Fire Frontline Monitoring by Enabling UAV-Based Virtual Reality with Adaptive Imaging Rate
Fire Frontline Monitoring by Enabling UAV-Based Virtual Reality with Adaptive Imaging Rate
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DOI：
10.1109/ieeeconf44664.2019.9049048
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发表时间：
2019-11
期刊：
影响因子：
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通讯作者：
Shafkat Islam;Qiyuan Huang;F. Afghah;P. Fulé;Abolfazl Razi
中科院分区：
文献类型：
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作者：
Shafkat Islam;Qiyuan Huang;F. Afghah;P. Fulé;Abolfazl Razi
最近，使用无人机进行森林火灾管理由于其操作和部署成本低，灵活的移动性和高质量的成像等优点而受到研究界的广泛关注。它还最大限度地减少了人为干预，特别是在难以到达的地区，使用地面基础设施很麻烦。无人机可以通过按需收集具有可调缩放、聚焦和视角的高分辨率图像，为消防员提供虚拟现实，以改善消防控制并消除人为危险。在本文中，我们提出了一种新的模型，火灾扩展以及分布式算法的无人机重新定位自己的前线不断扩大的火灾领域。所提出的算法包括用于火灾边缘检测的轻量级图像处理，这对于资源受限的无人机来说是非常理想的计算昂贵的深度学习方法。该定位算法包括运动切线和垂直于火前线，以遵循火灾的扩展，同时保持最小的成对距离，避免碰撞和非重叠成像。我们提出了一种行动奖励机制，以调整无人机的速度和处理速度的基础上，火灾的扩展速度和可用的机载处理能力。仿真结果支持所提出的算法的有效性。
Recently, using drones for forest fire management has gained a lot of attention from the research community due to their advantages such as low operation and deployment cost, flexible mobility, and high-quality imaging. It also minimizes human intervention, especially in hard-to-reach areas where the use of ground-based infrastructure is troublesome. Drones can provide virtual reality to firefighters by collecting on-demand high-resolution images with adjustable zoom, focus, and perspective to improve fire control and eliminate human hazards. In this paper, we propose a novel model for fire expansion as well as a distributed algorithm for drones to relocate themselves towards the front-line of an expanding fire field. The proposed algorithm comprises a light-weight image processing for fire edge detection that is highly desirable over computational expensive deep learning methods for resource-constrained drones. The positioning algorithm includes motions tangential and normal to fire frontline to follow the fire expansion while keeping minimum pairwise distances for collision avoidance and non-overlapping imaging. We proposed an action-reward mechanism to adjust the drones’ speed and processing rate based on the fire expansion rate and the available onboard processing power. Simulations results are provided to support the efficacy of the proposed algorithm.