{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T17:53:32Z","timestamp":1775066012166,"version":"3.50.1"},"reference-count":37,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2021,4,10]],"date-time":"2021-04-10T00:00:00Z","timestamp":1618012800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Beijing major science and technology projects","award":["Z191100008019002"],"award-info":[{"award-number":["Z191100008019002"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Traditional road-embedded monitoring systems for traffic monitoring have the disadvantages of a short life, high energy consumption and data redundancy, resulting in insufficient durability and high cost. In order to improve the durability and efficiency of the road-embedded monitoring system, a pavement vibration monitoring system is developed based on the Internet of things (IoT). The system includes multi-acceleration sensing nodes, a gateway, and a cloud platform. The key design principles and technologies of each part of the system are proposed, which provides valuable experience for the application of IoT monitoring technology in road infrastructures. Characterized by low power consumption, distributed computing, and high extensibility properties, the pavement vibration IoT monitoring system can realize the monitoring, transmission, and analysis of pavement vibration signal, and acquires the real-time traffic information. This road-embedded system improves the intellectual capacity of road infrastructure and is conducive to the construction of a new generation of smart roads.<\/jats:p>","DOI":"10.3390\/s21082679","type":"journal-article","created":{"date-parts":[[2021,4,12]],"date-time":"2021-04-12T05:52:00Z","timestamp":1618206720000},"page":"2679","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":29,"title":["Real-Time and Efficient Traffic Information Acquisition via Pavement Vibration IoT Monitoring System"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8115-1780","authenticated-orcid":false,"given":"Zhoujing","family":"Ye","sequence":"first","affiliation":[{"name":"National Center for Materials Service Safety, University of Science and Technology Beijing, Haidian District, Beijing 100083, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8791-7393","authenticated-orcid":false,"given":"Guannan","family":"Yan","sequence":"additional","affiliation":[{"name":"National Center for Materials Service Safety, University of Science and Technology Beijing, Haidian District, Beijing 100083, China"}]},{"given":"Ya","family":"Wei","sequence":"additional","affiliation":[{"name":"Department of Civil Engineering, Tsinghua University, Haidian District, Beijing 100084, China"}]},{"given":"Bin","family":"Zhou","sequence":"additional","affiliation":[{"name":"Yunnan Research Institute of Highway Science and Technology, Panlong District, Kunming 650051, China"}]},{"given":"Ning","family":"Li","sequence":"additional","affiliation":[{"name":"Yunnan Research Institute of Highway Science and Technology, Panlong District, Kunming 650051, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5718-722X","authenticated-orcid":false,"given":"Shihui","family":"Shen","sequence":"additional","affiliation":[{"name":"Rail Transportation Engineering, Penn State University, Altoona, PA 16601, USA"}]},{"given":"Linbing","family":"Wang","sequence":"additional","affiliation":[{"name":"National Center for Materials Service Safety, University of Science and Technology Beijing, Haidian District, Beijing 100083, China"},{"name":"Virginia Tech, Blacksburg, VA 24061, USA"}]}],"member":"1968","published-online":{"date-parts":[[2021,4,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Hou, Y., Li, Q., Zhang, C., Lu, G., and Cao, D. (2020). The State-of-the-Art Review on Applications of Intrusive Sensing, Image Processing Techniques, and Machine Learning Methods in Pavement Monitoring and Analysis. Engineering.","DOI":"10.1016\/j.eng.2020.07.030"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1109\/MNET.001.1900146","article-title":"Integrating Blockchain and IoT\/ITS for Safer Roads","volume":"34","author":"Ali","year":"2020","journal-title":"IEEE Netw."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"657","DOI":"10.1007\/s11277-020-07386-z","article-title":"A Road Monitoring Approach with Real-Time Capturing of Events for Efficient Vehicles Safety in Smart City","volume":"114","author":"Lal","year":"2020","journal-title":"Wirel. Pers. Commun."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"441","DOI":"10.1109\/TITS.2010.2045500","article-title":"A Taxonomy and Analysis of Camera Calibration Methods for Traffic Monitoring Applications","volume":"11","author":"Kanhere","year":"2010","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_5","first-page":"364","article-title":"Radar-based road-traffic monitoring in urban environments","volume":"23","author":"Cabido","year":"2012","journal-title":"Digit. Signal Process."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"568","DOI":"10.1016\/j.trc.2009.10.006","article-title":"Evaluation of Traffic Data Obtained via GPS-Enabled Mobile Phones: The Mobile Century Field Experiment","volume":"18","author":"Herrera","year":"2010","journal-title":"Transp. Res. Part C"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"3868","DOI":"10.1109\/TGRS.2012.2186637","article-title":"Optimum SAR\/GMTI Processing and Its Application to the Radar Satellite RADARSAT-2 for Traffic Monitoring","volume":"50","author":"Sikaneta","year":"2012","journal-title":"Geosci. Remote Sens. IEEE Trans."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"065003","DOI":"10.1088\/0957-0233\/26\/6\/065003","article-title":"Sampling optimization for high-speed weigh-in-motion measurements using in-pavement strain-based sensors","volume":"26","author":"Zhang","year":"2015","journal-title":"Meas. Sci. Technol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1016\/j.iatssr.2010.06.003","article-title":"Improving truck safety: Potential of weigh-in-motion technology","volume":"34","author":"Jacob","year":"2010","journal-title":"IATSS Res."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"6952","DOI":"10.3390\/s8116952","article-title":"A novel vehicle classification using embedded strain gauge sensors","volume":"8","author":"Zhang","year":"2008","journal-title":"Sensors"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1380","DOI":"10.1109\/TITS.2014.2364253","article-title":"A prototype integrated monitoring system for pavement and traffic based on an embedded sensing network","volume":"16","author":"Xue","year":"2015","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1016\/S0304-3886(01)00043-2","article-title":"Assessment of vehicle weight measurement method using PVDF transducers","volume":"51","author":"Mazurek","year":"2001","journal-title":"J. Electrost."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"025023","DOI":"10.1088\/0964-1726\/24\/2\/025023","article-title":"A new smart traffic monitoring method using embedded cement-based piezoelectric sensors","volume":"24","author":"Zhang","year":"2015","journal-title":"Smart Mater. Struct."},{"key":"ref_14","unstructured":"Xu, D. (2010). Fabrication and Properties of Cement Based Piezoelectric Sensor and Its Application Research in Civil Engineering Fields. [Ph.D. Thesis, Shandong University]."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1177\/0361198118775840","article-title":"A vibration-based vehicle classification system using distributed optical sensing technology","volume":"2672","author":"Zhao","year":"2018","journal-title":"Transp. Res. Rec."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1080\/10298436.2017.1402601","article-title":"Airport pavement responses obtained from wireless sensing network upon digital signal processing","volume":"19","author":"Dong","year":"2018","journal-title":"Int. J. Pavement Eng."},{"key":"ref_17","unstructured":"Hostettler, R. (2009). Traffic Counting Using Measurements of Road Surface Vibrations. [Master\u2019s Thesis, Lulea University of Technology]."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"300","DOI":"10.1016\/j.trc.2014.06.007","article-title":"Estimating vehicle speed with embedded inertial sensors","volume":"46","author":"Levenberg","year":"2014","journal-title":"Trans. Res. Part C Emerg. Technol."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"206","DOI":"10.1016\/j.conbuildmat.2018.04.146","article-title":"Characterization of particle movement in Superpave gyratory compactor at meso-scale using SmartRock sensors","volume":"175","author":"Wang","year":"2018","journal-title":"Constr. Build. Mater."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"118592","DOI":"10.1016\/j.conbuildmat.2020.118592","article-title":"Experimental investigation on dynamic response of asphalt pavement using SmartRock sensor under vibrating compaction loading","volume":"247","author":"Dan","year":"2020","journal-title":"Constr. Build. Mater."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"443","DOI":"10.1111\/mice.12269","article-title":"Development of a cost-effective wireless vibration Weigh-In-Motion system to estimate axle weights of trucks","volume":"32","author":"Bajwa","year":"2017","journal-title":"Comput. Aided Civ. Infrastruct. Eng."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Bajwa, R., Rajagopal, R., Coleri, E., Varaiya, P., and Flores, C. (2013, January 8\u201311). In-pavement wireless weigh-in-motion. Proceedings of the 12th International Conference on Information Processing in Sensor Networks, Philadelphia, PA, USA.","DOI":"10.1145\/2461381.2461397"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1009","DOI":"10.1111\/mice.12544","article-title":"Pavement performance assessment using a cost-effective wireless accelerometer system","volume":"35","author":"Bajwa","year":"2020","journal-title":"Comput.-Aided Civ. Infrastruct. Eng."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"104","DOI":"10.1109\/TITS.2013.2273488","article-title":"A Wireless Accelerometer-Based Automatic Vehicle Classification Prototype System","volume":"15","author":"Ma","year":"2014","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1080\/15472450.2015.1004063","article-title":"Detection and classification of vehicles by measurement of road-pavement vibration and by means of supervised machine learning","volume":"20","author":"Stocker","year":"2016","journal-title":"J. Intell. Transp. Syst."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Kleyko, D., Hostettler, R., Lyamin, N., Birk, W., Wiklund, U., and Osipov, E. (2016, January 1\u20134). Vehicle Classification Using Road Side Sensors and Feature-free Data Smashing Approach. Proceedings of the IEEE 19th International Conference on Intelligent Transportation Systems (ITSC), Rio de Janeiro, Brazil.","DOI":"10.1109\/ITSC.2016.7795877"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1016\/j.ijprt.2017.07.005","article-title":"A prototype IOT based wireless sensor network for traffic information monitoring","volume":"11","author":"Huang","year":"2018","journal-title":"Int. J. Pavement Res. Technol."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Rayes, A., and Samer, S. (2017). Internet of Things from Hype to Reality, Springer Publishing Company, Incorporated.","DOI":"10.1007\/978-3-319-44860-2"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Zhang, C., Shen, S., Huang, H., and Wang, L. (2021). Estimation of the Vehicle Speed Using Cross-Correlation Algorithms and MEMS Wireless Sensors. Sensors, 21.","DOI":"10.3390\/s21051721"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"519","DOI":"10.1007\/s42947-020-0179-9","article-title":"Numerical analysis on distribution and response of acceleration field of pavement under moving load","volume":"14","author":"Yan","year":"2020","journal-title":"Int. J. Pavement Res. Technol."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"012123","DOI":"10.1088\/1757-899X\/1084\/1\/012123","article-title":"Design and Monitoring of Smart Roads Based on Weather Data by using IoT","volume":"1084","author":"Bachu","year":"2021","journal-title":"IOP Conf. Ser. Mater. Sci. Eng."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"101226","DOI":"10.1016\/j.aei.2020.101226","article-title":"A framework of pavement management system based on IoT and big data","volume":"47","author":"Dong","year":"2021","journal-title":"Adv. Eng. Inform."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Leizerovych, R., Kondratenko, G., Sidenko, I., and Kondratenko, Y. (2020, January 14\u201318). IoT-complex for Monitoring and Analysis of Motor Highway Condition Using Artificial Neural Networks. Proceedings of the 2020 IEEE 11th International Conference on Dependable Systems, Services and Technologies (DESSERT), Kyiv, Ukraine.","DOI":"10.1109\/DESSERT50317.2020.9125004"},{"key":"ref_34","first-page":"1","article-title":"Novel Convolutional Neural Network (NCNN) for the Diagnosis of Bearing Defects in Rotary Machinery","volume":"70","author":"Kumar","year":"2021","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"102500","DOI":"10.1016\/j.scs.2020.102500","article-title":"Congestion prediction for smart sustainable cities using IoT and machine learning approaches","volume":"64","author":"Majumdar","year":"2021","journal-title":"Sustain. Cities Soc."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Ye, Z., Wang, L., Xu, W., Gao, Z., and Yan, G. (2017). Monitoring traffic information with a developed acceleration sensing node. Sensors, 17.","DOI":"10.3390\/s17122817"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"134","DOI":"10.1111\/mice.12448","article-title":"Collecting comprehensive traffic information using pavement vibration monitoring data","volume":"35","author":"Ye","year":"2020","journal-title":"Comput. Aided Civ. Infrastruct. Eng."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/8\/2679\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T14:12:17Z","timestamp":1760364737000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/8\/2679"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,4,10]]},"references-count":37,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2021,4]]}},"alternative-id":["s21082679"],"URL":"https:\/\/doi.org\/10.3390\/s21082679","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,4,10]]}}}