-title":"Real-time assessment of asphalt pavement moduli and traffic loads using monitoring data from Built-in Sensors: Optimal sensor placement and identification algorithm","volume":"187","author":"Ma","year":"2023","journal-title":"Mech. Syst. Signal Process."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Zhang, X., Fang, S., Shen, Y., Yuan, X., and Lu, Z. (2023). Hierarchical Velocity Optimization for Connected Automated Vehicles With Cellular Vehicle-to-Everything Communication at Continuous Signalized Intersections. IEEE Trans. Intell. Transp. Syst.","DOI":"10.1109\/TITS.2023.3274580"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/21\/8753\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T21:12:37Z","timestamp":1760130757000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/21\/8753"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,27]]},"references-count":28,"journal-issue":{"issue":"21","published-online":{"date-parts":[[2023,11]]}},"alternative-id":["s23218753"],"URL":"https:\/\/doi.org\/10.3390\/s23218753","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,10,27]]}}}