In many parts of the world, uncontrolled fires in sparsely populated areas are a major concern as they can quickly grow into large and destructive conflagrations in short time spans. Detecting these fires has traditionally been a job for trained humans on the ground, or in the air. In many cases, these manned solutions are simply not able to survey the amount of area necessary to maintain sufficient vigilance and coverage. This paper investigates the use of unmanned aerial systems (UAS) for automated wildfire detection. The proposed system uses low-cost, consumer-grade electronics and sensors combined with various airframes to create a system suitable for automatic detection of wildfires. The system employs automatic image processing techniques to analyze captured images and autonomously detect fire-related features such as fire lines, burnt regions, and flammable material. This image recognition algorithm is designed to cope with environmental occlusions such as shadows, smoke and obstructions. Once the fire is identified and classified, it is used to initialize a spatial/temporal fire simulation. This simulation is based on occupancy maps whose fidelity can be varied to include stochastic elements, various types of vegetation, weather conditions, and unique terrain. The simulations can be used to predict the effects of optimized firefighting methods to prevent the future propagation of the fires and greatly reduce time to detection of wildfires, thereby greatly minimizing the ensuing damage. This paper also documents experimental flight tests using a SenseFly Swinglet UAS conducted in Brisbane, Australia as well as modifications for custom UAS.
A laser multibeam differential interferometric sensor (LAMBDIS) was developed that provides measurement of vibration fields of objects with high sensitivity, while having low sensitivity to the whole-body motion of the object, or the sensor itself. The principle of operation of the LAMBDIS is based on the interference of light reflected from different points on the object surface illuminated with a linear array of laser beams. The Doppler shift induced by the sensor motion is approximately the same for all beams and is automatically subtracted from the measurements. The performance of the sensor for laser-acoustic detection of a buried object was experimentally investigated. The ability of LAMBDIS to detect buried objects from a moving vehicle has been demonstrated in field experiments.
A Laser Multi-Beam Differential Interferometric Sensor (LAMBDIS) for measuring vibration fields has been developed that alleviates one of the major issues of traditional laser Doppler vibrometers: effect on measurements by motion of the vibrometer itself. The LAMBDIS simultaneously measures Doppler shifts of light reflected from different points on the object surface illuminated with a linear array of laser beams. As a result, the LAMBDIS measures relative velocities between points on an object surface, while the Doppler shift caused by the sensor motion is approximately the same for all beams and is automatically subtracted from the measurements. This allows measurements of vibration fields of objects with high sensitivity from a moving platform. Scanning the linear array of laser beams in the transverse direction provides a two-dimensional vibration image of the surface. Performance of the sensor for ground vibration sensing for acoustic detection of buried objects has been investigated in the laboratory and field experiments. The sensor proved effective at detecting buried objects from a moving vehicle. [Work supported by the Office of Naval Research.]
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