arXiv:2607. 06999v1 Announce Type: cross Abstract: This paper presents a physics-guided machine learning (PGML) framework for fuel density prediction, integrating physics constraints and domain knowledge into deep learning models to enhance model accuracy and stability.
By Tolga Caglar, Jaynil Jaiswal, Saqib Azim, Yudhir Gala, Mai H. Nguyen, Ilkay Altintas
The paper introduces a simulation‑grounded vision‑language model (VLM) framework for wildfire monitoring that converts 2D wildfire simulations into labeled video episodes using a fixed Blender mapping to create low‑detail 3D proxies. These proxies, along with controllable video generation, provide a multimodal memory that a training‑free multi‑agent VLM system uses to retrieve reference episodes, reconcile visual and memory‑based predictions, and generate structured wildfire reports. The system achieves 77.3% accuracy on six simulator‑derived report fields, outperforming direct VLM querying and text‑only memory baselines.
By Duowen Chen, Yuchen Sun, Zhiqi Li, Yuxuan Liao, Sinan Wang, Bart van Bloemen Waanders, Bo Zhu
arXiv:2606. 07416v1 Announce Type: new Abstract: Atmospheric plasma spraying (APS) is a widely used coating process in which in-flight particle temperature and velocity strongly influence coating quality.
By Abhijeet Praveen, Sareh Soleimani, Cormac Cureton, Aman Sidhu, Kintak Raymond Yu, Cristian Cojocaru, Narges Armanfard
arXiv:2606.10174v2 Announce Type: replace
Abstract: Wildfire detection and monitoring are critical for mitigating fire spread and reducing environmental and infrastructural damage. In this work, we i...
By Emadeldeen Hamdan, Yingyi Luo, B. Ugur Toreyin, Erdem Koyuncu, Adam J. Watts, Ugur Gudukbay, Ahmet Enis Cetin
arXiv:2412. 02831v2 Announce Type: replace-cross Abstract: The increasing accessibility of radiometric thermal imaging sensors for unmanned aerial vehicles (UAVs) offers significant potential for advancing AI-driven aerial wildfire management.
By Bryce Hopkins, Leo ONeill, Michael Marinaccio, Mobin Habibpour, Eric Rowell, Russell Parsons, Sarah Flanary, Irtija Nazim, Carl Seielstad, Fatemeh Afghah
arXiv:2508.19485v2 Announce Type: replace
Abstract: Gas leaks pose severe risks to human health and industrial safety. However, accurate and timely monitoring of gas leaks remains a major challenge....
By Xinlong Zhao, Qixiang Pang, Shan Du