Connectivity Of Devices Research Articles

Navigating the Cyber Threat Landscape: An In-Depth Analysis of Attack Detection within IoT Ecosystems

The Internet of Things (IoT) is seeing significant growth, as the quantity of interconnected devices in communication networks is on the rise. The increased connectivity of devices has heightened their susceptibility to hackers, underscoring the need to safeguard IoT devices. This research investigates cybersecurity in the context of the Internet of Medical Things (IoMT), which encompasses the cybersecurity mechanisms used for various healthcare devices connected to the system. This study seeks to provide a concise overview of several artificial intelligence (AI)-based methodologies and techniques, as well as examining the associated solution approaches used in cybersecurity for healthcare systems. The analyzed methodologies are further categorized into four groups: machine learning (ML) techniques, deep learning (DL) techniques, a combination of ML and DL techniques, Transformer-based techniques, and other state-of-the-art techniques, including graph-based methods and blockchain methods. In addition, this article presents a detailed description of the benchmark datasets that are recommended for use in intrusion detection systems (IDS) for both IoT and IoMT networks. Moreover, a detailed description of the primary evaluation metrics used in the analysis of the discussed models is provided. Ultimately, this study thoroughly examines and analyzes the features and practicality of several cybersecurity models, while also emphasizing recent research directions.

Crafting high‐performance polymer‐integrated solid electrolyte for solid state sodium ion batteries

AbstractThe development of modern solid‐state batteries with high energy density has provided the reliable and durable solution needed for over‐the‐air network connectivity devices. In this study, a NASICON‐type Na3Zr2Si2PO12 (NZSP) ceramic filler was prepared using the sol‐gel method and then a polymer‐integrated solid electrolyte consisting of polyethylene oxide (PEO), NZSP, and sodium perborate (SPB) was prepared by Stokes' solution casting process. Through physico‐chemical and electrochemical characterization techniques, the morphology, electrochemical, and thermal properties of the prepared solid electrolyte sample were carefully studied. The PEO/NZSP/SPB electrolyte developed for all‐solid‐state sodium‐ion batteries (ASSSBs) exhibited a strong ionic conductivity, a large window for electrochemical stability, and was effective in controlling the growth of sodium dendrites. Furthermore, the polymer‐integrated solid electrolyte showed impressive rate capability, high discharge capacity (73.2 mAh g−1) at 0.1 mA cm−2, and good faradaic efficiency (98%) even after 100 cycles. These results reveal that the PEO/NZSP/SPB electrolyte is a potential and inevitable candidate for the evolution of high‐performance rechargeable ASSSBs.

SMART HOME ENERGY SAVING WITH BIG DATA AND MACHINE LEARNING

In response to escalating energy consumption, particularly within the housing sector, a global imperative to reduce energy usage has emerged, propelling the concept of "smart houses" to the forefront of innovation. This paradigm shift owes its genesis to the convergence of advancements in energy conversion, communication networks, and information technology, catalyzing the emergence of the Internet of Things (IoT). The IoT facilitates seamless connectivity of devices via the World Wide Web, enabling remote management, monitoring, and detection capabilities. Capitalizing on this technological synergy, the integration of IoT, big data, and machine learning with home automation systems holds immense promise for enhancing energy efficiency. This paper introduces HEMS-IoT, a groundbreaking energy control system for intelligent homes, underpinned by big data analytics and machine learning algorithms, prioritizing security, convenience, and energy conservation. Leveraging J48 neural network technology and the Weka API, the study illuminates user behaviors and energy consumption patterns, enabling household classification based on energy usage profiles. Moreover, to ensure user comfort and safety, RuleML and Apache Mahout are deployed to customize energy-saving recommendations tailored to individual preferences. By presenting a practical demonstration of smart home monitoring, this paper validates the effectiveness of the proposed approach in enhancing security, comfort, and energy conservation. This pioneering research not only showcases the transformative potential of IoT-driven energy management systems but also sets the stage for a sustainable and interconnected future.

Hearing outcomes following reimplantation of functional legacy cochlear implants

ObjectivesRecently, patients with certain legacy cochlear implants (CIs) have sought out reimplantation to enjoy the benefits offered by newer processor technology. This decision can be difficult, especially when the individual relies exclusively on the device for communication and scores at the ceiling of performance metrics. To date, most outcome data is derived from reimplantation of a non-functioning CI—a relatively easy decision. The aim of this study is to report hearing outcomes following reimplantation of legacy implants to guide surgeons and patients approaching this high-stakes clinical situation. Patients and interventionFour patients implanted with Advanced Bionics Clarion C1 devices over 20 years ago underwent reimplantation. ResultsThree reimplanted patients demonstrated a maintenance or improvement in their audiometric performance with one patient experiencing only a 5 % decrease in AzBioQ score. Each patient expressed satisfaction with the expansion of technological capabilities including improved battery life, and device connectivity. There were no failed reimplantations or other adverse effects. ConclusionsReimplantation of a functioning legacy CI result in stability or improvement in auditory performance. All individuals in this series report that they enjoy the new connectivity and programming technologies. As the rate advancement in CI technology continues to increase and newer device architectures emerge, these data will help to inform the decision to reimplant functioning devices.

Integration of E-Learning Platforms in Moroccan Higher Education: Assessing the Technological Leap and Addressing the Digital Divide Among Urban and Rural Students

The integration of e-learning platforms in Moroccan higher education has been a significant step towards modernizing the educational landscape. This study examines the adoption and impact of e-learning platforms in Moroccan universities, with a particular focus on the technological and socio-economic disparities between urban and rural areas. The research analyzes the availability and quality of internet connectivity and digital devices, as well as the challenges and barriers faced by students and educators. Additionally, the study explores the impact of e-learning on student engagement and academic performance, providing a comparative analysis before and after the integration of these platforms. The findings highlight the need for targeted interventions to bridge the digital divide and ensure equitable access to e-learning resources. Recommendations for improving digital infrastructure, providing financial support, and enhancing digital literacy are discussed to promote effective and inclusive e-learning in Morocco.

Typical and extreme scenario-based capacity and connection coordinated planning method for integrated energy hubs

An integrated energy hub (IEH) is a promising way to improve system operation efficiency by coordinating different types of energy vectors. By considering the collaborative interaction among different flexible devices. This study proposes a capacity and connection coordinated planning method for the IEH based on typical and extreme scenarios, which aims to promote the economic and reliable operation of the IEH with flexible devices. First, a directed graph-based IEH modelling method is formulated, through which various flexible devices, including energy storage devices, are formulated in a unified model. Second, to realise the coordinated optimisation of the capacity and connection of an IEH, a comprehensive planning method is proposed by considering multiple system requirements, e.g., construction costs, connection relationships, and operation modes. Finally, typical and extreme scenarios are simultaneously modelled into the proposed planning method to improve the system economy while ensuring operation reliability. The main innovations of the proposed planning method include the improvement of the graph theory based IEH formulation approach, the coordinated planning model for both capacity and connection of various devices, and the planning method considering the extreme and typical scenarios. The numerical simulation results illustrate that the proposed method improves the introduced reliability indicator by 7.40 % compared to the typical scenario method, and it can reduce the total annual cost by 1.71 % compared with fixed connection methods. Furthermore, the proposed method reduces the computation time to 0.08 % of that of the traditional planning method using a complete dataset while sacrificing only 0.91 % of the economic optimality.

Internet of Things in Healthcare

The health monitoring system plays a pivotal role in healthcare management. Internet of Things (IoT) technology is an emerging field that facilitates the connectivity of devices to the internet. Consequently, patient data can be transmitted to the cloud for accessibility via the internet, enabling doctors to remotely monitor patients and vice versa. This paper explores the services and applications of IoT in the context of health monitoring systems, while also addressing key challenges. Given the sensitive nature of patient health data, encryption techniques for data protection are also examined. Keywords—Challenges in IoT, Data protection, Encryption, IoT technology, IoMT.

Force Performance Analysis and Numerical Simulation of Assembled Ribbed-Slab Abutments

This study investigates the structural performance of assembled rib-plate bridge abutments (ARBAs) with two different connection methods: bull leg bolt and flange connections. In addition, we explored the bending and shear performance of the connection parts and related areas to assess the damage characteristics and modes of these ARBAs. Utilizing model testing, a numerical analysis was conducted to define the force performance of the ARBA, with reference to a cast-in-place rib-plate abutment. The research results indicate that the bearing capacity and deformation capacity of the cap part of the assembled ribbed slab abutment model with cow leg connections are lower than those of the cast-in-place structure. When the structure fails, a 45° diagonal crack develops from the cross-section at the mid-span joint to the connection between the rib slab and the cap, until the concrete protective layer at the joint is crushed, exhibiting a shear failure mode. The bearing capacity of the assembly rib plate type abutment cap connected by the flange plate is basically the same as that of the cast-in-place structure, and the deformation capacity is weaker than that of the cast-in-place rib plate type abutment. The expansion of structural cracks is consistent with that of the rib plate type abutment connected by the cow leg. When the flange plate at the mid span is damaged, the contact surface between the flange plate and the concrete is pried off, resulting in the inability of the structure to continue bearing, exhibiting a shear failure mode. Through numerical simulation, taking the stress performance of the integral cast-in-place ribbed slab abutment as a reference, the assembled ribbed slab abutment connected by the flange plate is basically consistent with the integral cast-in-place ribbed slab abutment in terms of ultimate load, concrete damage, and steel reinforcement skeleton stress, and the connection device has not yet reached the yield state. The ultimate displacement is slightly weaker than that of the integral cast-in-place ribbed slab abutment. By comparison, it can be seen that the ultimate bearing capacity of the assembled ribbed slab abutment connected by the flange is basically the same as that of the cast-in-place ribbed slab abutment, and the stress performance can reach an “equivalent cast-in-place”, making it the preferred solution for the assembled abutment structure. The finite element parameter analysis of the flanged ARBA revealed that the thickness of the stiffening ribs, the number of bolts, and length of the flange plate anchoring steel plate were proportional to the ultimate load-bearing capacity of the prefabricated ARBA. In the case of no change in the structural damage mode, considering the economic benefits and load-bearing capacity of the structure, the following parameter combinations of the flanged ARBA are recommended: a thickness of 30 mm of the stiffening ribs, the number of bolts is 12, and a length of 50 cm of the length of flange plate anchoring steel plate.

Optimizing fog device deployment for maximal network connectivity and edge coverage using metaheuristic algorithm

Fog computing emerged to address the limitations and challenges of traditional Cloud computing, particularly in handling real-time, heterogeneous, and latency-sensitive applications. However, the spread of Fog computing devices across the network introduces various challenges, especially concerning device connectivity and ensuring sufficient coverage to fulfil users’ requests. To maintain network operability, Fog Device Deployment (FDD) must effectively consider two crucial factors: connectivity and coverage. Network connectivity relies on FDD, determining the physical network topology, while coverage determines the accessibility of the Internet of Things (IoT) or edge devices. Both these objectives significantly impact the network performance and guarantee the network's Quality of Service (QoS). However, determining an optimal FDD method that reduces computation and communication overhead, and provides high network connectivity and coverage, is challenging. In this work, we propose an FDD algorithm that effectively connects the Fog devices for internal communication and covers maximum edge devices to entertain the requests. Firstly, FDD is formulated as a multi-objective optimization problem and then, an emerging metaheuristic Jaya Algorithm (JA) is applied to optimize the multi-objective function. The suitability of the JA, for the FDD problem, is substantiated by its rapid convergence and better computational complexity when contrasted with other contemporary population-based algorithms. In conclusion, the performance of the proposed method is assessed across a spectrum of benchmark-generated instances, each reflecting distinct Fog scenarios. The experimental outcomes showcase the proposed method's remarkable promise, especially when compared against state-of-the-art methodologies.

Strain Monitoring and Installation Adjustment of Satellite–Rocket Connection Device Based on Distributed Optical Fibers

In this study, a distributed optical fiber sensor was used for strain monitoring and installation adjustment of a satellite–rocket connection device under a preload. The distributed optical fiber sensor was installed on both the tape and the satellite docking frame, utilizing OFDR (Optical Frequency Domain Reflectometry) based on Backward Rayleigh scattering strain demodulation methods to precisely measure the strain distribution of both components when subjected to a preload. In order to deal with the uneven stress of the belt in the process of preloading, a finite element analysis was performed to obtain the strain distribution of the belt under preloading. The strain monitoring results of the optical fiber and strain gauge were compared, and the strain trend of the finite element simulation results was verified. Finally, the measured strain data were adopted to assist the installation and adjustment of the satellite–rocket connection device to achieve a uniform distribution of the preload. The experimental results showed that the standard deviation of strain at each position of the tape was reduced after adjustment. This study provides guidance for the installation of satellite–rocket connection devices.

Building a Full Stack Solution for Seamless Device Connectivity and Data Management

This paper involves developing a full-stack IoT application with a cloud server. The project encompasses defining the project scope, selecting suitable hardware, developing firmware/software for IoT devices, setting up a cloud server with IoT services, configuring data ingestion and storage, building a backend application for data processing, creating a frontend UI/dashboard, establishing bidirectional communication, conducting testing, deploying the applications, and implementing continuous monitoring and optimization. By following these steps, the project aims to create a comprehensive IoT solution that collects, analyzes, and visualizes data from connected devices, enabling remote monitoring and control.

A fast and plug-and-play mechanical connector for microfluidic chips

This article introduces a fast and plug-and-play mechanical connector for microfluidic chips. With this connection device, fast and pluggable connection between microfluidic chips and liquid storage tanks can be achieved, allowing microfluidic flow between the storage tank and the chip and between chips while ensuring airtightness and avoiding liquid leakage. The reason for liquid leakage and the maximum sealing pressure are theoretically analyzed from the perspective of surface tension. The relationship between different liquids (surface tension coefficient), air gap distance, and leakage pressure is explored. Furthermore, the effect of fast connection method and capillary connection method on liquid flow inside the chip is compared. The experiment shows that the flow rate using the fast connection method can reach at least 70% of that using the capillary connection method, and can gradually increase to 96% with increasing pressure and flow rate.

A Torpor-based Enhanced Security Model for CSMA/CA Protocol in Wireless Networks

Mobile wireless networks enable the connection of devices to a network with minimal or no infrastructure. This comes with the advantages of ease and cost-effectiveness, thus largely popularizing the network. Notwithstanding these merits, the open physical media, infrastructural-less attributes, and pervasive deployment of wireless networks make the channel of communication (media access) vulnerable to attacks such as traffic analysis, monitoring, and jamming. This study designed a virtual local area network (VLAN) model to circumvent virtual jamming attacks and other intrusions at the Media Access Control (MAC) layer of the Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) protocol. A Torpor VLAN (TVLAN) Data Frame Encapsulation and the algorithm for T-VLAN security in CSMA/CA were formulated and presented. A simulation experiment was conducted on the model using OMNeT++ software. The performance metrics used to evaluate the model were packet delivery ratio, network throughput, end-to-end channel delay, and channel load. The simulation results show that the TVLAN defence mechanism did not increase the channel load arbitrarily during TVLAN defence. similarly, the system throughput was shown to be 82% during TVLAN defence. Nevertheless, the network delay of the system during TVLAN defence was significantly high but the channel load was 297 when the TVLAN security mechanism was launched. These results demonstrate the model’s ability to provide a survivability mechanism for critical systems when under attack and add a security layer to the CSMA/CA protocol in wireless networks. Such a remarkable performance is required of a CSMA/CA infrastructure for improving the cybersecurity posture of a wireless network.

Design and application of a new type of switchable semi-closed sputum suction device for transfer

Sputum suction is a necessary measure to remove respiratory secretions and collect sputum specimens, and the traditional sputum suction device includes open and closed methods. However, the open sputum suction device can easily cause sputum splashing during operation, polluting the operator and the surrounding environment. The closed sputum suction device is more expensive than the open sputum suction device. Although it can be used repeatedly, the friction between the protective sleeve and the wall of the suction tube increases after repeated uses, which in turn affects the operation. In addition, the two sputum suction methods need to be connected to a sputum collector when the sputum specimen is collected. This process can easily lead to leakage and contamination of specimens, and at the same time increase the infection risk for patients. In order to overcome the above problems, the medical staff from the department of critical care medicine of the First Affiliated Hospital of Dalian Medical University invented a new type of switchable semi-closed sputum suction device, and obtained the National Utility Model Patent of China (ZL 2020 2 1564712.3). The device is composed of a suction device connection port, a sliding negative pressure switch, an adapter interface, a pipe body, a transparent film protective sleeve, a clip-on connection joint, and a sputum collector. The sliding negative pressure switch at the connection port of the suction device can realize one-person one-handed operation. The sputum collector is connected with the sputum suction device to ensure that the specimen is not exposed. The transparent film protective sleeve covers the sputum suction tube body to ensure that the whole process of sputum suction operation is pollution-free. The clip-on connection joint is connected with the artificial airway interface to avoid sputum splashing during sputum suction, and it is clamped immediately after operation to reduce environmental pollution. Compared with the existing sputum suction device, the new switchable semi-closed sputum suction device has a more reasonable design and lower cost, which is worthy of clinical promotion.

IOT and AI Implementations on Remote Healthcare Monitoring System

Abstract: "IoT and AI Implementations on Remote Healthcare Monitoring System using Raspberry Pi 3" seeks to revolutionize healthcare by integrating cutting-edge technologies into a cohesive system for remote patient monitoring. Leveraging the power of Raspberry Pi 3, Internet of Things (IoT) devices will be employed to collect real-time health data from patients in diverse locations. This data will then undergo sophisticated analysis through Artificial Intelligence (AI) algorithms, enhancing the system's ability to identify anomalies, trends, and potential health risks with a high degree of accuracy. The Raspberry Pi 3 serves as a versatile and cost-effective hub, managing the connectivity and processing requirements of the IoT devices. The system aims to provide continuous and proactive healthcare support by enabling remote monitoring of vital signs and timely interventions based on AI- driven insights. The outcomes of this project not only contribute to the advancement of healthcare technology but also address the growing need for scalable and accessible healthcare solutions in a rapidly evolving digital landscape.

Train-earth-grid coupling DC magnetic bias model for stray current diffusion

The DC magnetic bias phenomenon in transformers can result in increased noise and harmonic components. This study focuses on the DC magnetic bias generated by stray currents in the DC traction power supply system of neutral grounding transformers under multiple train operation conditions. A two-layer soil model is utilized to calculate geodetic potential, with rail potentials from both mainline and depot serving as sources for stray current within the model. Two paths of stray current intrusion into the transformer via the grounding network and cable armor layer from the Main substation have been modeled and analyzed. A simulation test has been designed to verify that the maximum error between experimental data and model calculation data is 8.87%. The implementation of a blocking connection device between the depot and mainline, as well as a change in grounding strategy for the metal protective layer, can effectively reduce DC bias magnetic current in the substation.

Buzz Characteristics Under Fluid–Structure Interaction of Variable-Geometry Lip for Hypersonic Inlet

Variable-geometry lip structures can effectively broaden the operating range and improve the performance of hypersonic inlets. However, the presence of connection devices leads to a significant reduction in structural stiffness, which can easily trigger fluid–structure interaction (FSI) issues of the lip. In this study, an in-house FSI program is employed to investigate the buzz characteristics under FSI of the lip for a hypersonic inlet. The results indicate that FSI induces instability in the downstream shock train, resulting in the premature occurrence of inlet buzz. The buzz mode induced by FSI significantly differs from the rigid inlet buzz. During the buzz induced by FSI, both violent and mild buzz modes coexist, with these two modes irregularly alternating. During the violent buzz, the inlet achieves a brief start, leading to a fundamentally different evolution of the flowfield structure compared to the rigid model. During the mild buzz, the inlet remains unstart, so the evolution of the flowfield structure is similar to that of the rigid model. In comparison to the rigid inlet buzz, the amplitudes of pressure fluctuations significantly increase, and the dominant frequency decreases for the buzz induced by FSI. Simultaneously, different evolution characteristics of flow frequencies within various inlet regions are observed. Additionally, performance parameters no longer exhibit regular cyclic variations, with significant amplifications in their amplitudes. This study deepens the understanding of the buzz characteristics under FSI of lips for hypersonic inlets and provides a novel perspective on the mechanisms underlying buzz occurrence.

MOBILE HEALTH (MHEALTH) INNOVATIONS FOR PUBLIC HEALTH FEEDBACK: A GLOBAL PERSPECTIVE

In recent years, Mobile Health (mHealth) innovations have emerged as a transformative force in the realm of public health, revolutionizing the way healthcare is delivered and monitored worldwide. This review presents a comprehensive overview of the latest advancements in mHealth technologies, focusing particularly on their role in soliciting and utilizing public health feedback on a global scale. The proliferation of smartphones and mobile applications has paved the way for novel approaches to healthcare delivery, monitoring, and data collection. Through leveraging the ubiquity and connectivity of mobile devices, mHealth initiatives have facilitated enhanced communication between healthcare providers and patients, enabling real-time monitoring of health metrics, adherence to treatment regimens, and timely interventions. One of the key aspects of mHealth innovations is their capacity to engage diverse populations and solicit feedback regarding various aspects of public health, ranging from disease outbreaks to healthcare service quality. Through interactive platforms and user-friendly interfaces, individuals can provide valuable insights, report symptoms, and participate in surveys, thereby contributing to the generation of actionable data for public health interventions. Furthermore, mHealth solutions have demonstrated significant promise in overcoming barriers to healthcare access, particularly in underserved and remote communities. By delivering health information, diagnostic tools, and remote consultations via mobile platforms, these innovations have expanded the reach of essential healthcare services, thereby bridging gaps in healthcare delivery and improving health outcomes on a global scale. However, challenges such as privacy concerns, technological literacy, and disparities in digital access persist, underscoring the importance of equitable deployment and user-centered design in mHealth initiatives. Moreover, the integration of mHealth solutions into existing healthcare infrastructure requires careful coordination among stakeholders, including policymakers, healthcare providers, and technology developers. Mobile Health (mHealth) innovations hold immense potential to revolutionize public health feedback mechanisms on a global scale. By harnessing the power of mobile technologies, these initiatives can empower individuals, enhance healthcare delivery, and inform evidence-based public health policies for a healthier future.
 Keywords: Mobile Health, mHealth, Public Health, Healthcare, Innovation, Review.

Performance evaluation of distributed multi-agent IoT monitoring based on intelligent reflecting surface

The advent of intelligent reflecting surface (IRS) technology has revolutionized the landscape of wireless communication systems, offering promising opportunities for enhancing the performance of Internet of Things (IoT) applications. This paper presents a comprehensive performance evaluation of multi-agent IoT monitoring systems leveraging IRS technology. We focus on three criteria for selecting IRS units and assess the impact on system performance. Specifically, we analyze the system performance by deriving an outage probability expression for each criterion. Our study begins by introducing the concept of IRS and its role in IoT monitoring. We then present three IRS unit selection criteria: optimal selection (OS), partial selection (PS), and random selection (RS). For each criterion, we mathematically model and analyze the system outage probability, shedding light on the reliability and connectivity of IoT devices. The outage probability expressions derived in this work offer valuable insights into the trade-offs associated with IRS unit selection criteria in the context of IoT monitoring. Additionally, our findings contribute to the optimization of multi-agent IoT monitoring systems, enabling improved communication performance and enhanced reliability.

Exploring IoT Integration for Innovative Advancements in Civil Engineering

Civil engineering developments have allocation with the recent trends of integration with IoT technologies and devices. This technology significantly improves automation and remote monitoring for various tasks in the construction process, building maintenance and safety, allowing operators to remain remote free ever than before. IoT is simply the connection of several devices to the internet as per the need. The real implication of IoT is beyond and complex than this. The IoT is meant to signify the establishment of entire networks of devices which are connected to the internet and with each other. Various sensors and monitors recognize the conditions, communicate them to online network or app, and transmit relevant information to your phone automatically. Internet of Things (IoT) is the technology that transforming construction industries, automate processes, and improves construction area and other relevant fields in civil like Global Positioning System (GPS), Water Resources Management and Water Supply, Smart Construction, Water & Waste Water Treatment, Traffic Management and Control, Waste Management, Concrete Technology, Environmental Impact Assessment & Monitoring and Smart Lighting System. This research paper covers implementation of IoT in all these fields of civil engineering and updating the current scenario. IoT is potentially used to increase the productivity, on-site safety, and operational efficiency. Through the placement of low-power sensors, managers can improve worksite visibility at every stage of a project in realtime, from planning to construction, and even task post-construction. The construction industry is bringing real-time information into processes that are long-standing. Internet of Things (IoT) devices and sensors are collecting job site data in a more affordable, efficient and effective way than can ever previously imagined. This latest technology represents exciting hikes forward in the civil engineering world. Foremost principles among these are integrated in this study for Internet of Things with the world of civil engineering.