{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,3]],"date-time":"2026-08-03T12:47:05Z","timestamp":1785761225393,"version":"3.56.0"},"reference-count":27,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004735","name":"Natural Science Foundation of Hunan Province","doi-asserted-by":"publisher","award":["2025JJ70121"],"award-info":[{"award-number":["2025JJ70121"]}],"id":[{"id":"10.13039\/501100004735","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Pontosense Inc."}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Termite infestation poses a critical threat to ancient timber structures because hidden in-wood activity can cause progressive structural decay before visible surface symptoms appear. Through-wood termite detection remains challenging because termite-induced electromagnetic responses are weak, small-scale, and vulnerable to timber attenuation and multipath propagation. To address this problem, this study presents one of the first investigations to formulate through-wood termite detection as a multi-frequency wireless sensing and image\u2013wireless fusion problem for non-destructive heritage timber inspection. We propose a Reliability-Aware Image\u2013Wireless Fusion Network (RA-IWFNet), in which the image branch captures high-resolution surface-level visual cues while the dual-band wireless branch integrates complementary mmWave radar micro-motion responses and Wi-Fi Channel State Information (CSI) channel variations. A learnable temperature-scaled fusion gate estimates input-dependent image and wireless contributions and constructs a normalized fused representation for four-class recognition, including Termite, Lyctidae, Human, and None. Here, reliability is operationally defined as learned input-adaptive relative modality contribution rather than explicit uncertainty or signal-quality estimation. RA-IWFNet is evaluated under two complementary protocols: a field-motivated protocol with joint visual and wireless degradation and a synchronized verification protocol using physically co-acquired multimodal samples. Across repeated training runs, RA-IWFNet achieves 81.91\u00b11.33% accuracy and 81.96\u00b11.27% Macro-F1 under field-mixed visual degradation and moderate wireless degradation. On the synchronized verification subset, gated fusion achieves 91.53\u00b12.44% accuracy and 91.62\u00b12.44% Macro-F1, yielding higher mean performance than single-modality and non-adaptive fusion baselines. Feature-space, error-correction, and gate-temperature analyses further support the effectiveness of adaptive modality integration. These results provide controlled laboratory feasibility evidence and suggest that multi-frequency wireless sensing combined with adaptive image\u2013wireless fusion offers a promising non-invasive pathway toward practical through-wood termite inspection in heritage timber structures.<\/jats:p>","DOI":"10.3390\/s26154859","type":"journal-article","created":{"date-parts":[[2026,8,3]],"date-time":"2026-08-03T11:50:21Z","timestamp":1785757821000},"page":"4859","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Reliability-Aware Image\u2013Wireless Fusion for Through-Wood Termite Detection"],"prefix":"10.3390","volume":"26","author":[{"given":"Wei","family":"Zhang","sequence":"first","affiliation":[{"name":"College of Computer Science and Engineering, Changsha University, Changsha 410022, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiangshu","family":"Qi","sequence":"additional","affiliation":[{"name":"Graduate School of Computer and Information Sciences, Hosei University, Tokyo 102-8160, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qinglong","family":"Tian","sequence":"additional","affiliation":[{"name":"College of Computer Science and Engineering, Changsha University, Changsha 410022, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ziqian","family":"Ling","sequence":"additional","affiliation":[{"name":"College of Computer Science and Engineering, Changsha University, Changsha 410022, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yi","family":"Cao","sequence":"additional","affiliation":[{"name":"College of Computer Science and Engineering, Changsha University, Changsha 410022, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Youxi","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Computer Science and Engineering, Changsha University, Changsha 410022, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alex","family":"Qi","sequence":"additional","affiliation":[{"name":"Pontosense Inc., Kitchener, ON N2H 5G5, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,8,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"101368","DOI":"10.1016\/j.cois.2025.101368","article-title":"Invasive termites and their growing global impact as major urban pests","volume":"69","author":"Chouvenc","year":"2025","journal-title":"Curr. 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