{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,21]],"date-time":"2026-02-21T18:03:33Z","timestamp":1771697013415,"version":"3.50.1"},"reference-count":52,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2020,3,31]],"date-time":"2020-03-31T00:00:00Z","timestamp":1585612800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>The current methods that aim at monitoring the structural health status (SHS) of road pavements allow detecting surface defects and failures. This notwithstanding, there is a lack of methods and systems that are able to identify concealed cracks (particularly, bottom-up cracks) and monitor their growth over time. For this reason, the objective of this study is to set up a supervised machine learning (ML)-based method for the identification and classification of the SHS of a differently cracked road pavement based on its vibro-acoustic signature. The method aims at collecting these signatures (using acoustic-sensors, located at the roadside) and classifying the pavement\u2019s SHS through ML models. Different ML classifiers (i.e., multilayer perceptron, MLP, convolutional neural network, CNN, random forest classifier, RFC, and support vector classifier, SVC) were used and compared. Results show the possibility of associating with great accuracy (i.e., MLP = 91.8%, CNN = 95.6%, RFC = 91.0%, and SVC = 99.1%) a specific vibro-acoustic signature to a differently cracked road pavement. These results are encouraging and represent the bases for the application of the proposed method in real contexts, such as monitoring roads and bridges using wireless sensor networks, which is the target of future studies.<\/jats:p>","DOI":"10.3390\/a13040081","type":"journal-article","created":{"date-parts":[[2020,3,31]],"date-time":"2020-03-31T10:29:38Z","timestamp":1585650578000},"page":"81","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":56,"title":["Detection and Monitoring of Bottom-Up Cracks in Road Pavement Using a Machine-Learning Approach"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3576-7976","authenticated-orcid":false,"given":"Filippo Giammaria","family":"Pratic\u00f2","sequence":"first","affiliation":[{"name":"Department of Information, Infrastructure and Sustainable Energy (DIIES), Via Graziella, Feo di Vito, University Mediterranea of Reggio Calabria, 89124 Reggio Calabria, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7312-6726","authenticated-orcid":false,"given":"Rosario","family":"Fedele","sequence":"additional","affiliation":[{"name":"Department of Information, Infrastructure and Sustainable Energy (DIIES), Via Graziella, Feo di Vito, University Mediterranea of Reggio Calabria, 89124 Reggio Calabria, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9981-4108","authenticated-orcid":false,"given":"Vitalii","family":"Naumov","sequence":"additional","affiliation":[{"name":"Faculty of Civil Engineering, Cracow University of Technology, Warszawska 24, 31155 Krakow, Poland"}]},{"given":"Tomas","family":"Sauer","sequence":"additional","affiliation":[{"name":"Institute for Software Systems in Technical Applications of Computer Science, University of Passau, Innstra\u00dfe 43, D-94032 Passau, Germany"}]}],"member":"1968","published-online":{"date-parts":[[2020,3,31]]},"reference":[{"key":"ref_1","first-page":"670","article-title":"A review on fatigue and rutting performance of asphalt mixes","volume":"6","author":"Moghaddam","year":"2011","journal-title":"Sci. Res. Essays"},{"key":"ref_2","unstructured":"Gedafa, D.S. (2007, January 16). Performance Prediction and Maintenance of Flexible Pavement. Proceedings of the 2007 Mid-Continent Transportation Research Symposium, Ames, IA, USA."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1186\/s12940-016-0203-3","article-title":"Undereporting of Acute Pesticide Poisoning in Tanzania: Modelling Results from Two Cross-Sectional Studies","volume":"15","author":"Lekei","year":"2016","journal-title":"Environ. Health"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1016\/j.conbuildmat.2018.03.058","article-title":"Asphalt mixtures modified with basalt fibres for surface courses","volume":"170","author":"Celauro","year":"2018","journal-title":"Constr. Build. Mater."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1016\/j.sbspro.2018.03.004","article-title":"A comparison between smart city approaches in road traffic management","volume":"238","author":"Pop","year":"2018","journal-title":"Procedia Soc. Behav. Sci."},{"key":"ref_6","unstructured":"The European Parliament and the Council of the European Union (2020, January 20). Directive 2010\/40\/EU of the European Parliament and of the Council of 7 July 2010 on the framework for the deployment of Intelligent Transport Systems in the field of road transport and for interfaces with other modes of transport (Text with EEA relevance). Available online: https:\/\/www.cita.lu\/uploads\/its\/Directive_2010-40-EU_EN.pdf."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"605","DOI":"10.1016\/j.jhazmat.2009.08.136","article-title":"Potential of fire extinguisher powder as a filler in bituminous mixes","volume":"173","author":"Moro","year":"2010","journal-title":"J. Hazard. Mater."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Pratic\u00f2, F.G., Vaiana, R., and Gallelli, V. (2012). Transport and Traffic Management by Micro Simulation Models: Operational Use and Performance of Roundabouts, WIT Transactions on the Built Environment.","DOI":"10.2495\/UT120331"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Cafiso, S., D\u2019Agostino, C., Delfino, E., and Montella, A. (2017, January 26\u201328). From manual to automatic pavement distress detection and classification. Proceedings of the 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS), Naples, Italy.","DOI":"10.1109\/MTITS.2017.8005711"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s12544-015-0156-6","article-title":"Review of remote sensing methodologies for pavement management and assessment","volume":"7","author":"Schnebele","year":"2015","journal-title":"Eur. Transp. Res. Rev."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"201","DOI":"10.1016\/j.sigpro.2016.05.016","article-title":"An overview of ground-penetrating radar signal processing techniques for road inspections","volume":"132","author":"Benedetto","year":"2017","journal-title":"Signal Process."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"399","DOI":"10.1111\/mice.12052","article-title":"Wavelet denoising of TSD deflection slope measurements for improved pavement structural evaluation","volume":"29","author":"Katicha","year":"2014","journal-title":"Comput. Civ. Infrastruct. Eng."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"3334","DOI":"10.1109\/TITS.2017.2773084","article-title":"Evaluation of detection approaches for road anomalies based on accelerometer readings - Addressing who\u2019s who","volume":"19","author":"Carlos","year":"2018","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"99","DOI":"10.3846\/1822-427X.2009.4.99-107","article-title":"Factors affecting variance and bias of non-nuclear density gauges for porous european mixes and dense-graded friction courses","volume":"4","author":"Moro","year":"2009","journal-title":"Balt. J. Road Bridg. Eng."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1016\/j.conbuildmat.2015.10.021","article-title":"A study on the relationship between mean texture depth and mean profile depth of asphalt pavements","volume":"101","author":"Vaiana","year":"2015","journal-title":"Constr. Build. Mater."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1016\/j.apacoust.2013.07.017","article-title":"A modified Close Proximity method to evaluate the time trends of road pavements acoustical performances","volume":"76","author":"Licitra","year":"2014","journal-title":"Appl. Acoust."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1171","DOI":"10.1016\/S0003-682X(03)00085-9","article-title":"A novel approach to the acoustic characterisation of porous road surfaces","volume":"64","author":"Morgan","year":"2003","journal-title":"Appl. Acoust."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1357","DOI":"10.1016\/j.soildyn.2011.04.009","article-title":"The effect of road unevenness on the dynamic vehicle response and ground-borne vibrations due to road traffic","volume":"31","author":"Lak","year":"2011","journal-title":"Soil Dyn. Earthq. Eng."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"196","DOI":"10.1016\/j.autcon.2017.08.017","article-title":"Pothole detection on asphalt pavements from 2D-colour pothole images using fuzzy c-means clustering and morphological reconstruction","volume":"83","author":"Ouma","year":"2017","journal-title":"Autom. Constr."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"302","DOI":"10.1590\/S1678-58782011000300005","article-title":"Vehicle dynamic response due to pavement roughness","volume":"33","author":"Barbosa","year":"2011","journal-title":"J. Braz. Soc. Mech. Sci. Eng."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1061\/(ASCE)TE.1943-5436.0000617","article-title":"Estimation of pavement macrotexture by principal component analysis of acoustic measurements","volume":"140","author":"Zhang","year":"2014","journal-title":"J. Transp. Eng."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"725","DOI":"10.1080\/10298436.2012.705004","article-title":"Pavement macro-texture analysis using wavelets","volume":"14","author":"Zelelew","year":"2013","journal-title":"Int. J. Pavement Eng."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Subirats, P., Dumoulin, J., Legeay, V., and Barba, D. (2006, January 8\u201311). Automation of pavement surface crack detection using the continuous wavelet transform. Proceedings of the International Conference on Image Processing, Atlanta, GA, USA.","DOI":"10.1109\/ICIP.2006.313007"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"481","DOI":"10.1016\/j.aei.2016.06.003","article-title":"Wavelet-morphology based detection of incipient linear cracks in asphalt pavements from RGB camera imagery and classification using circular Radon transform","volume":"30","author":"Ouma","year":"2016","journal-title":"Adv. Eng. Inform."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"342","DOI":"10.1111\/mice.12042","article-title":"Road crack detection using visual features extracted by gabor filters","volume":"29","author":"Zalama","year":"2014","journal-title":"Comput. Civ. Infrastruct. Eng."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Hassan, N., Mathavan, S., and Kamal, K. (2017, January 7\u20138). Road crack detection using the particle filter. Proceedings of the 23rd IEEE International Conference on Automation and Computing (ICAC), Huddersfield, UK.","DOI":"10.23919\/IConAC.2017.8082050"},{"key":"ref_27","first-page":"6056","article-title":"Review and analysis of crack detection and classification techniques based on crack types","volume":"13","author":"Sitara","year":"2018","journal-title":"Int. J. Appl. Eng. Res."},{"key":"ref_28","unstructured":"Moussa, G., and Hussain, K. (2011, January 19). A new technique for automatic detection and parameters estimation of pavement crack. Proceedings of the 4th International Multi-Conference on Engineering and Technological Innovation, Orlando, FL, USA."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"699","DOI":"10.1016\/j.trd.2018.04.024","article-title":"Analyzing spatiotemporal traffic line source emissions based on massive didi online car-hailing service data","volume":"62","author":"Sun","year":"2018","journal-title":"Transp. Res. Part D Transp. Environ."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"675","DOI":"10.5198\/jtlu.2017.954","article-title":"Analyzing spatiotemporal congestion pattern on urban roads based on taxi GPS data","volume":"10","author":"Zhang","year":"2017","journal-title":"J. Transp. Land Use"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"775","DOI":"10.1016\/j.conbuildmat.2017.04.097","article-title":"Recognition, location, measurement, and 3D reconstruction of concealed cracks using convolutional neural networks","volume":"146","author":"Tong","year":"2017","journal-title":"Constr. Build. Mater."},{"key":"ref_32","first-page":"397","article-title":"Prediction of the MEPDG asphalt concrete permanent deformation using closed form solution","volume":"7","author":"Jeong","year":"2014","journal-title":"Int. J. Pavement Res. Technol."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"7088","DOI":"10.1016\/j.eswa.2010.12.060","article-title":"An expert system based on wavelet transform and radon neural network for pavement distress classification","volume":"38","author":"Zakeri","year":"2011","journal-title":"Expert Syst. Appl."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Shi, A., and Yu, X.H. (2012, January 2\u20134). Structural damage detection using artificial neural networks and wavelet transform. Proceedings of the IEEE International Conference on Computational Intelligence for Measurement Systems and Applications (CIMSA), Tianjin, China.","DOI":"10.1109\/CIMSA.2012.6269593"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"114","DOI":"10.1016\/j.commatsci.2013.09.025","article-title":"Sensitivity analysis of crack propagation in pavement bituminous layered structures using a hybrid system integrating Artificial Neural Networks and Finite Element Method","volume":"82","author":"Gajewski","year":"2014","journal-title":"Comput. Mater. Sci."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Wang, X., and Hu, Z. (2017, January 8\u201310). Grid-based pavement crack analysis using deep learning. Proceedings of the 4th International Conference on Transportation Information and Safety (ICTIS), Banff, AB, Canada.","DOI":"10.1109\/ICTIS.2017.8047878"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"119","DOI":"10.3141\/2595-13","article-title":"Comparison of supervised classifcation techniques for vision-based pavement crack detection","volume":"2595","author":"Mokhtari","year":"2016","journal-title":"Transp. Res. Rec."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"438","DOI":"10.1016\/j.measurement.2018.11.081","article-title":"New machine learning-based prediction models for fracture energy of asphalt mixtures","volume":"135","author":"Majidifard","year":"2019","journal-title":"Meas. J. Int. Meas. Confed."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"323","DOI":"10.18280\/mmep.050408","article-title":"Energy savings in transportation: Setting up an innovative SHM method","volume":"5","author":"Fedele","year":"2018","journal-title":"Math. Model. Eng. Probl."},{"key":"ref_40","unstructured":"Fedele, R., Pratic\u00f2, F.G., Carotenuto, R., and Della Corte, F.G. (2017, January 23\u201327). Damage detection into road pavements through acoustic signature analysis: First results. Proceedings of the 24th International Congress on Sound and Vibration (ICSV), London, UK."},{"key":"ref_41","unstructured":"Fedele, R., Della Corte, F.G., Carotenuto, R., and Pratic\u00f2, F.G. (2017, January 12\u201315). Sensing road pavement health status through acoustic signals analysis. Proceedings of the 13th Conference on PhD Research in Microelectronics and Electronics (PRIME), Giardini Naxos, Italy."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1016\/j.jappgeo.2017.03.007","article-title":"Extended analytical solutions for effective elastic moduli of cracked porous media","volume":"140","author":"Nguyen","year":"2017","journal-title":"J. Appl. Geophys."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1016\/S0267-7261(00)00002-6","article-title":"Propagation and attenuation characteristics of various ground vibrations","volume":"19","author":"Kim","year":"2000","journal-title":"Soil Dyn. Earthq. Eng."},{"key":"ref_44","unstructured":"Fedele, R., and Pratic\u00f2, F.G. (2019, January 30). Monitoring infrastructure asset through its acoustic signature. Proceedings of the INTER-NOISE and NOISE-CON Congress and Conference Proceedings, Madrid, Spain."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"2230","DOI":"10.1520\/JTE20190209","article-title":"The prediction of road cracks through acoustic signature: Extended finite element modeling and experiments","volume":"49","author":"Fedele","year":"2021","journal-title":"J. Test. Eval."},{"key":"ref_46","unstructured":"(2020, January 20). Google Brain Tensorflow. Available online: https:\/\/www.tensorflow.org\/tutorials\/."},{"key":"ref_47","unstructured":"Cournapeau, D. (2020, January 20). Scikit-Learn. Available online: https:\/\/scikit-learn.org\/stable\/."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1109\/2.485891","article-title":"Artificial neural networks: A tutorial","volume":"29","author":"Jain","year":"1996","journal-title":"Computer"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/S0167-7012(00)00201-3","article-title":"Artificial neural networks: Fundamentals, computing, design, and application","volume":"43","author":"Basheer","year":"2000","journal-title":"J. Microbiol. Methods"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/j.trd.2014.04.004","article-title":"On the dependence of acoustic performance on pavement characteristics","volume":"29","year":"2014","journal-title":"Transp. Res. Part D Transp. Environ."},{"key":"ref_51","first-page":"605","article-title":"Energy harvesting for IoT road monitoring systems","volume":"17","author":"Fedele","year":"2018","journal-title":"Instr. Mes. Metr."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3390\/electronics8101180","article-title":"A real-time decision platform for the management of structures and infrastructures","volume":"8","author":"Merenda","year":"2019","journal-title":"Electronics"}],"container-title":["Algorithms"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1999-4893\/13\/4\/81\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:13:49Z","timestamp":1760174029000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1999-4893\/13\/4\/81"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,3,31]]},"references-count":52,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2020,4]]}},"alternative-id":["a13040081"],"URL":"https:\/\/doi.org\/10.3390\/a13040081","relation":{},"ISSN":["1999-4893"],"issn-type":[{"value":"1999-4893","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,3,31]]}}}