Date of Award

Spring 5-9-2024

Degree Type


Degree Name

Doctor of Philosophy in Interdisciplinary Engineering - Smart Infrastructure


Southern Polytechnic College of Engineering and Engineering Technology

Committee Chair/First Advisor

Dr. Billy Kihei


This research explored the challenges of multimedia transmission within Dedicated Short-Range Communication (DSRC) Vehicular Ad Hoc Networks (VANETs) and introduced a novel compression technique. This technique addressed transmission bandwidth challenges while capitalizing on available opportunities. The primary goal was to ensure a requisite packet reception rate (PRR), overcoming transmission challenges and facilitating efficient audio-visual data transmission and delivery. A novel compression technique was introduced called ”Adapti-WAVE(Wireless Access in Vehicular Environment) Compression.” The novel technique combines the Discrete Wavelet Transform Low-Low subband (DWT-LL) with Singular Value Decomposition (SVD), while Linear Programming (LP) dynamically adjusts singular values, aligning the compression process with vehicle density thresholds. This technique achieved remarkable compression ratios of 47%, preserving critical image features while dynamically adapting to vehicle density variation without compromising essential safety messages like Basic Safety Messages (BSM). The outcome of this research highlights the superiority of the combined DWT-LL, SVD, and LP approaches, exhibiting exceptional performance in maintaining image quality across various compression levels. The results showcased a high Peak Signal-to-Noise Ratio (PSNR), low Mean Squared Error (MSE), and elevated Structural Similarity Index Measure (SSIM) values in comparison to the contemporary Discrete Cosine Transform (DCT) technique that is mostly used in image compression. This novel approach proved to be well-suited for the transmission of audio-visual data despite the transmission bandwidth challenges in DSRC VANET without sacrificing image quality. This research contributes a refined image compression system tailored for DSRC VANETs, with a particular focus on enhancing applications for public emergency notifications

Available for download on Monday, February 15, 2027