Recently, the usage of 360-degree videos has prevailed in various sectors such as education, real estate, medical, entertainment and more. The development of the Virtual World “Metaverse” demanded a Virtual Reality (VR) environment with high immersion and a smooth user experience. However, various challenges are faced to provide real-time streaming due to the nature of high-resolution 360-degree videos such as high bandwidth requirement, high computing power and low delay tolerance. To overcome these challenges, streaming methods such as Dynamic Adaptive Streaming over HTTP (DASH), Tiling, Viewport-Adaptive and Machine Learning (ML) are discussed. Moreover, the superiorities of the development of 5G and 6G networks, Mobile Edge Computing (MEC) and Caching and the Information-Centric Network (ICN) approaches to optimize the 360-degree video streaming are elaborated. All of these methods strike to improve the Quality of Experience (QoE) and Quality of Service (QoS) of VR services. Next, the challenges faced in QoE modeling and the existing objective and subjective QoE assessment methods of 360-degree video are presented. Lastly, potential future research that utilizes and further improves the existing methods substantially is discussed. With the efforts of various research studies and industries and the gradual development of the network in recent years, a deep fake virtual world, “Metaverse” with high immersion and conducive for daily life working, learning and socializing are around the corner.
Water, mostly oceans, covers over two-third of the earth. About 95% of these oceans are yet to be explored which includes 99% of the sea-beds. The introduction of the Internet of Underwater Things (IoUT) underwater has become a powerful technology necessary to the quest to develop a SMART Ocean. Autonomous Underwater Vehicles (AUVs) play a crucial role in this technology because of their mobility and longer energy storage. In order for AUV technologies to be effective, the challenges of AUVs must be adequately solved. This paper provides an overview of the challenges of IoUT, the contributions of AUVs in IoUT as well as the current challenges and opening in AUV. A summary and suggestion for future work was discussed.
Number of accidents caused by microsleep increases rapidly each day. This is due to the current trend of life, for example high workload, long working hours, traffic jams, having too much caffeine, drinking alcohol, age factor, and many others. This microsleep can lead to major accidents, higher number of deaths, injuries, demolition of property and permanent disability. The creation of SMART Vehicles in the Internet of Things (IoT) increases the technology capabilities in transportation sectors, in addition to reduce the number of crashes on the roads. An integration with Artificial Intelligent (AI) can be a perfect combination on development of a microsleep detection and prevention. While the image processing will be used as the method of detecting the face changes from normal to microsleep symptoms on detecting the eye degree, the head motion and the mouth yawning. This work presented a review of current research that supported the integration of IoT and AI. The analysis and discussion on the best solution and method to prevent microsleep accidents was shown. Lastly, recommendation on development of real sensors for SMART Vehicles will be discussed. A preliminary result on this work also will be shown.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.