Data Processing and Fusion For Multi-Source Wireless Systems

The constant evolution of the telecommunication technologies is one fundamental aspect that characterizes the modern era. In the context of healthcare and security, different scenarios are characterized by the presence of multiple sources of information that can support a large number of innovative services. For example, in emergency scenarios, reliable transmission of heterogeneous information (health conditions, ambient and diagnostic videos) can be a valid support for managing the first-aid operations. The presence of multiple sources of information requires a careful communication management, especially in case of limited transmission resource availability. The objective of my Ph.D. activity is to develop new optimization techniques for multimedia communications, considering emergency scenarios characterized by wireless connectivity. Different criteria are defined in order to prioritize the available heterogeneous information before transmission. The proposed solutions are based on the modern concept of content/context awareness: the transmission parameters are optimized taking into account the informative content of the data and the general context in which the information sources are located. To this purpose, novel cross-layer adaptation strategies are proposed for multiple SVC videos delivered over wireless channel. The objective is to optimize the resource allocation dynamically adjusting the overall transmitted throughput to meet the actual available bandwidth. After introducing a realistic camera network, some numerical results obtained with the proposed techniques are showed. In addition, through numerical simulations the benefits are showed, in terms of QoE, introduced by the proposed adaptive aggregation and transmission strategies applied in the context of emergency scenarios. The proposed solution is fully integrated in European research activities, including the FP7 ICT project CONCERTO. To implement, validate and demonstrate the functionalities of the proposed solutions, extensive transmission simulation campaigns are performed. Hence, the presented solutions are integrated on a common system simulator which is been developed within the CONCERTO project

Network-assisted Smart Access Point Selection for Pervasive Real-time mHealth Applications

AbstractDue to the fast evolution of wireless access networks and high-performance mobile devices together with the spreading of wearable medical sensors, electronic healthcare (eHealth) services have recently started to receive more and more attention, especially in the mobile Health (mHealth) domain. The vast majority of mHealth services require strict medical level Quality of Service (QoS) and Quality of Experience (QoE) provision. Emergency use-cases, remote patient monitoring, tele-consultation and guided surgical intervention require real-time communication and appropriate connection quality. The increasing significance of different overlapping wireless accesses makes possible to provide the required network resources for ubiquitous and pervasive mHealth applications. Aiming to support such use-cases in a heterogeneous network environment, we propose a network-assisted intelligent access point selection scheme for ubiquitous applications of Future Internet architectures focusing on real-time mobile telemedicine services. Our solution is able to discover nearby base stations that cover the current location of the mobile device efficiently and to trigger heterogeneous handovers based on the state and quality of the current access network. The solution is empirically evaluated in Wi-Fi networks used by real-life Android mobile devices and we observed that the scheme can improve the quality of mHealth applications and enhance traffic load balancing capabilities of wireless architectures

2007-2008 Lynn University Academic Catalog

https://spiral.lynn.edu/accatalogs/1028/thumbnail.jp

Content-aware packet scheduling strategy for medical ultrasound videos over LTE wireless networks

In parallel to the advancements in communication technologies, telemedicine research has continually adapted to develop various healthcare applications. The latest wireless technology Long-Term Evolution(LTE) is being increasingly deployed across developed countries and rapidly adopted by developing countries. In this paper, a content-aware packet scheduling approach for medical ultrasound videos is proposed. The contribution of this work is introducing a utility function based on the temporal complexity of the video frames. The utility function is used with four schedulers to prioritise the video packets based on their temporal complexity and type of frame (e.g. I frame). The results show that the utility function improves the packet delay performance obtained in our simulation when compared with content-unaware approach. Further, gain in average PSNR and SSIM are also observed in the received video quality. Research on content-aware packet scheduling for telemedicine applications over advanced wireless networks is limited and our work contributes towards addressing this research gap

Emergency Accident Alert

The escalation of the fatalities of road user has triggered a serious concern in the country. Factors identified were communication problem between the caller and the call-taker cause delay in the process of saving the victim which then become a source for insufficient preparation at the hospital. By utilising the knowledge of the current evolving technology which is now a trend, the author suggests to develop a mobile application that encourages bystander and eyewitness of road accident to immediately send details of victim’s condition to the emergency operator. The method used for the development of this Emergency Accident Alert is the Rapid Application Development (RAD) model. A prototype that describes the functionalities of the system will be developed using Phonegap that blends in HTML, CSS, Javascript and Jquery (scripting languages) to produce the desired mobile applicatio

2013-2014 Lynn University Academic Catalog

https://spiral.lynn.edu/accatalogs/1034/thumbnail.jp

2009-2010 Lynn University Academic Catalog

https://spiral.lynn.edu/accatalogs/1030/thumbnail.jp

Confronting the COVID-19 pandemic: grief, loss, and social order

This research addresses the challenge the 2019- 2020 COVID-19 pandemic (COVID-19) presents to social order as a result of mass grieving and loss. It places a particular emphasis on the UK response and lessons that can be learnt for further ‘waves’. A tendency for research to look at technocratic policy responses has led to the overlooking of the social impact that pandemics produce. This study, in contrast, employs a qualitative, comparative methodology to examine four key cases – the UK, Italy, South Korea, and Germany – from 1 January to 31 July 2020, as well as the UK during the 1918-19 influenza epidemic – to examine the politics of COVID-9 as a mass death event. Our research finds that the narrative framing of the pandemic as a particular type of crisis; the ways that deaths have been recorded and managed; and the manner in which loss has been mourned and commemorated vary across cases. This variance, the research suggests, has implications for the ways that societies may respond, particularly in the medium- and longterm. Recommendations are made for governments responding to future ‘waves’ of the virus in relation to communicating loss to the public, and commemorating deaths in a manner that supports social cohesion and prepares the public for future crises

2014-2015 Lynn University Academic Catalog

https://spiral.lynn.edu/accatalogs/1035/thumbnail.jp