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"Al-Turjman, Fadi"
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Smart things & femtocells : from hype to reality
This book provides a comprehensive overview for the use of femtocells in smart Internet of Things (IoT) environments. Femtocells will help mobile operators to provide a basis for the next generation of services which are a combination of voice, video, and data services to mobile users. This book discusses modelling traffic and deployment strategies in femtocells and provides a review for the use of femtocells and their applications in IoT environments. Moreover, it highlights the efficient real-time medium access, data delivery, caching and security aspects in smart spaces. It concludes by presenting open research issues associated with smart IoT-femtocell based applications-- Provided by publisher.
Book
Value-Based Caching in Information-Centric Wireless Body Area Networks
We propose a resilient cache replacement approach based on a Value of sensed Information (VoI) policy. To resolve and fetch content when the origin is not available due to isolated in-network nodes (fragmentation) and harsh operational conditions, we exploit a content caching approach. Our approach depends on four functional parameters in sensory Wireless Body Area Networks (WBANs). These four parameters are: age of data based on periodic request, popularity of on-demand requests, communication interference cost, and the duration for which the sensor node is required to operate in active mode to capture the sensed readings. These parameters are considered together to assign a value to the cached data to retain the most valuable information in the cache for prolonged time periods. The higher the value, the longer the duration for which the data will be retained in the cache. This caching strategy provides significant availability for most valuable and difficult to retrieve data in the WBANs. Extensive simulations are performed to compare the proposed scheme against other significant caching schemes in the literature while varying critical aspects in WBANs (e.g., data popularity, cache size, publisher load, connectivity-degree, and severe probabilities of node failures). These simulation results indicate that the proposed VoI-based approach is a valid tool for the retrieval of cached content in disruptive and challenging scenarios, such as the one experienced in WBANs, since it allows the retrieval of content for a long period even while experiencing severe in-network node failures.
Journal Article
Internet of nano-things and wireless body area networks (WBAN)
\"The Internet of Nano-Things (IoNT) is a system of nano-connected devices, objects, or organisms that have unique identifiers to transfer data over a computer or cellular network wirelessly to the Cloud. The book covers data routing and energy consumption challenges and proposes nano-sensing platforms in critical Wireless Body Area Networks (WBAN)\"-- Provided by publisher.
Book
Smart Graphene-Based Electrochemical Nanobiosensor for Clinical Diagnosis: Review
The technological improvement in the field of physics, chemistry, electronics, nanotechnology, biology, and molecular biology has contributed to the development of various electrochemical biosensors with a broad range of applications in healthcare settings, food control and monitoring, and environmental monitoring. In the past, conventional biosensors that have employed bioreceptors, such as enzymes, antibodies, Nucleic Acid (NA), etc., and used different transduction methods such as optical, thermal, electrochemical, electrical and magnetic detection, have been developed. Yet, with all the progresses made so far, these biosensors are clouded with many challenges, such as interference with undesirable compound, low sensitivity, specificity, selectivity, and longer processing time. In order to address these challenges, there is high need for developing novel, fast, highly sensitive biosensors with high accuracy and specificity. Scientists explore these gaps by incorporating nanoparticles (NPs) and nanocomposites (NCs) to enhance the desired properties. Graphene nanostructures have emerged as one of the ideal materials for biosensing technology due to their excellent dispersity, ease of functionalization, physiochemical properties, optical properties, good electrical conductivity, etc. The Integration of the Internet of Medical Things (IoMT) in the development of biosensors has the potential to improve diagnosis and treatment of diseases through early diagnosis and on time monitoring. The outcome of this comprehensive review will be useful to understand the significant role of graphene-based electrochemical biosensor integrated with Artificial Intelligence AI and IoMT for clinical diagnostics. The review is further extended to cover open research issues and future aspects of biosensing technology for diagnosis and management of clinical diseases and performance evaluation based on Linear Range (LR) and Limit of Detection (LOD) within the ranges of Micromolar µM (10−6), Nanomolar nM (10−9), Picomolar pM (10−12), femtomolar fM (10−15), and attomolar aM (10−18).
Journal Article
Artificial intelligence of health-enabled spaces
\"Artificial Intelligence of Health-Enabled Spaces (AIoH) has made revolutionary advances in clinical studies that we know so far. Among these advances, intelligent and medical services are gaining lots of interest. Nowadays, AI-powered technologies are not only used in saving lives, but also in our daily life activities in diagnosing, controlling, and even tracking of COVID-19 patients. The AI-powered solutions are expected to communicate with cellular networks smoothly in the next generation networks (5G/6G and beyond) for more effective/critical medical applications. This will open the door for another interesting research areas. This book focuses on the development and analysis of Artificial Intelligence (AI) models applications across multi-disciplines. AI based deep learning models, fuzzy and hybrid intelligent systems, and intrinsic explainable model are also being presented in this book. Some of the fields considered in this smart health-oriented book includes AI applications in Electrical Engineering, Biomedical Engineering, Environmental Engineering, Computer Engineering, Education, Cyber Security, Chemistry, Pharmacy, Molecular Biology, and Tourism. This book is dedicated to addressing the major challenges in fighting diseases and psychological issues using AI. Challenges vary from cost and complexity to availability and accuracy. The aim of this book is hence to focus on both the design and implementation aspects of the AI-based approaches in proposed health-related solutions. Targeted readers are from varying disciplines who are interested in implementing the smart planet/environments vision via intelligent enabling technologies\"-- Provided by publisher.
Book
Deep Learning for Healthcare Decision Making
Health care today is known to suffer from siloed and fragmented data, delayed clinical communications, and disparate workflow tools due to the lack of interoperability caused by vendor-locked health care systems, lack of trust among data holders, and security/privacy concerns regarding data sharing. The health information industry is ready for big leaps and bounds in terms of growth and advancement. This book is an attempt to unveil the hidden potential of the enormous amount of health information and technology. Throughout this book, we attempt to combine numerous compelling views, guidelines, and frameworks to enable personalized health care service options through the successful application of deep learning frameworks. The progress of the health-care sector will be incremental as it learns from associations between data over time through the application of suitable AI, deep net frameworks, and patterns. The major challenge health care is facing is the effective and accurate learning of unstructured clinical data through the application of precise algorithms. Incorrect input data leading to erroneous outputs with false positives is intolerable in healthcare as patients’ lives are at stake. This book is written with the intent to uncover the stakes and possibilities involved in realizing personalized health-care services through efficient and effective deep learning algorithms. The specific focus of this book will be on the application of deep learning in any area of health care, including clinical trials, telemedicine, health records management, etc.
eBook
Drones in IoT-enabled spaces
\"This book addresses major issues and challenges in drone-based solutions proposed for IoT-enabled cellular/computer networks, routing/communication protocols, surveillances applications, secured data management, and positioning approaches. It focuses mainly on smart and context-aware implementations\"--Provided by publisher.
Book
Non-Contact Sensing Testbed for Post-Surgery Monitoring by Exploiting Artificial-Intelligence
Non-contact health care monitoring is a unique feature in the emerging 5G networks that is achieved by exploiting artificial intelligence (AI). The ratio of the number of health care problems and patients is increasing exponentially and creating burgeoning data. The integration of AI and Internet of things (IoT) systems enables us to increase the huge volume of data to be generated. The approach by which AI is applied to the IoT systems enhances the intelligence of the health care system. In post-surgery monitoring of the patient, timely consultation is essential before further loss. Unfortunately, even after the advice of the doctor to the patient, he/she may forget to perform the activity in the correct way, which may lead to complications in recovery. In this research, the idea is to design a non-contact sensing testbed using AI for the classification of post-surgery activities. Universal software-defined radio peripheral (USRP) is utilized to collect the data of spinal cord operated patients during weight lifting activity. The wireless channel state information (WCSI) is extracted by using orthogonal frequency division multiplexing (OFDM) technique. AI applies machine learning to classify the correct and wrong way of weight lifting activity that was considered for experimental analysis. The accuracy achieved by the proposed testbed by using a fine K-nearest neighbor (FKNN) algorithm is 99.6%.
Journal Article
Current Technologies for Detection of COVID-19: Biosensors, Artificial Intelligence and Internet of Medical Things (IoMT): Review
Despite the fact that COVID-19 is no longer a global pandemic due to development and integration of different technologies for the diagnosis and treatment of the disease, technological advancement in the field of molecular biology, electronics, computer science, artificial intelligence, Internet of Things, nanotechnology, etc. has led to the development of molecular approaches and computer aided diagnosis for the detection of COVID-19. This study provides a holistic approach on COVID-19 detection based on (1) molecular diagnosis which includes RT-PCR, antigen–antibody, and CRISPR-based biosensors and (2) computer aided detection based on AI-driven models which include deep learning and transfer learning approach. The review also provide comparison between these two emerging technologies and open research issues for the development of smart-IoMT-enabled platforms for the detection of COVID-19.
Journal Article
A Survey on Consensus Protocols and Attacks on Blockchain Technology
In the current era, blockchain has approximately 30 consensus algorithms. This architecturally distributed database stores data in an encrypted form with multiple checks, including elliptical curve cryptography (ECC) and Merkle hash tree. Additionally, many researchers aim to implement a public key infrastructure (PKI) cryptography mechanism to boost the security of blockchain-based data management. However, the issue is that many of these are required for advanced cryptographic protocols. For all consensus protocols, security features are required to be discussed because these consensus algorithms have recently been attacked by address resolution protocols (ARP), distributed denial of service attacks (DDoS), and sharding attacks in a permission-less blockchain. The existence of a byzantine adversary is perilous, and is involved in these ongoing attacks. Considering the above issues, we conducted an informative survey based on the consensus protocol attack on blockchain through the latest published article from IEEE, Springer, Elsevier, ACM, Willy, Hindawi, and other publishers. We incorporate various methods involved in blockchain. Our main intention is to gain clarity from earlier published articles to elaborate numerous key methods in terms of a survey article.
Journal Article