Fighting Pandemics with Augmented Reality and Smart Sensing-based Social Distancing

In a postpandemic world, remaining vigilant and maintaining social distancing are still crucial so societies can contain the virus and the public can avoid disproportionate health impacts. Augmented reality (AR) can visually assist users in understanding the distances in social distancing. However, integrating external sensing and analysis is required for social distancing beyond the users’ local environment. We present DistAR, an android-based application for social distancing leveraging AR and smart sensing using on-device analysis of optical images and environment crowdedness from smart campus data. Our prototype is one of the first efforts to combine AR and smart sensing technologies to create a real-time social distancing application.Peer reviewe

Mobile Augmented Reality: User Interfaces, Frameworks, and Intelligence

Mobile Augmented Reality (MAR) integrates computer-generated virtual objects with physical environments for mobile devices. MAR systems enable users to interact with MAR devices, such as smartphones and head-worn wearables, and perform seamless transitions from the physical world to a mixed world with digital entities. These MAR systems support user experiences using MAR devices to provide universal access to digital content. Over the past 20 years, several MAR systems have been developed, however, the studies and design of MAR frameworks have not yet been systematically reviewed from the perspective of user-centric design. This article presents the first effort of surveying existing MAR frameworks (count: 37) and further discuss the latest studies on MAR through a top-down approach: (1) MAR applications; (2) MAR visualisation techniques adaptive to user mobility and contexts; (3) systematic evaluation of MAR frameworks, including supported platforms and corresponding features such as tracking, feature extraction, and sensing capabilities; and (4) underlying machine learning approaches supporting intelligent operations within MAR systems. Finally, we summarise the development of emerging research fields and the current state-of-the-art, and discuss the important open challenges and possible theoretical and technical directions. This survey aims to benefit both researchers and MAR system developers alike.Peer reviewe

Edge Computing: The Computing Infrastructure for the Smart Mega-cities of the Future

Future mega-cities are expected to be smart and integrate sensing, wireless communications, and artificial intelligence to offer innovative services to their citizens. This development has the potential to generate massive amounts of data which need to be processed in a cost-effective, scalable, and continuous manner. Fulfilling this requirement requires solutions that can offer the necessary computational infrastructure while meeting the constraints of cities (e.g., budget and energy). This paper contributes a research vision for using edge computing to deliver the computing infrastructure for emerging smart mega-cities. We present use cases, identify key requirements, and reflect on the current state-of-the-art. We also address edge server placements, which is a key challenge for the adoption of edge computing, demonstrating how it is needed to determine a scalable and effective deployment of edge nodes for satisfying the processing needs of smart mega-cities.Peer reviewe

Intelligent and Scalable Air Quality Monitoring with 5G Edge

Air pollution introduces a major challenge for societies, where it leads to the premature deaths of millions of people each year globally. Massive deployment of air quality sensing devices and data analysis for the resultant data will pave the way for the development of real-time intelligent applications and services, e.g., minimization of exposure to poor air quality either on an individual or city scale. 5G and edge computing supports dense deployments of sensors at high resolution with ubiquitous connectivity, high bandwidth, high-speed gigabit connections, and ultralow latency analysis. This article conceptualizes AI-powered scalable air quality monitoring and presents two systems of calibrating low-cost air quality sensors and the image processing of pictures captured by hyperspectral cameras to better detect air quality. We develop and deploy different AI algorithms in these two systems on a 5G edge testbed and perform a detailed analytics regarding to 1) the performance of AI algorithms and 2) the required communication and computation resources.Peer reviewe

RNAi-Mediated Knock-Down of Arylamine N-acetyltransferase-1 Expression Induces E-cadherin Up-Regulation and Cell-Cell Contact Growth Inhibition

Arylamine N-acetyltransferase-1 (NAT1) is an enzyme that catalyzes the biotransformation of arylamine and hydrazine substrates. It also has a role in the catabolism of the folate metabolite p-aminobenzoyl glutamate. Recent bioinformatics studies have correlated NAT1 expression with various cancer subtypes. However, a direct role for NAT1 in cell biology has not been established. In this study, we have knocked down NAT1 in the colon adenocarcinoma cell-line HT-29 and found a marked change in cell morphology that was accompanied by an increase in cell-cell contact growth inhibition and a loss of cell viability at confluence. NAT1 knock-down also led to attenuation in anchorage independent growth in soft agar. Loss of NAT1 led to the up-regulation of E-cadherin mRNA and protein levels. This change in E-cadherin was not attributed to RNAi off-target effects and was also observed in the prostate cancer cell-line 22Rv1. In vivo, NAT1 knock-down cells grew with a longer doubling time compared to cells stably transfected with a scrambled RNAi or to parental HT-29 cells. This study has shown that NAT1 affects cell growth and morphology. In addition, it suggests that NAT1 may be a novel drug target for cancer therapeutics

5G edge computing enhanced mobile augmented reality

Abstract Physical world enhancements through virtually drawn annotations on mobile devices are a core component of mobile augmented reality (MAR) experiences. However, resource intensive computer vision tasks typically limit the full deployment of MAR pipelines on-device due to a lack of required computation resources. As an alternative, a distributed scheme between client devices and edge servers enables offloading computation intensive tasks to powerful machines. This introduces challenges, such as maintaining low communication latency and high bandwidth channels between client and edge server. Current LTE and WiFi infrastructure do not fulfil such requirements. 5G networks are an ideal candidate to provide seamless MAR experiences. This research investigates the enhancement of MAR with both 5G and edge computing and aims to address two particular challenges: 1) the creation of a new 5G-based edge computing infrastructure to support reliable MAR, and 2) investigating which particular transport protocols allow for optimised quality of experience (QoE) for MAR applications within 5G infrastructure

Mpeg-2 to wmv transcoder with adaptive error compensation and dynamic switches

Abstract—In this paper, we study the problem of vide