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- 摘要
- 关键词
- 实验方案
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Camera sensor-based contamination detection for water environment monitoring
摘要： Water environment monitoring is of great importance to human health, ecosystem sustainability, and water transport. Unlike traditional water quality monitoring problems, this paper focuses on visual perception of water environment. We first introduce the development of a customized aquatic sensor node equipped with an embedded camera sensor. Based on this platform, we present an efficient and holistic contamination detection approach, which can automatically adapt to the detection of floating debris in dynamic waters or the identification of salient regions in static waters. Our approach is specifically designed based on compressed sensing theory to give full consideration to the unique challenges in water environment and the resource constraints on sensor nodes. Both laboratory and field experiments demonstrate the proposed method can fast and accurately detect various types of water pollutants and is a better choice for camera sensor-based water environment monitoring compared with other methods.
关键词： Contamination detection,Camera sensor,Compressed sensing,Environmental monitoring
更新于2025-09-23 15:21:21
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A Lightweight Leddar Optical Fusion Scanning System (FSS) for Canopy Foliage Monitoring
摘要： A growing need for sampling environmental spaces in high detail is driving the rapid development of non-destructive three-dimensional (3D) sensing technologies. LiDAR sensors, capable of precise 3D measurement at various scales from indoor to landscape, still lack affordable and portable products for broad-scale and multi-temporal monitoring. This study aims to configure a compact and low-cost 3D fusion scanning system (FSS) with a multi-segment Leddar (light emitting diode detection and ranging, LeddarTech), a monocular camera, and rotational robotics to recover hemispherical, colored point clouds. This includes an entire framework of calibration and fusion algorithms utilizing Leddar depth measurements and image parallax information. The FSS was applied to scan a cottonwood (Populus spp.) stand repeatedly during autumnal leaf drop. Results show that the calibration error based on bundle adjustment is between 1 and 3 pixels. The FSS scans exhibit a similar canopy volume profile to the benchmarking terrestrial laser scans, with an r2 between 0.5 and 0.7 in varying stages of leaf cover. The 3D point distribution information from FSS also provides a valuable correction factor for the leaf area index (LAI) estimation. The consistency of corrected LAI measurement demonstrates the practical value of deploying FSS for canopy foliage monitoring.
关键词： terrestrial laser scanning,canopy monitoring,monocular camera,sensor fusion,LiDAR,Leddar,structure from motion,leaf area index
更新于2025-09-12 10:27:22