{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,25]],"date-time":"2026-06-25T10:00:32Z","timestamp":1782381632230,"version":"3.54.5"},"reference-count":39,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2025,12,22]],"date-time":"2025-12-22T00:00:00Z","timestamp":1766361600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"EU Funded Erasmus Plus Capacity Building in Higher Education ACTIVE Climate Action Project","award":["ERASMUS-EDU-2023-CBHE Project:101082866 ACTIVE"],"award-info":[{"award-number":["ERASMUS-EDU-2023-CBHE Project:101082866 ACTIVE"]}]},{"name":"EU Funded Erasmus Plus Capacity Building in Higher Education Project CENTRAL(Capacity building and ExchaNge towards attaining Technological Research and modernizing Academic Learning","award":["598914-EPP-1-2018-1-DK-EPPKA2- CBHE-JP"],"award-info":[{"award-number":["598914-EPP-1-2018-1-DK-EPPKA2- CBHE-JP"]}]},{"name":"National Center of Robotics and Automation- Condition Monitoring Systems Laboratory, Mehran University of Engineering and Technology","award":["2(1076)\/HEC\/M&E\/2018\/704"],"award-info":[{"award-number":["2(1076)\/HEC\/M&E\/2018\/704"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computers"],"abstract":"<jats:p>This research article presents a novel road defect detection methodology that integrates deep learning techniques and a federated learning approach. Existing road defect detection systems heavily rely on manual inspection and sensor-based techniques, which are prone to errors. To overcome these limitations, a data-acquisition system utilizing a GoPro HERO 9 camera was used to capture high-quality videos and images of road surfaces. A comprehensive dataset consist of multiple road defects, such as cracks, potholes, and uneven surfaces, that were pre-processed and augmented to prepare them for effective model training. A Real-Time Detection Transformer-based architecture model was used that achieved mAP50 of 99.60% and mAP50-95 of 99.55% in cross-validation of road defect detection and object detection tasks. Federated learning helped to train the model in a decentralized manner that enhanced data protection and scalability. The proposed system achieves higher detection accuracy for road defects by increasing speed and efficiency while enhancing scalability, which makes it a potential asset for real-time monitoring.<\/jats:p>","DOI":"10.3390\/computers15010006","type":"journal-article","created":{"date-parts":[[2025,12,23]],"date-time":"2025-12-23T14:27:47Z","timestamp":1766500067000},"page":"6","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Federated Learning-Based Road Defect Detection with Transformer Models for Real-Time Monitoring"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-7474-8674","authenticated-orcid":false,"given":"Bushra","family":"Abro","sequence":"first","affiliation":[{"name":"National Centre for Robotics, Automation and Artificial Intelligence, Mehran University of Engineering and Technology (MUET), Jamshoro 76062, Pakistan"},{"name":"NCRA-CMS Lab, Mehran University of Engineering and Technology (MUET), Jamshoro 76062, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-2947-5808","authenticated-orcid":false,"given":"Sahil","family":"Jatoi","sequence":"additional","affiliation":[{"name":"National Centre for Robotics, Automation and Artificial Intelligence, Mehran University of Engineering and Technology (MUET), Jamshoro 76062, Pakistan"},{"name":"NCRA-CMS Lab, Mehran University of Engineering and Technology (MUET), Jamshoro 76062, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4068-0875","authenticated-orcid":false,"given":"Muhammad Zakir","family":"Shaikh","sequence":"additional","affiliation":[{"name":"National Centre for Robotics, Automation and Artificial Intelligence, Mehran University of Engineering and Technology (MUET), Jamshoro 76062, Pakistan"},{"name":"NCRA-CMS Lab, Mehran University of Engineering and Technology (MUET), Jamshoro 76062, Pakistan"},{"name":"Mechanical Engineering and Energy Efficiency, School of Industrial Engineering, University of Malaga, C\/Doctor Ortiz Ramos, s\/n, Campus de Teatinos, 29071 M\u00e1laga, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7817-6442","authenticated-orcid":false,"given":"Enrique Nava","family":"Baro","sequence":"additional","affiliation":[{"name":"Departamento de Ingenier\u00eda de Comunicaciones, Universidad de Malaga, C\/Doctor Ortiz Ramos, s\/n, Campus de Teatinos, 29071 M\u00e1laga, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0995-1921","authenticated-orcid":false,"given":"Mariofanna","family":"Milanova","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Arkansas at Little Rock, 2801 South University Avenue, Little Rock, AR 72204, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4340-9602","authenticated-orcid":false,"given":"Bhawani Shankar","family":"Chowdhry","sequence":"additional","affiliation":[{"name":"National Centre for Robotics, Automation and Artificial Intelligence, Mehran University of Engineering and Technology (MUET), Jamshoro 76062, Pakistan"},{"name":"NCRA-CMS Lab, Mehran University of Engineering and Technology (MUET), Jamshoro 76062, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,12,22]]},"reference":[{"key":"ref_1","first-page":"79","article-title":"Road Defect Detection System Based on Deep Learning","volume":"2","author":"Lin","year":"2025","journal-title":"J. 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