{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:40:06Z","timestamp":1760143206034,"version":"build-2065373602"},"reference-count":33,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2024,1,14]],"date-time":"2024-01-14T00:00:00Z","timestamp":1705190400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Smart Pavements Australia Research Collaboration (SPARC) Hub","award":["IH18.12.1","IH180100010"],"award-info":[{"award-number":["IH18.12.1","IH180100010"]}]},{"name":"Australian Research Council (ARC) Industrial Transformation Research Hub (ITRH) Scheme","award":["IH18.12.1","IH180100010"],"award-info":[{"award-number":["IH18.12.1","IH180100010"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Road dust is a mixture of fine and coarse particles released into the air due to an external force, such as tire\u2013ground friction or wind, which is harmful to human health when inhaled. Continuous dust emission from the road surfaces is detrimental to the road itself and the road users. Due to this, multiple dust monitoring and control techniques are currently adopted in the world. The current dust monitoring methods require expensive equipment and expertise. This study introduces a novel pragmatic and robust approach to quantifying traffic-induced road dust using a deep learning method called semantic segmentation. Based on the authors\u2019 previous works, the best-performing semantic segmentation machine learning models were selected and used to identify dust in an image pixel-wise. The total number of dust pixels was then correlated with real-world dust measurements obtained from a research-grade dust monitor. Our method shows that semantic segmentation can be adopted to quantify traffic-induced dust reasonably. Over 90% of the predictions from both correlations fall in true positive quadrant, indicating that when dust concentrations are below the threshold, the segmentation can accurately predict them. The results were validated and extended for real-time application. Our code implementation is publicly available.<\/jats:p>","DOI":"10.3390\/s24020510","type":"journal-article","created":{"date-parts":[[2024,1,15]],"date-time":"2024-01-15T07:25:07Z","timestamp":1705303507000},"page":"510","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Beyond Conventional Monitoring: A Semantic Segmentation Approach to Quantifying Traffic-Induced Dust on Unsealed Roads"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3050-1290","authenticated-orcid":false,"given":"Asanka","family":"de Silva","sequence":"first","affiliation":[{"name":"ARC Industrial Transformation Research Hub (ITRH)\u2014SPARC Hub, Department of Civil Engineering, Monash University, Clayton Campus, Clayton, VIC 3800, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6001-512X","authenticated-orcid":false,"given":"Rajitha","family":"Ranasinghe","sequence":"additional","affiliation":[{"name":"ARC Industrial Transformation Research Hub (ITRH)\u2014SPARC Hub, Department of Civil Engineering, Monash University, Clayton Campus, Clayton, VIC 3800, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0839-1045","authenticated-orcid":false,"given":"Arooran","family":"Sounthararajah","sequence":"additional","affiliation":[{"name":"ARC Industrial Transformation Research Hub (ITRH)\u2014SPARC Hub, Department of Civil Engineering, Monash University, Clayton Campus, Clayton, VIC 3800, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hamed","family":"Haghighi","sequence":"additional","affiliation":[{"name":"Product Development Hub, Road Science, Downer EDI Works Pty Ltd., Somerton, VIC 3061, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1725-7972","authenticated-orcid":false,"given":"Jayantha","family":"Kodikara","sequence":"additional","affiliation":[{"name":"ARC Industrial Transformation Research Hub (ITRH)\u2014SPARC Hub, Department of Civil Engineering, Monash University, Clayton Campus, Clayton, VIC 3800, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,1,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"e2018013","DOI":"10.4178\/epih.e2018013","article-title":"Road dust and its effect on human health: A literature review","volume":"40","author":"Khan","year":"2018","journal-title":"Epidemiol. 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