Article
Computer Science, Information Systems
Jiwoo Lee, Sohyeon Park, Young-Gon Kim, Eun-Kyu Lee, Junghee Jo
Summary: This paper proposes a model that utilizes both biometric and behavioral authentication, measuring the length of contact area of multiple fingers and utilizing secure geometric information generated by smart watch accelerometers, to address the security vulnerabilities and cost issues of traditional authentication methods such as fingerprint scanning.
Review
Computer Science, Information Systems
Umar Zaman, Imran, Faisal Mehmood, Naeem Iqbal, Jungsuk Kim, Muhammad Ibrahim
Summary: With the advancement of computing and communication technologies, the healthcare information processing paradigm is undergoing a transformation. The Internet of Things (IoT) has introduced security vulnerabilities and risks, which can be addressed through the use of blockchain (BC) technology. Additionally, artificial intelligence (AI) applications have the potential to greatly improve health diagnosis and monitoring practices. This study explores the integration of BC, IoT, and AI technologies to tackle the challenges faced in the healthcare sector.
Review
Computer Science, Information Systems
Ignacio Rodriguez-Rodriguez, Jose-Victor Rodriguez, Maria Campo-Valera
Summary: Type 1 Diabetes Mellitus (DM1) is a metabolic condition characterized by high blood sugar levels due to insufficient insulin production. Current methods of monitoring and managing blood glucose levels suffer from imprecision, but advancements in technology offer the potential for continuous and accurate monitoring and prediction. A holistic approach using intelligent data analysis and IoMT (Internet of Medical Things) can provide a comprehensive solution for managing DM1.
Article
Engineering, Electrical & Electronic
Shuqi Liu, Wei Shao, Tan Li, Weitao Xua, Linqi Song
Summary: This article reviews and categorizes the latest advances in user authentication for wearable devices, classifying them into physiological biometrics-based and behavioral biometrics-based methods. Features are extracted using signal processing techniques and user authentication is achieved using specially designed classification methods. Finally, evaluation metrics for user authentication in wearable devices are reviewed.
DIGITAL SIGNAL PROCESSING
(2022)
Article
Agriculture, Multidisciplinary
Ruiqin Ma, Shu Li, Xinxing Li, Buwen Liang, Yan Cui
Summary: This study used bio-sensing and modeling evaluation to accurately perceive and acquire key parameters by continuously monitoring the transportation environment and dynamically sensing the physiological conditions of meat sheep. It constructed a stress assessment method and a prediction model for transportation stress, and ultimately improved the reliability and quality control of meat sheep transportation.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2022)
Article
Computer Science, Information Systems
Mazin Alshamrani
Summary: The Internet of Things (IoT) and artificial intelligence (AI) are two rapidly growing technologies worldwide. The concept of smart cities aims to transform the healthcare sector by utilizing IoT and AI to improve efficiency, reduce costs, and prioritize patient care. This study surveys the most relevant health Internet of things (H-IoT) applications supported by smart city infrastructure and evaluates monitoring applications based on various IoT-based sensors.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2022)
Review
Health Care Sciences & Services
Anita Ramachandran, Anupama Karuppiah
Summary: Sleep apnea is a common sleep disorder that can lead to various health issues, but current diagnostic methods are expensive and inconvenient. Research shows that combining embedded systems and machine learning can make the diagnosis of sleep apnea easier, more affordable, and accessible.
Review
Computer Science, Information Systems
Muhammad Imran, Umar Zaman, Imran, Junaid Imtiaz, Muhammad Fayaz, Jeonghwan Gwak
Summary: This study comprehensively investigates the applications of IoT, machine learning, and blockchain in healthcare, highlighting the importance of these technologies and their future directions.
Article
Computer Science, Information Systems
Qihao Zhou, Kan Zheng, Kuan Zhang, Lu Hou, Xianbin Wang
Summary: This article investigates the taxonomy of security issues associated with smart contracts in the context of Blockchain-based Internet of Things (BIoT) applications. It proposes a tree-based machine learning vulnerability detection method to overcome the limitations of existing methods. The experimental evaluation demonstrates the effectiveness and efficiency of the proposed method.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Information Systems
Gaurang Bansal, Karthik Rajgopal, Vinay Chamola, Zehui Xiong, Dusit Niyato
Summary: The COVID-19 pandemic has revealed limitations in existing healthcare systems, leading to an increase in healthcare innovation and the use of metaverse technology to provide alternative healthcare systems. This paper presents a comprehensive survey of the latest developments in the healthcare industry using the metaverse, covering seven domains. It reviews metaverse applications, discusses technical issues and available solutions in each domain, and emphasizes the challenges that need to be addressed before fully embracing the metaverse in the healthcare industry.
Article
Computer Science, Information Systems
Gabriele Baldoni, Rafael Teixeira, Carlos Guimaraes, Mario Antunes, Diogo Gomes, Angelo Corsaro
Summary: This paper presents Zenoh-Flow, a dataflow programming framework that enables fully decentralized end-to-end machine learning applications and abstracts communication aspects. A real-world use case demonstrates the effectiveness of the framework, showcasing significant improvements in performance and network usage.
Article
Computer Science, Information Systems
Ignacio Rodriguez-Rodriguez, Maria Campo-Valera, Jose-Victor Rodriguez
Summary: This paper explores the use of IoMT for continuous monitoring of DM1 and applies wearable technologies and machine learning strategies to develop prediction models. The results demonstrate the accuracy of this approach in predicting blood glucose levels, offering an effective management method for DM1 patients.
INTERNET OF THINGS
(2023)
Review
Computer Science, Information Systems
Maha S. Diab, Esther Rodriguez-Villegas
Summary: The use of machine learning in medical and assistive applications is gaining attention, especially when combined with novel wearable devices. However, the computational demands of machine learning models often require transmitting data to remote cloud servers for inference, which is not ideal. The emerging field of Tiny Machine Learning (TinyML) aims to replace cloud servers with alternative inference devices closer to the sensing platform. This study addresses the gaps in literature regarding the use of MCUs as edge inference devices for healthcare wearables.
Article
Chemistry, Analytical
Kyle DeMedeiros, Abdeltawab Hendawi, Marco Alvarez
Summary: Machine learning and deep learning are commonly used tools for anomaly detection. As the number of Internet-connected devices increases rapidly, anomaly detection in IoT devices and sensor networks becomes critical. This paper surveys anomaly detection in sensor networks/the IoT, defines anomalies, and evaluates different approaches. The goal is to highlight how anomaly detection is performed in the Internet of Things, identify approaches, and address research gaps.
Review
Chemistry, Analytical
Eva Rodriguez, Beatriz Otero, Ramon Canal
Summary: Recent advances in hardware and information technology have accelerated the proliferation of smart and interconnected devices in the Internet of Things (IoT). This paper presents a comprehensive survey of Machine Learning (ML)- and Deep Learning (DL)-based solutions for privacy in IoT, including analysis of privacy threats and attacks, implementation details, and effective solutions.
Article
Computer Science, Artificial Intelligence
B. D. Deebak, Fadi Al-Turjman
Summary: This paper introduces the application of S-USI in cloud-based healthcare systems and proposes a robust secure-based S-USI mechanism and a coexistence protocol proof for pervasive services in the cloud.
COMPLEX & INTELLIGENT SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Fahim Ullah, Fadi Al-Turjman
Summary: Blockchain-based smart contracts are transforming the smart real estate sector in smart cities. This study explores the literature on blockchain smart contracts in smart real estate and proposes a conceptual framework for their adoption in smart cities. Through a systematic review of literature published between 2000 and 2020, ten key aspects of blockchain smart contracts are identified and organized into six layers. The study presents a decentralized application and its interactions with Ethereum Virtual Machine (EVM), along with a detailed design and interaction mechanism for real estate owners and users as parties to a smart contract. It also provides a stepwise procedure for establishing and terminating smart contracts, along with a list of functions for initiating, creating, modifying, or terminating a smart contract. The study has the potential to enhance the contracting process for users and create new business opportunities for real estate owners, property technologies companies, and real estate agents.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Aditya Khamparia, Babita Pandey, Fadi Al-Turjman, Prajoy Podder
Summary: This article presents a computer aided detection system for early knee osteoarthritis and rheumatoid detection using X-ray images and machine learning classifiers. The CAD system can be used remotely to assist medical practitioners in treatments of knee arthritis. The presented results show commendable improvement over different existing feature extractors in combination with different classifiers.
Article
Computer Science, Artificial Intelligence
Abdullahi Umar Ibrahim, Pwadubashiyi Coston Pwavodi, Mehmet Ozsoz, Fadi Al-Turjman, Tirah Galaya, Joy Johnson Agbo
Summary: This article provides an overview of the characteristics, historical pandemics, and diagnostic methods of coronaviruses. It emphasizes the need for rapid, sensitive, simple, and affordable diagnostic tools for the virus, and introduces AI-driven and CRISPR-based approaches for diagnosis and treatment. The article also highlights limitations of laboratory techniques and open research issues in the field.
JOURNAL OF EXPERIMENTAL & THEORETICAL ARTIFICIAL INTELLIGENCE
(2023)
Article
Computer Science, Information Systems
S. Ramesh, S. Nirmalraj, S. Murugan, R. Manikandan, Fadi Al-Turjman
Summary: The use of mobile devices and mobile applications have posed challenges to the infrastructure of mobile and wireless networking. This article proposes a method to handle the challenges of mobile sensor networks by providing secure and energy-efficient communication, enabling sensor node mobility and energy optimization.
JOURNAL OF SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY
(2023)
Article
Computer Science, Artificial Intelligence
Rajagopal Kumar, Fadi Al-Turjman, L. N. B. Srinivas, M. Braveen, Jothilakshmi Ramakrishnan
Summary: This paper proposes an Adaptive Neuro-fuzzy Inference System (ANFIS)-based machine learning technique to predict the possible outbreak of COVID-19 in India. The technique effectively tracks the growth of the epidemic and provides important information for public health control.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
S. D. Agashe, B. K. Lande, Vanita Jain, Gopal Chaudhary, Fadi Al-turjman
Summary: This paper proposes a new method for computing the optimal control, which steers the initial state of a system to a specified or unspecified point in the state space by minimizing a given performance index. The classical Calculus of Variations and the modern approach of variation in control that leads to Pontriagin's principle are compared. By deriving the maximum principle of Pontriagin using the classical Calculus of Variations modified with brief perturbation, an expression for the change in the value of performance index is obtained. Three examples are provided to demonstrate the feasibility of the derived methods.
Article
Automation & Control Systems
Arun Sekar Rajasekaran, Maria Azees, Fadi Al-Turjman
Summary: This paper provides a summary of V2G network characteristics, significance, security services, and challenges. It also offers an overview of various security attacks and related countermeasures to make V2G communications more secure.
JOURNAL OF CONTROL AND DECISION
(2023)
Review
Engineering, Electrical & Electronic
Rakesh Kumar Lenka, Hitesh Mohapatra, Fadi Al-Turjman, Chadi Altrjman
Summary: In this paper, the author surveys the most recent state-of-the-art routing protocols in WSN assisted IoT networks and highlights their limitations and future research directions.
INTERNATIONAL JOURNAL OF EMERGING ELECTRIC POWER SYSTEMS
(2023)
Article
Computer Science, Information Systems
Premkumar Chithaluru, Fadi Al-Turjman, Manoj Kumar, Thompson Stephan
Summary: The major challenges of IIoT include network resource management, self-organization, routing, mobility, scalability, security, and data aggregation. This article discusses the use of computational intelligence, specifically neural networks and fuzzy logic, to address the challenges of resource management in IIoT networks. Neural networks and fuzzy sets are considered suitable candidates for implementing computational solutions in IIoT networks.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Computer Science, Artificial Intelligence
Rakesh S. Kumar, Gayathri Nagasubramanian, S. Muthuramalingam, Fadi Al-Turjman
Summary: Analyzing real-time news feeds and their impacts in the real world is a complex task, especially in countries with a multilingual environment. Multilingual and multimodal news analysis is an emerging trend for evaluating news source neutralities. Four new deep news particle filtering techniques were developed in this work, which showed 15% to 20% better performance than conventional news analysis techniques.
ACM TRANSACTIONS ON ASIAN AND LOW-RESOURCE LANGUAGE INFORMATION PROCESSING
(2023)
Article
Clinical Neurology
Ali Rajabian, Saman Vinke, Joseph Candelario-Mckeown, Catherine Milabo, Maricel Salazar, Abdul Karim Nizam, Nadia Salloum, Jonathan Hyam, Harith Akram, Eileen Joyce, Thomas Foltynie, Patricia Limousin, Marwan Hariz, Ludvic Zrinzo
Summary: A study examined the use of intraoperative MRI (iMRI) to guide and verify lead placement during deep brain stimulation (DBS) surgery. The results showed that iMRI offers a high level of accuracy and safety in confirming lead placement. This is the largest series reporting the use of iMRI in DBS surgery, demonstrating its precision and safety.
JOURNAL OF NEUROSURGERY
(2023)
Article
Computer Science, Information Systems
Jegadeesan Subramani, Azees Maria, Arun Sekar Rajasekaran, Fadi Al-Turjman, Mahesh Gopal
Summary: Vehicular Ad-hoc Networks (VANETs) have potential for improving traffic management and driver safety, but there are security and privacy concerns in vehicle communication. This study proposes a blockchain-based physically secure and privacy-aware anonymous authentication technique to address these issues.
Article
Engineering, Multidisciplinary
Adedoyin A. Hussain, Fadi Al-Turjman
Summary: The internet of medical things allows patients to access flexible and virtualized devices over the internet, but task scheduling is a fundamental issue. A hybrid genetic algorithm AI method is proposed to improve task scheduling efficiency and reduce cost and time. This research can enhance the operational efficiency of the internet of medical things.
CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES
(2023)
Article
Mathematical & Computational Biology
Auwalu Saleh Mubarak, Zubaida Said Ameen, Fadi Al-Turjman
Summary: This article discusses the importance of identifying potholes on vehicles and introduces the method of developing object detection models using deep learning and computer vision techniques. The research results show that the model trained on images filtered using Gaussian smoothing performs the best.
MATHEMATICAL BIOSCIENCES AND ENGINEERING
(2023)