{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T00:17:58Z","timestamp":1773706678293,"version":"3.50.1"},"reference-count":37,"publisher":"SAGE Publications","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IDT"],"published-print":{"date-parts":[[2024,9,16]]},"abstract":"<jats:p>In recent smart city innovations, parking lot location has garnered a lot of focus. The issue of where to put cars has been the subject of a lot of literature. However, these efforts rely heavily on algorithms built on centralized servers using historical data as their basis. In this study, we propose a smart parking allocation system by fusing k-NN, decision trees, and random forests with the boosting techniques Adaboost and Catboost. Implementing the recommended intelligent parking distribution technique in Smart Society 5.0 offers promise as a practical means of handling parking in contemporary urban settings. Users will be given parking spots in accordance with their preferences and present locations as recorded in a centralized database using the proposed system\u2019s hybrid algorithms. The evaluation of performance considers the effectiveness of both the ML classifier and the boosting technique, and it finds that the combination of Random Forest and Adaboost achieves 98% accuracy. Users and operators alike can benefit from the suggested method\u2019s optimised parking allocation and pricing structure, which in turn provides more convenient and efficient parking options.<\/jats:p>","DOI":"10.3233\/idt-230339","type":"journal-article","created":{"date-parts":[[2024,7,5]],"date-time":"2024-07-05T15:47:16Z","timestamp":1720194436000},"page":"2145-2159","source":"Crossref","is-referenced-by-count":6,"title":["An intelligent parking allocation framework for digital society 5.0"],"prefix":"10.1177","volume":"18","author":[{"given":"Karthikeyan","family":"Velayuthapandian","sequence":"first","affiliation":[]},{"given":"Mathavan","family":"Veyilraj","sequence":"additional","affiliation":[]},{"given":"Marlin Abhishek","family":"Jayakumaraj","sequence":"additional","affiliation":[]}],"member":"179","reference":[{"key":"10.3233\/IDT-230339_ref1","first-page":"123","article-title":"An intelligent parking system using machine learning algorithms","volume":"76","author":"Al-Dmour","year":"2019","journal-title":"Computers & Electrical Engineering"},{"key":"10.3233\/IDT-230339_ref2","first-page":"57","article-title":"Intelligent parking system: A hybrid GA-SVM approach","volume":"126","author":"Azadeh","year":"2019","journal-title":"Expert Systems with Applications"},{"issue":"8","key":"10.3233\/IDT-230339_ref5","doi-asserted-by":"crossref","first-page":"5389","DOI":"10.1109\/TITS.2020.3011198","article-title":"A novel emergent intelligence technique for public transport vehicle allocation problem in a dynamic transportation system","volume":"22","author":"Chavhan","year":"2020","journal-title":"IEEE Transactions on Intelligent Transportation Systems."},{"issue":"2","key":"10.3233\/IDT-230339_ref7","first-page":"812","article-title":"A hybrid CNN-SVM model for intelligent parking system","volume":"11","author":"Chong","year":"2021","journal-title":"Applied Sciences."},{"issue":"11","key":"10.3233\/IDT-230339_ref8","doi-asserted-by":"crossref","first-page":"3872","DOI":"10.3390\/app10113872","article-title":"Survey of smart parking systems","volume":"10","author":"Diaz Og\u00e1s","year":"2020","journal-title":"Applied Sciences."},{"issue":"12","key":"10.3233\/IDT-230339_ref9","doi-asserted-by":"crossref","first-page":"1474","DOI":"10.3390\/electronics10121474","article-title":"Network slicing on 5G vehicular cloud computing systems","volume":"10","author":"Skondras","year":"2021","journal-title":"Electronics."},{"key":"10.3233\/IDT-230339_ref10","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1016\/j.vehcom.2019.01.001","article-title":"Mobility management on 5g vehicular cloud computing systems","volume":"16","author":"Skondras","year":"2019","journal-title":"Vehicular Communications."},{"key":"10.3233\/IDT-230339_ref13","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1016\/j.pecs.2016.12.004","article-title":"Fuel consumption and CO2 emissions from passenger cars in Europe-Laboratory versus real-world emissions","volume":"60","author":"Fontaras","year":"2017","journal-title":"Progress in Energy and Combustion Science."},{"issue":"6","key":"10.3233\/IDT-230339_ref14","doi-asserted-by":"crossref","first-page":"2504","DOI":"10.1109\/TMAG.2013.2252605","article-title":"A method for eliminating metadata cache deallocation latency in enterprise file servers","volume":"49","author":"Fukatani","year":"2013","journal-title":"IEEE Transactions on Magnetics."},{"issue":"1","key":"10.3233\/IDT-230339_ref15","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1109\/MITS.2018.2879192","article-title":"Establishing heterogeneous parking prices for uniform parking availability for autonomous and human-driven vehicles","volume":"11","author":"Fulman","year":"2018","journal-title":"IEEE Intelligent Transportation Systems Magazine."},{"key":"10.3233\/IDT-230339_ref16","doi-asserted-by":"crossref","first-page":"1278","DOI":"10.1016\/j.sbspro.2012.09.842","article-title":"A new \u201csmart parking\u201d system infrastructure and implementation","volume":"54","author":"Geng","year":"2012","journal-title":"Procedia-Social and Behavioral Sciences."},{"issue":"6","key":"10.3233\/IDT-230339_ref17","doi-asserted-by":"crossref","first-page":"5945","DOI":"10.1109\/TVT.2020.2979637","article-title":"A parking slot allocation framework based on virtual voting and adaptive pricing algorithm","volume":"69","author":"Hassija","year":"2020","journal-title":"IEEE Transactions on Vehicular Technology."},{"issue":"9","key":"10.3233\/IDT-230339_ref19","doi-asserted-by":"crossref","first-page":"2041","DOI":"10.1109\/TCSVT.2016.2564899","article-title":"Vacant parking space detection based on a multilayer inference framework","volume":"27","author":"Huang","year":"2016","journal-title":"IEEE Transactions on Circuits and Systems for Video Technology."},{"issue":"6","key":"10.3233\/IDT-230339_ref20","doi-asserted-by":"crossref","first-page":"5482","DOI":"10.1109\/JSEN.2022.3148128","article-title":"Challenges, applications, and future of wireless sensors in Internet of Things: A review","volume":"22","author":"Jamshed","year":"2022","journal-title":"IEEE Sensors Journal."},{"key":"10.3233\/IDT-230339_ref21","doi-asserted-by":"crossref","first-page":"2235","DOI":"10.1016\/j.procs.2020.04.241","article-title":"Machine learning approach on traffic congestion monitoring system in internet of vehicles","volume":"171","author":"Kamble","year":"2020","journal-title":"Procedia Computer Science."},{"issue":"3","key":"10.3233\/IDT-230339_ref23","first-page":"1033","article-title":"Hybrid machine learning classification scheme for speaker identification","volume":"46","author":"Karthikeyan","year":"2022","journal-title":"Journal of Forensic Sciences."},{"issue":"2","key":"10.3233\/IDT-230339_ref24","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s10044-024-01278-9","article-title":"A stacked convolutional neural network framework with multi-scale attention mechanism for text-independent voiceprint recognition","volume":"27","author":"Karthikeyan","year":"2024","journal-title":"Pattern Analysis and Applications."},{"issue":"2","key":"10.3233\/IDT-230339_ref25","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1080\/0952813X.2022.2092560","article-title":"Modified layer deep convolution neural network for text-independent speaker recognition","volume":"36","author":"Karthikeyan","year":"2024","journal-title":"Journal of Experimental & Theoretical Artificial Intelligence."},{"key":"10.3233\/IDT-230339_ref26","first-page":"55024","article-title":"A parking occupancy prediction algorithm using a decision tree and random forest","volume":"6","author":"Kim","year":"2018","journal-title":"IEEE Access."},{"issue":"2","key":"10.3233\/IDT-230339_ref27","first-page":"243","article-title":"Parking slot prediction using machine learning algorithms","volume":"9","author":"Khomh","year":"2018","journal-title":"Journal of Ambient Intelligence and Humanized Computing."},{"issue":"12","key":"10.3233\/IDT-230339_ref28","first-page":"2829","article-title":"A parking-slot prediction system based on a k-NN algorithm using real-time camera images","volume":"17","author":"Lee","year":"2017","journal-title":"Sensors."},{"key":"10.3233\/IDT-230339_ref29","doi-asserted-by":"crossref","first-page":"72759","DOI":"10.1109\/ACCESS.2021.3079903","article-title":"A real-time intelligent energy management strategy for hybrid electric vehicles using reinforcement learning","volume":"9","author":"Lee","year":"2021","journal-title":"IEEE Access."},{"key":"10.3233\/IDT-230339_ref30","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/1476-069X-9-65","article-title":"Evaluation of the public health impacts of traffic congestion: A health risk assessment","volume":"9","author":"Levy","year":"2010","journal-title":"Environmental Health."},{"key":"10.3233\/IDT-230339_ref31","doi-asserted-by":"crossref","first-page":"34275","DOI":"10.1109\/ACCESS.2019.2904972","article-title":"SPA: Smart parking algorithm based on driver behavior and parking traffic predictions","volume":"7","author":"Lin","year":"2019","journal-title":"IEEE Access."},{"issue":"12","key":"10.3233\/IDT-230339_ref32","doi-asserted-by":"crossref","first-page":"3229","DOI":"10.1109\/TITS.2017.2685143","article-title":"A survey of smart parking solutions","volume":"18","author":"Lin","year":"2017","journal-title":"IEEE Transactions on Intelligent Transportation Systems."},{"issue":"4","key":"10.3233\/IDT-230339_ref33","doi-asserted-by":"crossref","first-page":"1692","DOI":"10.1109\/TCNS.2022.3165015","article-title":"Parking lot allocation using rematching and dynamic parking fee design","volume":"9","author":"Nakazato","year":"2022","journal-title":"IEEE Transactions on Control of Network Systems."},{"issue":"10","key":"10.3233\/IDT-230339_ref35","first-page":"160","article-title":"Intelligent parking system using support vector machines","volume":"5","author":"Ramanathan","year":"2016","journal-title":"International Journal of Computer Science and Mobile Computing."},{"issue":"1.9","key":"10.3233\/IDT-230339_ref36","first-page":"121","article-title":"A comparative study of machine learning algorithms for parking slot prediction","volume":"8","author":"Sahu","year":"2019","journal-title":"International Journal of Engineering & Technology."},{"issue":"5","key":"10.3233\/IDT-230339_ref37","first-page":"984","article-title":"An intelligent parking management system based on a hybrid FCM-ANFIS model","volume":"17","author":"Shakya","year":"2017","journal-title":"Sensors."},{"key":"10.3233\/IDT-230339_ref40","doi-asserted-by":"crossref","first-page":"313","DOI":"10.1016\/j.comcom.2020.02.069","article-title":"Applications of artificial intelligence and machine learning in smart cities","volume":"154","author":"Ullah","year":"2020","journal-title":"Computer Communications."},{"key":"10.3233\/IDT-230339_ref41","doi-asserted-by":"crossref","unstructured":"Velayuthapandian K, Subramoniam SP. A focus module-based lightweight end-to-end CNN framework for voiceprint recognition. Signal, Image and Video Processing. 2023 Sep; 17(6): 2817-25.","DOI":"10.1007\/s11760-023-02500-7"},{"key":"10.3233\/IDT-230339_ref42","doi-asserted-by":"crossref","first-page":"174530","DOI":"10.1109\/ACCESS.2020.3025589","article-title":"Short-term prediction of available parking space based on machine learning approaches","volume":"8","author":"Ye","year":"2020","journal-title":"IEEE Access."},{"issue":"1","key":"10.3233\/IDT-230339_ref43","first-page":"324","article-title":"Parking lot slot prediction by using artificial neural network","volume":"10","author":"Yildirim","year":"2017","journal-title":"International Journal of Computational Intelligence Systems."},{"key":"10.3233\/IDT-230339_ref44","doi-asserted-by":"crossref","first-page":"307","DOI":"10.1016\/j.scitotenv.2013.01.074","article-title":"Air pollution and health risks due to vehicle traffic","volume":"450","author":"Zhang","year":"2013","journal-title":"Science of the Total Environment."},{"issue":"8","key":"10.3233\/IDT-230339_ref45","first-page":"2993","article-title":"A comparative study of machine learning algorithms for parking slot prediction","volume":"10","author":"Zhang","year":"2019","journal-title":"Journal of Ambient Intelligence and Humanized Computing."},{"issue":"3","key":"10.3233\/IDT-230339_ref46","doi-asserted-by":"crossref","first-page":"821","DOI":"10.1086\/692115","article-title":"Traffic congestion, ambient air pollution, and health: Evidence from driving restrictions in Beijing","volume":"4","author":"Zhong","year":"2017","journal-title":"Journal of the Association of Environmental and Resource Economists."},{"issue":"3","key":"10.3233\/IDT-230339_ref47","first-page":"202","article-title":"Intelligent parking system using a hybrid decision tree-artificial neural network approach","volume":"24","author":"Zhu","year":"2020","journal-title":"Journal of Intelligent Transportation Systems."}],"container-title":["Intelligent Decision Technologies"],"original-title":[],"link":[{"URL":"https:\/\/content.iospress.com\/download?id=10.3233\/IDT-230339","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,3,11]],"date-time":"2025-03-11T08:05:02Z","timestamp":1741680302000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/full\/10.3233\/IDT-230339"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9,16]]},"references-count":37,"journal-issue":{"issue":"3"},"URL":"https:\/\/doi.org\/10.3233\/idt-230339","relation":{},"ISSN":["1872-4981","1875-8843"],"issn-type":[{"value":"1872-4981","type":"print"},{"value":"1875-8843","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,9,16]]}}}