Ahmed Abdelgawad

This book introduces a novel transcoding algorithm for real time video applications, designed to overcome inter-operability problems between MPEG-2 to H.264/AVC. The new algorithm achieves 92.8% reduction in the transcoding run time at a price of an acceptable Peak Signal-to-Noise Ratio (PSNR) degradation, enabling readers to use it for real time video applications. The algorithm described is evaluated through simulation and experimental results. In addition, the authors present a hardware implementation of the new algorithm using Field Programmable Gate Array (FPGA) and Application-specific standard products (ASIC).• Describes a novel transcoding algorithm for real time video applications, designed to overcome inter-operability problems between H.264/AVC to MPEG-2; • Implements algorithm presented using Field Programmable Gate Array (FPGA) and Application-specific Integrated Circuit (ASIC);• Demonstrates the solution to real problems, with verification through simulation and experimental results.

This book introduces resource-aware data fusion algorithms to gather and combine data from multiple sources (e.g., sensors) in order to achieve inferences. These techniques can be used in centralized and distributed systems to overcome sensor failure, technological limitation, and spatial and temporal coverage problems. The algorithms described in this book are evaluated with simulation and experimental results to show they will maintain data integrity and make data useful and informative. Describes techniques to overcome real problems posed by wireless sensor networks deployed in circumstances that might interfere with measurements provided, such as strong variations of pressure, temperature, radiation, and electromagnetic noise; Uses simulation and experimental results to evaluate algorithms presented and includes real test-bed; Includes case study implementing data fusion algorithms on a remote monitoring framework for sand production in oil pipelines.

This book introduces resource-aware data fusion algorithms to gather and combine data from multiple sources (e.g., sensors) in order to achieve inferences. These techniques can be used in centralized and distributed systems to overcome sensor failure, technological limitation, and spatial and temporal coverage problems. The algorithms described in this book are evaluated with simulation and experimental results to show they will maintain data integrity and make data useful and informative. Describes techniques to overcome real problems posed by wireless sensor networks deployed in circumstances that might interfere with measurements provided, such as strong variations of pressure, temperature, radiation, and electromagnetic noise; Uses simulation and experimental results to evaluate algorithms presented and includes real test-bed; Includes case study implementing data fusion algorithms on a remote monitoring framework for sand production in oil pipelines.