{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,23]],"date-time":"2026-03-23T12:42:45Z","timestamp":1774269765466,"version":"3.50.1"},"reference-count":45,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2023,10,19]],"date-time":"2023-10-19T00:00:00Z","timestamp":1697673600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Due to the rapid increase in private car ownership in China, most cities face the problem of insufficient parking spaces, leading to frequent occurrences of parking space conflicts. There is a wide variety of parking locks available on the market. However, most of them lack advanced intelligence and cannot cater to the growing diverse needs of people. The present study attempts to devise a smart parking lock to tackle this issue. Specifically, the smart parking lock uses a Raspberry Pi as the core controller, senses the vehicle with an ultrasonic ranging module, and collects the license plate image with a camera. In addition, algorithms for license plate recognition based on traditional image-processing methods typically require a high pixel resolution, but their recognition accuracy is often low. Therefore, we propose a new algorithm called UNET-GWO-SVM to achieve higher accuracy in embedded systems. Moreover, we developed a WeChat mini program to control the smart parking lock. Field tests were conducted on campus to evaluate the performance of the parking locks. The test results show that the corresponding effective unlocking rate is 99.0% when the recognition error is less than two license plate characters. The average time consumption is controlled at about 2 s. It can meet real-time requirements.<\/jats:p>","DOI":"10.3390\/s23208572","type":"journal-article","created":{"date-parts":[[2023,10,19]],"date-time":"2023-10-19T07:15:36Z","timestamp":1697699736000},"page":"8572","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Smart Parking Locks Based on Extended UNET-GWO-SVM Algorithm"],"prefix":"10.3390","volume":"23","author":[{"given":"Jianguo","family":"Shen","sequence":"first","affiliation":[{"name":"College of Physics and Electronic Information Engineering, Zhejiang Normal University, Jinhua 321000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-7772-5966","authenticated-orcid":false,"given":"Yu","family":"Xia","sequence":"additional","affiliation":[{"name":"College of Physics and Electronic Information Engineering, Zhejiang Normal University, Jinhua 321000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hao","family":"Ding","sequence":"additional","affiliation":[{"name":"College of Physics and Electronic Information Engineering, Zhejiang Normal University, Jinhua 321000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wen","family":"Cabrel","sequence":"additional","affiliation":[{"name":"College of Physics and Electronic Information Engineering, Zhejiang Normal University, Jinhua 321000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,10,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"10619","DOI":"10.1109\/JIOT.2020.3048177","article-title":"SRSP: A Secure and Reliable Smart Parking Scheme with Dual Privacy Preservation","volume":"8","author":"Lai","year":"2021","journal-title":"IEEE Internet Things J."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"3578","DOI":"10.1111\/itor.13184","article-title":"Online stochastic weighted matching algorithm for real-time shared parking","volume":"30","author":"Tang","year":"2023","journal-title":"Int. Trans. Oper. Res."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"5426","DOI":"10.1109\/JIOT.2020.2979899","article-title":"A Shared Bicycle Intelligent Lock Control and Management System Based on Multisensor","volume":"7","author":"Xue","year":"2020","journal-title":"IEEE Internet Things J."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1305","DOI":"10.1007\/s12652-020-02183-9","article-title":"Low power consumption and reliability of wireless communication network in intelligent parking system","volume":"12","author":"Lin","year":"2021","journal-title":"J. Ambient. Intell. Humaniz. Comput."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1648","DOI":"10.1177\/13548565211047157","article-title":"Locked down through virtual disconnect: Navigating life by staying on\/off the health QR code during COVID-19 in China","volume":"27","author":"Tai","year":"2021","journal-title":"Convergence"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"108756","DOI":"10.1016\/j.comnet.2021.108756","article-title":"A Social IoT-based platform for the deployment of a smart parking solution","volume":"205","author":"Floris","year":"2022","journal-title":"Comput. Netw."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Wang, H., and Xiao, N. (2023). Underwater Object Detection Method Based on Improved Faster RCNN. Appl. Sci., 13.","DOI":"10.3390\/app13042746"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"173804","DOI":"10.1109\/ACCESS.2020.3026181","article-title":"Robust Automatic Recognition of Chinese License Plates in Natural Scenes","volume":"8","author":"He","year":"2020","journal-title":"IEEE Access"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"211301","DOI":"10.1007\/s11432-019-2757-1","article-title":"Perceptual image quality assessment: A survey","volume":"63","author":"Zhai","year":"2020","journal-title":"Sci. China Inf. Sci."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"3790","DOI":"10.1109\/TIP.2020.2966081","article-title":"A Metric for Light Field Reconstruction, Compression, and Display Quality Evaluation","volume":"29","author":"Min","year":"2020","journal-title":"IEEE Trans. Image Process."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"5462","DOI":"10.1109\/TIP.2017.2735192","article-title":"Unified Blind Quality Assessment of Compressed Natural, Graphic, and Screen Content Images","volume":"26","author":"Min","year":"2017","journal-title":"IEEE Trans. Image Process."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"92907","DOI":"10.1109\/ACCESS.2020.2993008","article-title":"Automatic Vehicle License Plate Recognition Using Optimal K-Means with Convolutional Neural Network for Intelligent Transportation Systems","volume":"8","author":"Pustokhina","year":"2020","journal-title":"IEEE Access"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"201317","DOI":"10.1109\/ACCESS.2020.3035992","article-title":"A Robust Deep Learning Approach for Automatic Iranian Vehicle License Plate Detection and Recognition for Surveillance Systems","volume":"8","author":"Tourani","year":"2020","journal-title":"IEEE Access"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"211630","DOI":"10.1109\/ACCESS.2020.3040238","article-title":"A Robust License Plate Recognition Model Based on Bi-LSTM","volume":"8","author":"Zou","year":"2020","journal-title":"IEEE Access"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"697","DOI":"10.1109\/ACCESS.2019.2961744","article-title":"Robust License Plate Recognition with Shared Adversarial Training Network","volume":"8","author":"Zhang","year":"2020","journal-title":"IEEE Access"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"21777","DOI":"10.1109\/ACCESS.2021.3055243","article-title":"A Single Neural Network for Mixed Style License Plate Detection and Recognition","volume":"9","author":"Huang","year":"2021","journal-title":"IEEE Access"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"35185","DOI":"10.1109\/ACCESS.2020.2974973","article-title":"Multinational License Plate Recognition Using Generalized Character Sequence Detection","volume":"8","author":"Henry","year":"2020","journal-title":"IEEE Access"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"3686","DOI":"10.1109\/TITS.2019.2931791","article-title":"Simultaneous End-to-End Vehicle and License Plate Detection with Multi-Branch Attention Neural Network","volume":"21","author":"Chen","year":"2020","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_19","first-page":"1687","article-title":"Saliency guided faster-RCNN (SGFr-RCNN) model for object detection and recognition","volume":"34","author":"Sharma","year":"2022","journal-title":"J. King Saud Univ.-Comput. Inf. Sci."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Cai, C., Xu, H., Chen, S., Yang, L., Weng, Y., Huang, S., Dong, C., and Lou, X. (2023). Tree Recognition and Crown Width Extraction Based on Novel Faster-RCNN in a Dense Loblolly Pine Environment. Forests, 14.","DOI":"10.3390\/f14050863"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"92","DOI":"10.30693\/SMJ.2020.9.2.92","article-title":"Vehicle License Plate Recognition System using SSD-Mobilenet and ResNet for Mobile Device","volume":"9","author":"Kim","year":"2020","journal-title":"Korean Inst. Smart Media"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1049\/iet-its.2019.0481","article-title":"License plate segmentation and recognition system using deep learning and OpenVINO","volume":"14","author":"Ko","year":"2020","journal-title":"IET Intell. Transp. Syst."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1016\/j.imavis.2019.04.007","article-title":"Automatic License Plate Recognition via sliding-window darknet-YOLO deep learning","volume":"87","author":"Hendry","year":"2019","journal-title":"Image Vis. Comput."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1016\/j.icte.2019.11.001","article-title":"Real-time Bhutanese license plate localization using YOLO","volume":"6","author":"Jamtsho","year":"2020","journal-title":"ICT Express"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1041","DOI":"10.1049\/iet-ipr.2018.6449","article-title":"New approach to vehicle license plate location based on new model YOLO-L and plate pre-identification","volume":"13","author":"Min","year":"2019","journal-title":"IET Image Process."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Lin, H., Zhao, J., Li, S., and Qiu, G. (2020, January 12\u201314). License plate location method based on edge detection and mathematical morphology. Proceedings of the 2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC), Chongqing, China.","DOI":"10.1109\/ITNEC48623.2020.9085121"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Davix, X.A., Christopher, C.S., and Christine, S.S. (2017, January 20\u201321). License Plate Detection Using Channel Scale Space and Color Based Detection Method. Proceedings of the 2017 IEEE International Conference on Circuits and Systems (ICCS), Thiruvananthapuram, India.","DOI":"10.1109\/ICCS1.2017.8325967"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Mahmood, Z., Khan, K., Khan, U., Adil, S.H., Ali, S.S.A., and Shahzad, M. (2022). Towards Automatic License Plate Detection. Sensors, 22.","DOI":"10.3390\/s22031245"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"5256","DOI":"10.1109\/JSEN.2019.2900257","article-title":"License Plate Localization in Unconstrained Scenes Using a Two-Stage CNN-RNN","volume":"19","author":"Zhang","year":"2019","journal-title":"IEEE Sens. J."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"507","DOI":"10.1109\/TITS.2017.2784093","article-title":"A New CNN-Based Method for Multi-Directional Car License Plate Detection","volume":"19","author":"Xie","year":"2018","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Iqbal, A., and Jain, T. (2020, January 17\u201319). Synchrophasor based Data Driven Approach for Fault Identification using Multi-class Support Vector Machine. Proceedings of the 2020 21st National Power Systems Conference (NPSC), Gandhinagar, India.","DOI":"10.1109\/NPSC49263.2020.9331920"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"20107","DOI":"10.1007\/s11042-020-08629-8","article-title":"An efficient method for extraction and recognition of bangla characters from vehicle license plates","volume":"79","author":"Islam","year":"2020","journal-title":"Multimed. Tools Appl."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Ghahnavieh, A.E., Amirkhani-Shahraki, A., and Raie, A.A. (2014, January 20\u201322). Enhancing the license plates character recognition methods by means of SVM. Proceedings of the 2014 22nd Iranian Conference on Electrical Engineering (ICEE), Tehran, Iran.","DOI":"10.1109\/IranianCEE.2014.6999536"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Ye, X., Li, Y., Tong, L., and He, L. (2017, January 23\u201328). Remote sensing retrieval of suspended solids in Longquan Lake based on GA-SVM model. Proceedings of the 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Fort Worth, TX, USA.","DOI":"10.1109\/IGARSS.2017.8128249"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Song, G., and Zuo, Z. (2022, January 9\u201311). SVM License Plate Recognition Method Based on PSO Algorithm. Proceedings of the 2022 4th International Academic Exchange Conference on Science and Technology Innovation (IAECST), Guangzhou, China.","DOI":"10.1109\/IAECST57965.2022.10062228"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Hu, Y., Zhang, J., Jiang, W., and Sun, R. (2018, January 24\u201327). Chinese Pop Music Emotion Classification Based on FA-SVM. Proceedings of the 2018 International Conference on Control, Automation and Information Sciences (ICCAIS), Hangzhou, China.","DOI":"10.1109\/ICCAIS.2018.8570482"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Yu, X., Zhang, A., Mu, W., and Huo, X. (2020, January 20\u201322). Fault Diagnosis of Analog Circuit Based CS_SVM Algorithm. Proceedings of the 2020 IEEE 9th Data Driven Control and Learning Systems Conference (DDCLS), Liuzhou, China.","DOI":"10.1109\/DDCLS49620.2020.9275159"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Dong, J., Zhang, L., Liu, Z., Lin, Z., and Cai, Z. (2021, January 17\u201319). An Action Recognition Method Based on Radar Signal with Improved GWO-SVM Algorithm. Proceedings of the 2021 IEEE International Conference on Progress in Informatics and Computing (PIC), Shanghai, China.","DOI":"10.1109\/PIC53636.2021.9687009"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Singh, S., and Sehgal, V.K. (2022, January 1\u20133). A Comprehensive Study: Image Forensic Analysis Traditional to Cognitive Image Processing. Proceedings of the 2022 8th International Conference on Signal Processing and Communication (ICSC), Noida, India.","DOI":"10.1109\/ICSC56524.2022.10009322"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Awalgaonkar, N., Bartakke, P., and Chaugule, R. (2021, January 20\u201322). Automatic License Plate Recognition System Using SSD. Proceedings of the 2021 International Symposium of Asian Control Association on Intelligent Robotics and Industrial Automation (IRIA), Goa, India.","DOI":"10.1109\/IRIA53009.2021.9588707"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"347","DOI":"10.1007\/s10032-023-00432-z","article-title":"End-to-end optical music recognition for pianoform sheet music","volume":"26","author":"Rizo","year":"2023","journal-title":"Int. J. Doc. Anal. Recognit. (IJDAR)"},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Peng, H., Yu, J., and Nie, Y. (2023). Efficient Neural Network for Text Recognition in Natural Scenes Based on End-to-End Multi-Scale Attention Mechanism. Electronics, 12.","DOI":"10.3390\/electronics12061395"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"10236","DOI":"10.1109\/JIOT.2023.3237494","article-title":"CubeLearn: End-to-End Learning for Human Motion Recognition From Raw mmWave Radar Signals","volume":"10","author":"Zhao","year":"2023","journal-title":"IEEE Internet Things J."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Deng, F., Deng, L., Jiang, P., Zhang, G., and Yang, Q. (2023). ResSKNet-SSDP: Effective and Light End-To-End Architecture for Speaker Recognition. Sensors, 23.","DOI":"10.3390\/s23031203"},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Obeidat, Y.M., and Alqudah, A.M. (2023). An Embedded System Based on Raspberry Pi for Effective Electrocardiogram Monitoring. Appl. Sci., 13.","DOI":"10.3390\/app13148273"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/20\/8572\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T21:09:25Z","timestamp":1760130565000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/20\/8572"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,19]]},"references-count":45,"journal-issue":{"issue":"20","published-online":{"date-parts":[[2023,10]]}},"alternative-id":["s23208572"],"URL":"https:\/\/doi.org\/10.3390\/s23208572","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,10,19]]}}}