{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,20]],"date-time":"2026-05-20T15:27:51Z","timestamp":1779290871334,"version":"3.51.4"},"reference-count":47,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2025,9,19]],"date-time":"2025-09-19T00:00:00Z","timestamp":1758240000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["42301509"],"award-info":[{"award-number":["42301509"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2025T180082"],"award-info":[{"award-number":["2025T180082"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2024M761474"],"award-info":[{"award-number":["2024M761474"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["KYCX25_2107"],"award-info":[{"award-number":["KYCX25_2107"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"China Postdoctoral Science Foundation","award":["42301509"],"award-info":[{"award-number":["42301509"]}]},{"name":"China Postdoctoral Science Foundation","award":["2025T180082"],"award-info":[{"award-number":["2025T180082"]}]},{"name":"China Postdoctoral Science Foundation","award":["2024M761474"],"award-info":[{"award-number":["2024M761474"]}]},{"name":"China Postdoctoral Science Foundation","award":["KYCX25_2107"],"award-info":[{"award-number":["KYCX25_2107"]}]},{"name":"Postgraduate Research &amp; Practice Innovation Program of Jiangsu Province","award":["42301509"],"award-info":[{"award-number":["42301509"]}]},{"name":"Postgraduate Research &amp; Practice Innovation Program of Jiangsu Province","award":["2025T180082"],"award-info":[{"award-number":["2025T180082"]}]},{"name":"Postgraduate Research &amp; Practice Innovation Program of Jiangsu Province","award":["2024M761474"],"award-info":[{"award-number":["2024M761474"]}]},{"name":"Postgraduate Research &amp; Practice Innovation Program of Jiangsu Province","award":["KYCX25_2107"],"award-info":[{"award-number":["KYCX25_2107"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Precise object detection is fundamental to robust indoor navigation and localization. However, the practical deployment of deep learning-based detectors on mobile platforms is frequently impeded by their extensive parameter counts, substantial computational overhead, and prolonged inference latency, rendering them impractical for real-time and GPU-independent applications. To overcome these limitations, this paper presents Nav-YOLO, a highly optimized and lightweight architecture derived from YOLOv8n, specifically engineered for navigational tasks. The model\u2019s efficiency stems from several key improvements: a ShuffleNetv2-based backbone significantly reduces model parameters; a Slim-Neck structure incorporating GSConv and GSbottleneck modules streamlines the feature fusion process; the VoV-GSCSP hierarchical network aggregates features with minimal computational cost; and a compact detection head is designed using Hybrid Convolutional Transformer Architecture Search (HyCTAS). Furthermore, the adoption of Inner-IoU as the bounding box regression loss accelerates the convergence of the training process. The model\u2019s efficacy is demonstrated through a purpose-built Android application. Experimental evaluations on the VOC2007 and VOC2012 datasets reveal that Nav-YOLO substantially outperforms the baseline YOLOv8n, achieving mAP50 improvements of 10.3% and 5.0%, respectively, while maintaining a comparable parameter footprint. Consequently, Nav-YOLO demonstrates a superior balance of accuracy, model compactness, and inference speed, presenting a compelling alternative to existing object detection algorithms for mobile systems.<\/jats:p>","DOI":"10.3390\/ijgi14090364","type":"journal-article","created":{"date-parts":[[2025,9,19]],"date-time":"2025-09-19T12:33:32Z","timestamp":1758285212000},"page":"364","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Nav-YOLO: A Lightweight and Efficient Object Detection Model for Real-Time Indoor Navigation on Mobile Platforms"],"prefix":"10.3390","volume":"14","author":[{"given":"Cheng","family":"Su","sequence":"first","affiliation":[{"name":"School of Computer and Artificial Intelligence, Nanjing University of Finance and Economics, Nanjing 210023, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Litao","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Computer and Artificial Intelligence, Nanjing University of Finance and Economics, Nanjing 210023, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wen","family":"Dai","sequence":"additional","affiliation":[{"name":"School of Geographical Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jin","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Computer and Artificial Intelligence, Nanjing University of Finance and Economics, Nanjing 210023, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jialiang","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computer and Artificial Intelligence, Nanjing University of Finance and Economics, Nanjing 210023, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yucheng","family":"Mao","sequence":"additional","affiliation":[{"name":"School of Computer and Artificial Intelligence, Nanjing University of Finance and Economics, Nanjing 210023, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiangbing","family":"Sun","sequence":"additional","affiliation":[{"name":"School of Earth Science and Engineering, Hohai University, Nanjing 210023, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,9,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Alahmadi, T.J., Rahman, A.U., Alkahtani, H.K., and Kholidy, H. 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