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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.

As the Automotive Industry moves towards higher electronic functionality in vehicles, the volume of information transported is increasing at a rate that is surpassing the capability of standard copper wiring. In an effort to control the massive wiring required, the industry is moving into signal multiplexing approaches. However, multiplexing raises the data rates employed, which increase the requirements on the interconnect medium, and its price. Polymer Optical Fiber offers distinct advantages over the copper alternatives, in performance as well as economics. This paper will review standard and improved polymer optical fibers that address this very important market segment.